Tech Inquiry

Reports of a
Silicon Valley/Military Divide
Have Been Greatly Exaggerated

Jack Poulson <>
July 7, 2020

  1. Overview
  2. Direct Contracting
  3. Subcontracting Estimates
  4. Company Nearest Neighbors
  5. Conclusions
  6. Appendix


We performed an in-depth analysis of all public US federal (sub)contracting data over the last four and a half years to estimate the rankings of tech companies, both in and out of Silicon Valley, as contractors with the military, law enforcement, and diplomatic arms of the United States.

Inspired by Mijente's groundbreaking report on the US tech companies supporting the Immigration and Customs Enforcement (ICE) agency of the Department of Homeland Security (DHS), we also ranked contractors with the Justice Department, Department of Defense (DoD), State Department, Agency for International Development (AID), and Agency for Global Media (AGM).

We hope to address the alarmist claims from the Chairman of the Joint Chiefs of Staff and corporate executives that a tech company -- namely, Google -- electing to not directly contribute to weapons systems is "treasonous" and part of a divide between Silicon Valley and the US military that is a "national-security threat". [1, 2, 3]

We separately address:

  1. The implication that defense contracting is rare in Silicon Valley -- the capacity question, [4] and
  2. That the Department of Defense appears to only publicly criticize U.S. tech companies facilitating authoritarian suppression of dissent as a means of demanding that they contract with the Department of Defense -- the human rights question.

The Alleged Silicon Valley/Military Divide: Capacity

Our analysis shows a diversity of contracting postures (see Tables 2 and 3), not a systemic divide from Washington. Within a substantial list of namebrand tech companies, only Facebook, Apple, and Twitter look to be staying out of major military and law enforcement contracts. [5, 6]

The accusations of treason stemmed from Google's 2018 release of its worker-demanded AI Principles; because one of the principles involved a commitment to not building weapons systems, Google promised to not renew its contract providing custom-built drone object tracking AI for a Joint Artificial Intelligence Center (JAIC) pathfinder project (Maven). [7, 8]  Months later, the company cited potential conflicts with their AI Principles, along with their missing government certifications, as their motivations for walking away from the Joint Enterprise Defense Infrastructure cloud competition. The missing certifications, as well as the near-certainty that the award would go to Amazon or Microsoft, indicated that Google was not so much exiting federal cloud contracting as limiting embarrassment from a loss.

This intuition was later born out through the company's deep involvement with the Department of Defense's efforts to include Artificial Intelligence / Machine Learning in the modernization of its battle networks: the Defense Innovation Initiative. [9]  Google's former CEO, Eric Schmidt, has chaired two of its components since their inception: the Defense Innovation Board (DIB) and the National Security Commission on AI (NSCAI). And, in May, Google Cloud poached the Executive Director of the DIB and then landed a secure cloud contract through its sibling, the Defense Innovation Unit (DIU). [10, 11]  On balance, Google's position became supporting the DoD's cloud and cybersecurity while avoiding direct contributions to weapons systems. [12]

Federal procurement data also suggests, contrary to popular narrative, that Palantir and Anduril are, financially speaking, modest players in the defense contracting space relative to Hewlett Packard (especially its spinoff, Perspecta), IBM, Microsoft, Dell Technologies, AT&T, Verizon, and Amazon. Even Accenture, through Accenture Federal Services, and Johns Hopkins University, through its Applied Physics Laboratory, rank substantially higher within the studied DoD and DHS agencies. [13]

We conclude that the US weapons and intelligence community dramatically overreacted to a prominent tech company democratically deciding to not contribute to weapons systems. [14]  In July 2019, as part of the Aspen Security Forum, Defense Innovation Unit director Michael Brown stated that coverage of Maven was "overblown" before pointing out that many tech companies, namely Amazon and Microsoft, understand that workplaces should not be democracies and that

"the place to exercise [concern over weapons systems] is at the ballot box and we need to support the government." [15, 16, 17]

The namebrand tech companies, universities, and tech-oriented traditional defense contractors, by and large, appear to be willing and able to modernize US battle networks. [18]

The Alleged Silicon Valley/Military Divide: Human Rights

We argue that two of the primary tech defense contractors, Microsoft and IBM, helped normalize their industry's suppression of human rights in exchange for market access. Despite the human rights messaging of Microsoft's head lawyer and lobbyist, the company has proactively suppressed dissent in Bing for more than a decade, and its subsidiary, LinkedIn, is infamous for doing the same; in early 2010 Bill Gates pointedly criticized Google for -- as it turns out, temporarily -- taking a principled stand for human rights. [19]  IBM's "safe city" products are known to have involved a video surveillance system for strongman Rodrigo Duterte in Davao City. And IBM's CEO having directly led sales of cataloguing equipment for Nazi Germany, which directly contributed to the Holocaust, is still defended by the company.

Similarly, Perspecta, a close Hewlett Packard affiliate/spin-off that dominates our chart of tech defense contractors, incorporates components of both Computer Sciences Corporation, which helped charter CIA rendition flights to secret prisons, and QinetiQ North America. QinetiQ, the privatization of England's former Defense Evaluation and Research Agency, has had former CIA Chief who personally authorized his agency's use of torture on its board. [20]

Another tech defense contractor, Cisco, has been in court since 2013 for not only helping custom-build China's "Golden Shield" project -- commonly known as the "Great Firewall of China" -- but even purpose-building a censorship, video surveillance, and "forced conversion" module for suppressing a dissident religious minority. Some of Cisco's internal marketing materials mentioning this work even leaked the day before a Senate human rights hearing. And despite Google's 2010-2018 public stance against suppressing dissent, Google's former CEO, and primary interface to the DoD, Eric Schmidt, has defended complying with authoritarian demands since 2006. [21]

Companies and executives which comply with authoritarian demands are only openly criticized by the US national security community if they do not significantly interface with the DoD. When they are willing to partner with the DoD, as is the case with Eric Schmidt and Reid Hoffman, they are welcomed as leaders.

Data Availability

Alongside this report, we are officially releasing the initial version of our procurement and lobbying explorer: In addition to providing summaries of over one hundred thousand companies' procurement and lobbying behavior, and lists of heavy-hitter vendors for over 100 government agencies, it includes custom nearest-neighbor utilities for finding lesser-known analogues of contractors.

Our manual curation of the noisy FPDS data is also made public in JavaScript Object Notation (JSON) via:

And since this work was sparked by a need to understand federal procurement data well enough to properly submit Freedom of Information requests for contracts, we are also releasing the responses to our requests. They involve three tech companies (two based in Silicon Valley):

  • A redacted contract, with Virginia-based Transvoyant, for the Air Force to test Transvoyant's software for a "Precise Predictive Logistics (P2L) Pilot" meant to produce a "LOGistics Common Operating Picture (LOGCOP)". The deliverables include:
    • "Situational (unit readiness, weapon system status) and battlespace (intelligence, political climates, adversary actions, weather) awareness in real-time and continuous" [emphasis ours],
    • "Visibility of missions (centralized repairs, supply chain, distribution networks) and operations (contingency and steady state) globally", and
    • "[The] ability to plan for operations now or anytime in the future, allows planners to adapt to dynamic situations that arise during currents operations and develop courses of actions (COAs)."
  • A redacted contract, with Palantir USG, Inc., for the Air Force to test Palantir's Gotham software for "Supply Chain Visualization and Analytics" to produce a "LOGistics Common Operating Picture (LOGCOP)".
  • The last response involves Pivotal Software -- a Dell Technologies subsidiary -- which is the largest recipient of funds from the Defense Innovation Unit. Pivotal's work on modernizing the Air Force's Air Operations Centers has been widely publicized, often alongside the tongue-in-cheek hashtag "#agileAF". The responsive documents to this request were provided on July 17, 2020.

Lastly, we make public our lists of annotated subcontract award summaries, which we describe in detail in a later section.

Analyzing Direct Contracting

This project began with the submission of a large number of Freedom of Information (FOI) requests, through the Office of the Secretary of Defense, for contracts relating to Silicon Valley's role in the Defense Innovation Initiative. Intermediate responses made clear that at least a passing familiarity with the Federal Procurement Data System was required. And due to the extended wait times, high redaction rates, and low response rates, we decided that a detailed study of the hundreds of gigabytes of federal procurement awards might prove intrinsically valuable, in addition to improving our ability to target future FOI requests.

While Tech Inquiry is entirely made up of tech workers, roughly our first year was spent pointedly avoiding the common pitfall of assuming that change is best achieved by throwing up a website and writing software. But such an acknowledgement of the centrality of organizing and communications should not prevent detailed curation and analysis of datasets that allow us to study up, such as databases of corporate registrations, corporate lobbying and political contributions, or, in the case of this report, military and law enforcement contracting.

Given that the author previously built recommendation systems for a major tech company, one of our first questions was whether the FPDS award data was rich enough to allow for the automatic retrieval of answers to questions of the form: "Which companies contract like Palantir?". As it turns out, the answer is yes -- we discuss our system for producing nearest neighbors of FPDS vendors in a later section. But, through our own usage of our tool, we found the following, more basic, questions to typically be more important:

  • What are all of the names a particular company is listed under?
  • Who are the parent and child companies -- if any -- of this company?
  • What is an informative website associated with this company?
  • What is this company's address and latitude/longitude? And is there an associated phone number?
  • Which agencies does a particular company primarily contract with? And how much money have they received from each?
  • Which companies (perhaps including all of their subsidiaries) receive the most money from a particular agency?
  • What are the most recent awards received by a particular company?
  • What are the biggest awards ever received by a particular company?
  • What is the parent award, if any, of a particular award? Or, from the opposite perspective: what are the subawards?
  • Which awards contained a particular phrase (e.g., "facial recognition" or "aws govcloud")? And what vendors and agencies were they associated with?
  • Who are the subcontractors of a particular company? And how much money did they receive from subcontracting?

Of all of these questions, the last turns out to be the most critical -- and, by far, the most laborious -- for understanding tech defense contracting, and we delay its discussion to a later section. The others can be fairly quickly answered in each instance through the curation of a Postgres database of geocoded FPDS award data with an associated interface (in our case,

But it is helpful for us to take a step back and briefly review the context of US federal procurement data before diving into the structure of the associated data feed and how we extract answers to our above questions from it.

Overview of the Federal Procurement Data System and its Curation

For an in-depth overview of the roots of U.S. federal procurement, dating back to the Revolutionary War, we highly recommend The U.S. Federal Procurement System: An Introduction by Christopher R. Yukins. But this report only involves the Federal Procurement Data System (FPDS), which, since 2010, has been run by IBM through the General Services Administration. At roughly 1:30AM ET each day, anywhere from 10,000 to 100,000 new award modification summaries are made available through an ATOM feed provided by the official source for FPDS data, [22]

While FPDS is the definitive source for US federal procurement data, it is known to have numerous shortcomings, such as inconsistencies and and inaccuracies in award amounts, slow and incomplete uploads from contract officers (including 90 day delays for DoD procurement), and corrections frequently taking place years after the signing data. The Government Accountability Office (GAO) issued a report in late 2019 covering many such shortcomings.

One of the more delicate issues is that FPDS integrates the proprietary Data Universal Numbering System (DUNS), an assignment of a nine digit number to each business entity. Beyond accuracy and precision issues associated with DUNS, bulk dissemination of FPDS data is alleged to violate the intellectual property of the owner of the data, Dun & Bradstreet. [23]  As a result, we avoid overreliance on DUNS information (which includes some information on parent companies) and manually maintain our own vendor name normalizations and corporate parentage hierarchies.

Anatomy of an FPDS Award

To give a concrete example of what type of data exists in the FPDS ATOM feed, a boiled down version of the JSON equivalent of the October 2019 JEDI award, which went to Microsoft, is shown in Figure 1.

 "title": "New IDC HQ003420D0001 awarded to MICROSOFT CORPORATION for the amount of $0",
 "content": {
  "IDV": {
   "contractID": {
    "IDVID": {
     "PIID": "HQ003420D0001",
     "modNumber": "0"
   "relevantContractDates": {
    "signedDate": "2019-10-25 00:00:00",
    "effectiveDate": "2019-10-25 00:00:00",
    "lastDateToOrder": "2030-10-24 00:00:00"
   "dollarValues": {
    "obligatedAmount": "0.00",
    "baseAndAllOptionsValue": "10000000000.00"
   "totalDollarValues": {
    "totalObligatedAmount": "0.00",
    "totalBaseAndAllOptionsValue": "10000000000.00"
   "purchaserInformation": {
    "contractingOfficeAgencyID": {
     "@departmentName": "DEPT OF DEFENSE"
    "contractingOfficeID": { "@name": "WASHINGTON HEADQUARTERS SERVICES" },
    "fundingRequestingAgencyID": {
     "@name": "DEPT OF DEFENSE",
     "@departmentName": "DEPT OF DEFENSE"
    "fundingRequestingOfficeID": { "@name": "DOD CIO" }
   "contractMarketingData": {
    "websiteURL": "HTTPS://WWW.CLOUD.MIL",
    "whoCanUse": "DEFENSE",
    "emailAddress": "",
    "maximumOrderLimit": "1000000000.00",
   "contractData": {
    "contractActionType": { "@description": "IDC" },
   "vendor": {
    "vendorHeader": { "vendorName": "MICROSOFT CORPORATION" },
    "vendorSiteDetails": {
     "vendorLocation": {
      "streetAddress": "1 MICROSOFT WAY",
      "state": { "@name": "WASHINGTON", }
      "ZIPCode": {
       "@city": "REDMOND",
       "#text": "980528300"
      "countryCode": { "@name": "UNITED STATES" },
      "phoneNo": "5713532701"
     "vendorDUNSInformation": {
      "DUNSNumber": "081466849",
      "globalParentDUNSNumber": "081466849",
      "globalParentDUNSName": "MICROSOFT CORPORATION"
   "competition": {
    "extentCompeted": { "@description": "FULL AND OPEN COMPETITION" },
    "solicitationProcedures": { "@description": "NEGOTIATED PROPOSAL/QUOTE" },
    "numberOfOffersReceived": "7"
   "transactionInformation": {
    "createdBy": "ANGELA.DEREN.HQ0034@WHS.MIL",
    "createdDate": "2019-10-29 13:24:08",
    "lastModifiedBy": "HABERLACHJ",
    "lastModifiedDate": "2019-10-31 16:12:48",
    "status": { "@description": "FINAL" }

Figure 1: A small, relevant subset of a JSON translation of the official FPDS XML (via the python xmltodict module) for the original award to Microsoft for the Joint Enterprise Defense Infrastructure (JEDI) contract.

We can read off a number of useful conclusions from this -- again, truncated -- snippet:

  • The Procurement Instrument IDentifier (PIID) for JEDI is HQ0034-20-D-0001.
  • The original JEDI award was signed, and also made effective, on October 25, 2019. Whereas the last modification to this original award was October 31, 2019 (and an email address associated with the modifier is provided).
  • There is no legally obligated amount, whereas the potential value of the contract, if all options become exercised, is $10B.
  • The award was contracted through the Washington Headquarters Service but was requested by the DoD's Chief Information Officer (as it happens, later awards moved the requesting agency down to the Defense Information Systems Agency).
  • The official description of the award is to provide:
    Enterprise level, commercial Infrastructure as a Service (IAAS) and Platform as a Service (PAAS) to support Department of Defense business and mission operations.
  • Microsoft's listed address is:
    1 Microsoft Way
    Redmond, WA 98052-8300
    and their listed phone number is (571) 353-2701. While the address of large companies, such as Microsoft, is readily available, aggregated lists for obscure contractors are somewhat rare. This consistent source for company addresses is behind our ability to show maps of geocoded headquarters for the vast majority of federal contractors.
  • Microsoft's associated DUNS number is 081466849, and it has no listed parent company (technically, the award lists its parent as itself).
  • The award is claimed to have undergone a full, open competition that received 7 offers.
We underline that, on a typical day, between twenty and thirty thousand new award summaries are made public via the FPDS ATOM feed.

Three Measures of Contract Value

One of the significant complications in analyzing federal procurement is that there is no straight-forward answer for how to measure money-flow. One of the best such examples is the above JEDI award, which reports a minimum, or "obligated" award amount of zero, and a "base and all options" -- or "potential" -- value of ten billion dollars. That is to say, the minimum amount of the award was set to zero, and the maximum amount was set to ten billion, and the actual value could be anywhere in the middle. This was pointedly explained by the Department of Defense's Chief Information Officer, Dana Deasy:

"People think JEDI is a 10-year, $10 billion contract. It’s not – not necessarily. While that’s the maximum value and duration of the contract, the Pentagon has the option to terminate it after two years. There’s another end-it-or-extend-it decision three years later, and a third three years after that. The minimum the winning contractor is guaranteed to get? Just $1 million over two years."

To understand a possible source for the million dollar floor on the contract value, we incorporate two further complications:

  • Awards often cannot be analyzed in isolation -- they can have both modification awards (using the same PIID) and subawards (which reference the original award's PIID).
  • There are not just lower and upper bounds on contract values -- the "obligated" amount and "potential", a.k.a. "base and all options" value -- but also a typically more accurate lower bound, called the "current", or "base and exercised options" value.

Figure 2: A subaward to the original JEDI award showing all three contract value types as one million dollars.

One of the several subawards to the original JEDI award is shown in Figure 2, with each of the three measures of contract value set to the same mysterious one million dollar floor value mentioned by Deasy. But we emphasize that one should not expect FPDS award data to always be correct: a 2017 Government Accountability Office report claimed that less than one percent of awards are fully consistent!

The takeaway should be that, when FPDS award data is consistent, the running totals of the contract values should satisfy the ordering: \[ \text{obligated} \le \text{current} \le \text{potential}. \] In several extreme cases, typically involving DoD contracts run through the GSA's Federal Acquisition Service (FAS), both the "obligated" and "current" contract values are zero, while the "potential" value is almost exactly one trillion dollars.

We therefore argue that it is a serious, qualitative mistake to pick any one of these three contract values as representative. Our approach is to recognize the noise and inconsistency in FPDS data and instead focus on companies' rankings within government agencies when sorted by contract values.

Which contract value should we sort by to determine rankings? We do so for all three, and then take the most significant of the three results -- that is, the highest ranking -- as a numerical indicator of influence of a company on a particular agency. To give a specific example: we measured IBM as the 2nd largest vendor with the DHS's Customs and Border Protection by obligated amount, 3rd largest by current values, and 19th largest by potential values. As a result, we set IBM's influence ranking with CBP as 2nd. By focusing on per-agency rankings, rather than dollar amounts, we help avoid coming to misleading conclusions due to systemic idiosyncrasies and imprecision in agency data.

Normalizing Company Names

Most questions that we would like to investigate involve aggregating large numbers of awards for each vendor, which therefore requires adoption of some form of company identifier. An obvious approach would be to set this to the DUNS number, but, for the accuracy and intellectual property reasons described above, we instead use a specific spelling of the business name (potentially qualified with the state of incorporation) and manually curate a list of corrections from encountered misspellings (possibly restricted to its pairing with a particular DUNS numbers).

While our JEDI award example properly provided Microsoft's (lowercased) name as "microsoft corporation", this is far from always the case. Our current normalization map includes corrections from the encountered misspellings: "microsoft corporation sitz in", "microsoft corporation sitz in redmond corporation", and "microsoftcorporation".

To demonstrate why we also allow for the restriction of vendor name modifications to particular DUNS numbers, we take the -- exceedingly complicated -- example of the major defense contractor Science Applications International Corporation (SAIC).

In 2013, the company decided that it could avoid legal barriers arising from conflicts between different contracts by splitting off its legacy national security unit. Rather than making the reasonable choice of giving the spun-off company a new name, because the spin-off would be maintaining legacy contracts, they gave the spin-off the name SAIC and renamed the parent company Leidos (taken from the middle of the word "kaleidoscope").

As a result of the SAIC corporate shell game, knowing when to rename an occurrence of "SAIC" to "Leidos" requires knowledge of an extensive list of DUNS numbers (it turns out, more than 60 in this case) to build custom normalization rules around. These rules, and more than 9000 others, can be found in our vendor normalization map.

Normalizing Requesting and Contracting Agencies

As was the case for vendor name spellings, we can substantially improve the accuracy and consistency of the listings for the contracting and requesting agencies for an award. Our above approach can be adopted through the analogy: DUNS is to vendor name as office name is to agency name. That is, we build a normalization map that corrects listed agency names and provide overriding exceptions for specific pairings of offices and agencies.

For example, in the Microsoft JEDI award of Figure 1, the requesting agency identifier sets both the "@name" (which typically refers to the agency level) and "@departmentName" (which typically refers to the parent department of the agency) to "DEPT OF DEFENSE". A reasonable default rule is to normalize such a pairing to a unique string associated with the DoD -- we standardized on "Defense".

But we have the side information that the requesting office name was given as "DOD CIO", which refers to the DoD's Chief Information Officer. We therefore override our agency normalization map to normalize to "Defense: OCIO" when the agency was simply listed as the DoD but the office name is "DOD CIO". This rule, along with more than 650 others, can be found in our current agency normalization map.

We note that there exist interesting agencies, such as the National Security Agency and the National Reconnaissance Office, which we have only observed through the requesting office rather than the requesting agency. And several other agencies, such as the Defense Intelligence Agency (DIA), are often obscured as simply being the Department of Defense in the agency field -- in the case of the DIA, we often made use of the office being an obvious reference to the Defense Attache System. We corrected many such improper coarsenings up to the Department of Defense via a manual review of the list of all occurring pairings of agencies and offices.

Mapping Out Parent Companies and Subsidiaries

The defense contracting space is notorious for its frequent mergers, acquisitions, spin-offs, and even more exotic exchanges, such as the spin-merger. For example, when we colloquially refer to "Hewlett Packard", we mean a network of four affiliates: the personal computer company HP Inc., the enterprise IT provider Hewlett Packard Enterprise (HPE), HPE's B2B spin-merge DXC Technology, DXC's spin-off of its public sector segment, Perspecta, and all of their subsidiaries.

Two of HPE's major subsidiaries include:

When we speak of the sum of contracts between HPE and a particular agency -- for example, the Defense Information Systems Agency -- we could either be referring to the contracts awarded directly to HPE (an "exclusive" count), or all awards to HPE, HPE Government, Cray, and its other subsidiaries (an "inclusive" count). For this report, we focus on inclusive counts.

As mentioned in our discussion of the JEDI award, FPDS DUNS information sometimes provides a hint for a single parent company. But, for the same reasons which we avoid overdependence on DUNS information for unique vendor identifiers, as well as the fact that many companies have multiple parents (e.g., all joint ventures), we manually curate our own JSON map of parent companies. Our current map contains more than 5000 parent links, which, in combination with our vendor and agency normalization maps, allows us to automate inclusive award sums for a large number of pairings of vendors and agencies.

As another layer of complication, we consider HP, HPE, and Perspecta to be affiliates, not parents or subsidiaries of each other. And so when we compute influence rankings of the nebulous "Hewlett Packard" network, we use the maximum influence ranking between HP, HPE, and Perspecta. In almost all cases, this corresponds to Perspecta's influence rank.

Logistics of Data Retrieval and Indexing

At this point, we are ready to describe the construction of a table of direct contracting influence rankings, but we take the opportunity to add in the logistical details of efficiently retrieving, searching, and summarizing the federal procurement data.

As mentioned in the FPDA ATOM feed FAQ, each pull from the ATOM feed is limited to retrieving only ten records, but up to ten simultaneous requests are allowed -- which combines to up to 100 simultaneous award requests. Given that 30,000 to 100,000 award modifications are not unusual, performing multithreaded retrievals leads to very significant savings (often, from an hour down to a few minutes). And while the FAQ recommends 9AM ET retrievals, we find that the data is typically available around 1:30AM ET.

One can get an idea of the storage requirements for mirroring and indexing the entire FPDS database by reading the database guide: more than 1.5TB of hard disk space are required for their system. Getting access to this much space on DigitalOcean would cost $500 per month, which is out of the price range of our small, grassroots non-profit.

We therefore adopt a two-tiered approach: we store an entire copy of the raw FPDS data (converted into JSON via python's xmltodict module) on a private workstation and export salient subsets to CSV for loading into a Postgres database with full-text search indices. We then expose an interface to the indices via our public website,, which is a straight-forward combination of Express.js, jQuery, Pug, and Leaflet.

Addresses for companies are retrieved from the procurement awards and geocoded via a combination of geocodio (for U.S. addresses) and Nominatim (for international addresses).

Our lists of "similar contractors" for vendors are generated by extracting nearest neighbors from the results of the embedding processed, which we execute on a private workstation, described in a later section.

Building a picture of direct contracting influence

We can now combine all of the previously discussed FPDS curation mechanisms to compute maximum ranks of direct financial flow between various tech-related companies and U.S. federal agencies -- which we treat as proxies for influence/impact. Brief summaries of many of the studied companies are available in a section of the appendix.


For the sake of brevity, we will simply list the agencies of focus rather than providing short summaries. One exception is the Justice Department's Offices, Boards, and Divisions (OBD) unit, which is less widely documented. We recommend the book Badges without Borders (or the associated interview with, which details the history of the international, often explicitly anti-communist, policing programs once run through USAID's Office of Public Safety. These programs transitioned into the Justice Department's International Criminal Training Assistance Program (ICITAP) under the OBD agency. There are numerous recent awards from this program to Science Applications International Corporation and its subsidiary, Engility Holdings, for international policing in Indonesia, the Kingdom of Saudi Arabia, and Pakistan.

For the Justice Department as a whole, we investigate rankings within:

From the Treasury Department, we only include the Internal Revenue Service (IRS).

Several members of the Department of Homeland Security are of interest:

The largest number of agencies are from the Department of Defense:

Lastly, we include rankings within several independent agencies:

HP / Perspecta 21 311 31 828 7 3 10 6 6 41 13 82 7 25 302 35 225 365 10 20 80 635 165 5
Deloitte 8 51 6 172 2 27 14 24 152 7 42 125 21 97 13 94 16 38 297 47 17 12 925 15
MITRE 2 24 285 469 1 23 49 34 80 109 2 16 85 26 1 6471 100 1 155 247 451 955
IBM 24 75 3 2483 3 286 88 2 1118 10 221 137 118 27 143 61 62 23 18 19 241 25 302 18
Accenture 10 100 17 412 1 602 56 28 18 8 92 99 49 2438 62 40 126 80 34 3 13 197 33
AT&T 99 37 1 248 6 7 95 18 171 294 219 109 107 60 126 85 2019 24 9 891 32 70 26 20 15 38
Microsoft 128 105 33 1528 1463 68 146 66 37 75 255 102 253 113 364 441 1 2 57 561 490 448
Verizon 32 28 23 296 12 6 163 133 26 359 234 132 72 257 76 1134 595 1 204 47 553 2073 39 59
Dell 56 241 343 8396 53 20 4 28 33 30 123 38 252 47 64 59 307 63 26 1612 28 539 446 73 14
Johns Hopkins 5550 144 261 43 36 183 23 231 45 861 5 104 13 29 5 428 71 4814
IDA 17,896 62 1 1629 1150
Cisco 3250 2580 301 309 175 717 6 98
Palantir 44 3265 25 84 27 10,015 763 468 14 946 1208 1531
Oracle 1873 931 294 266 292 684 825 388 642 2270 111 315 337 40 142 175
Anduril 163 1255 5788 100 49
NVIDIA 5671 95
Intel 5504 11,060 91,055 102 12,104
Apple 1593 809 7400 1356 509 5380 19,124 20,847 13,639 3538 18,757 2039 1473 392 156
Google 8951 76,708 17,248 2227 2908 255 12,353
Amazon 1176 1096 6559 733 3219 13,141 7472 19,578 1208 730 1013 1895 986 1314 841
Facebook 8902 3054 1498
Twitter 1009
Table 1: Corporate influence rankings by contracts directly between various tech-related companies and U.S. agencies between the beginning of 2016 and July 4, 2020.     Measurements were generated by combining all awards listed in the Federal Procurement Data System (FPDS) which were signed or modified within the time window. In order to smooth out known inconsistencies and FPDS data, companies were ranked by each of the three ways to measure contract values (obligated, current, and potential) and their influence was set to the most significant (that is, smallest) of the three ranks.     These influence rankings were then binned as either: top 10 (       ), top 25, (       ), top 50, (       ), top 100, (       ), top 250, (       ), top 500 (       ), top 1000 (       ), or below (       ). If a company was not observed contracting with an agency, the square was left white. The numerical influence rankings are shown on mouse-over.

Even though we have restricted the analysis behind the influence rankings in Table 1 to direct contracts -- which misses, for example, a high-profile $25M (base and all options value) award between TRANSCOM and Amazon through ECS Federal -- we can interpret the results as underestimates. Given this caveat, we immediately notice that the Hewlett Packard network of companies noticeably dominate, with top-10 influence rankings in 8 of the 26 agencies. [25]

Equally as surprising is that consulting companies Accenture and Deloitte Consulting -- which contributed much of the award money to parent company Deloitte -- were more influential via direct contracting than essentially every tech company except HP and IBM. Next after the management consulting companies is the not-for-profit MITRE Corporation, which was built specifically to manage Federally Funded Research and Development Centers (FFRDCs); its high rankings should thus serve more as a benchmark than a surprise. We underline that it ranked first with the DIA, NGA, and DHS S&T, and second with the FBI.

If we restricted our attention to the "Big Five" tech companies: Google, Apple, Facebook, Amazon, and Microsoft, then a purely direct contracting analysis would suggest that Microsoft is the only significant defense contractor -- which, again, misses the numerous multi-million dollar Amazon Web Services awards passed through subcontracts (such as ECS Federal and JHC Technology). The question of how to account for more commoditized relationships -- namely, Intel, NVIDIA, and Apple hardware sales -- is more complicated, and we will partially address it in the next section.

We also notice the minor influence rankings of Palantir and Anduril relative to: management consulting companies, HP, Dell, telecoms, and even the Johns Hopkins Applied Physics Laboratory (which is responsible for the vast majority of awards to Johns Hopkins). Palantir's highest influence was within the U.S. Special Operations Command, who publicly praised Palantir's software during their years-long struggle to win the DCGS-A contract (and a subsequent "capability drop"). Anduril's biggest influences are observed as through DARPA, the Washington Headquarters Service, and Customs and Border Protection; direct inspection of their awards reveals, for example, a $250M (base and all options value) award through CBP for "autonomous surveillance towers" and a $100M (base and all options value) award requested by DARPA and contracted through the Air Force for "advance[d] battle management anduril phase 3 idiq". [26, 27]

A few of the agency columns are worth dedicated discussion. For example, Microsoft's second place influence rank within the Defense Information Systems Agency is entirely due to the $10B (base and all options value) JEDI award -- only Leidos ranked higher -- and so the award being transferred to Amazon due to a bid protest would give it the same position. The other top-ten influencers within DISA, unsurprisingly, included several communication infrastructure companies: Verizon, Cisco, and AT&T, as well as HP (IBM was 18th, and Dell was 26th).

The column combining the National Security Agency and the U.S. Cyber Command -- which we note only has a modest amount of reported awards -- contains top-ten rankings for Accenture (3rd) and Johns Hopkins (5th), but known NSA contractors Dell and AT&T were only 28th and 70th, respectively. The FBI rankings, like many others, show the professional services companies, Accenture and Deloitte, as heavier-hitters than tech giants. Nevertheless, Perspecta and IBM are both in the top 25, Verizon and Palantir are in the top 50, and Dell and AT&T are in the top 100.

As we will see in the next section, Palantir and Anduril's results are not significantly changed by incorporating subcontracts -- indeed, Anduril's are not changed at all -- and so, if they are setting the bar for what it means for a tech company to be a defense contractor, then HP, IBM, Microsoft, Dell, Cisco, AT&T, and Verizon are more than meeting it, even without incorporating their subcontracting passthroughs. And that Intel chips are a core component of most HP and Dell machines suggests we should already be able to justify its addition it into the list.

Incorporating Conservative Subcontracting Passthrough Estimates

We now discuss our approach for incorporating conservative subcontracting estimates into the direct contracting influence rankings of the last section (summarized in Table 1). Our approach was simple, yet exceedingly laborious:

  1. Generate a list of awards whose descriptions include key terms (we built a custom API to return such lists in a minimal JSON format).
  2. Manually remove all awards not attributable to the target company after direct inspection.
  3. Expand out to the entire award series of those that remain and annotate each such award with an estimated passthrough percentage.
  4. Augment the three types of total award amounts from the direct award analysis by adding in the products of the subcontract values and their estimated passthrough rates.
  5. Re-rank.
In practice, we combine steps (2-4) so that we need only perform a single pass through the original list. And we first sort the awards by maximum absolute value so that the most impactful items are handled first.

This process was repeated for ten companies, and, when restricted to our agencies of study, resulted in:
Keywords Kept subcontracts* Major intermediaries
Microsoft "microsoft" or "azure" or "windows licenses" or "windows server" 6860 subcontracts
(443 cloud,
6417 non-cloud)
Dell, CDW Corporation, Insight Enterprises,
and Minburn Technology Group
Amazon "amazon" or "aws" or "govcloud" 477 subcontracts Four Points Technology, JHC Technology, and ECS Federal
Google "google" 384 subcontracts The Daston Corporation, DLT Solutions, Eyak Technology,
and Dnutch Associates
Facebook "facebook" 172 subcontracts Chaise Management Group, Sage Communications, and ZilYen (now doing business as Forge Branding)
NVIDIA "nvidia" or "tesla" 163 subcontracts General Dynamics Mission Systems, Iron Bow Technologies,
FCN, Inc., and DH Technologies
Twitter "twitter" 43 subcontracts Sage Communications, ZilYen (now doing business as Forge Branding), and Chaise Management Group
Palantir "palantir" or "gotham" 26 subcontracts i3 Federal, Pat V. Mack, Sava Workforce Solutions, and Affigent
IDA "institute for defense analyses" 7 subcontracts telecoms (e.g., AT&T)
MITRE "mitre" 6 subcontracts MIT: each award was for "mitre-lincoln laboratory research&development"
Johns Hopkins "johns hopkins" 2 subcontracts
Anduril "anduril" 0 subcontracts

*: We emphasize that these counts of the number of manually annotated contracts -- which we colloquially described as the number of "kept subcontracts" -- contain a small percentage of awards that simply make reference to the company in question. In such cases, the percentage of money estimated to be passed through to the company is set to zero. Such awards are kept in the list to help demonstrate that a simple keyword search is insufficient.

As part of the subcontract review process, we noticed that, during the 2005-2011 time period that an Alaska Native subsidiary, Eyak Technology, was operating a kickback scheme relating to its billion-dollar prime contract with the U.S. Army Corps of Engineers, it was also serving as a supplier of Google technology to the U.S. Army through numerous awards in 2009. We also discovered that Amazon, through JHC Technology, has received several million dollars in AWS cloud contracts through the Federal Bureau of Prisons.

It also became clear that many of the NVIDIA subcontracted awards were for the acquisition of their DGX compact General-Purpose Graphics Processing Unit (GPGPU) supercomputers. Recipients included: The Army, Navy, Air Force, Washington Headquarters Service, and, most surprisingly, even Veterans Affairs.

While we would have preferred to have performed similar analyses for the remaining companies, we remind the reader that such analyses only increase ranks. Thus, incorporating any missed subcontracts for HP, Deloitte, IBM, AT&T, Verizon, and Dell would only make them more dominant. The opportunities for significant qualitative change are with extending our subcontract analysis to Appl, Cisco, Oracle, and Intel.

HP / Perspecta 21 311 32 829 7 3 10 6 6 41 13 83 7 25 303 35 226 366 10 20 81 636 168 5
Deloitte 8 51 6 172 2 28 14 24 153 7 42 125 21 97 13 94 16 38 297 48 17 12 928 15
MITRE* 2 24 285 470 1 24 49 34 81 109 2 16 85 26 1 6471 100 1 155 248 455 956
IBM 24 75 3 2484 3 286 88 2 1119 10 222 137 118 27 144 61 62 23 18 19 241 25 305 18
Accenture 10 101 18 413 1 602 56 28 18 8 93 99 49 2439 62 40 126 80 34 3 13 197 33
AT&T 100 37 1 248 6 7 95 18 172 294 220 109 108 60 127 85 2020 24 9 892 32 70 26 20 15 38
Microsoft* 73 98 8 1216 19 21 97 41 27 29 150 60 106 56 19 244 1 1 29 198 31 270
Verizon 32 28 24 296 12 6 163 133 26 359 235 133 73 258 76 1135 596 1 204 47 553 2074 40 59
Dell 56 241 343 8398 54 20 4 28 34 31 123 38 253 47 65 59 308 63 26 1613 29 539 447 74 14
Amazon* 555 709 150 731 620 207 47 474 2611 4827 9133 742 133 269 709 463 7 787 987 437 826
Johns Hopkins* 5552 144 261 44 36 183 23 231 46 862 5 104 13 29 5 428 71 4814
IDA* 17897 62 1 1630 1151
Cisco 3252 2581 301 309 175 718 7 100
Palantir* 41 3266 26 85 374 27 9455 763 460 14 947 1210 1532
Oracle 1875 933 294 267 293 684 825 388 642 2271 111 316 337 40 145 175
NVIDIA* 1104 3292 8097 2055 10,362 7238 18,956 168 26,173 1764 95 6969 3527 7990
Anduril* 163 1255 5789 100 49
Apple 1595 809 7401 1357 509 5382 19,126 20,849 13,641 3539 18,758 2040 1475 393 159
Google* 336 1197 1829 2545 745 755 963 5412 6859 6692 1928 540 1651 1363 793 390 123 2101
Facebook* 887 52,865 2807 2715 96
Twitter* 983 7833 254
Table 2: Corporate influence rankings by a combination of direct contracts and subcontracting passthroughs between various tech-related companies and U.S. agencies between the beginning of 2016 and July 4, 2020 (subcontract analysis only included up to June 20).     Direct contract measurements are generated in the same manner as for Table 1. Conservative subcontract passthroughs were estimated and incorporated for companies annotated with '*' through manual review of thousands of FPDS awards whose descriptions mentioned the company or one of its major products (e.g., "aws govcloud"). Due to the intense time demands of manually reviewing tens of thousands of awards, several companies were not augmented with subcontracting passthrough estimates.     These influence rankings were then binned as either: top 10 (       ), top 25, (       ), top 50, (       ), top 100, (       ), top 250, (       ), top 500 (       ), top 1000 (       ), or below (       ). If a company was not observed contracting with an agency, the square was left white. The numerical influence rankings are shown on mouse-over.

HP / Perspecta 21 311 32 829 7 3 10 6 6 41 13 83 7 25 303 35 226 366 10 20 81 636 168 5
IBM 24 75 3 2484 3 286 88 2 1119 10 222 137 118 27 144 61 62 23 18 19 241 25 305 18
Microsoft* 73 98 8 1216 19 21 97 41 27 29 150 60 106 56 19 244 1 1 29 198 31 270
Dell 56 241 343 8398 54 20 4 28 34 31 123 38 253 47 65 59 308 63 26 1613 29 539 447 74 14
Amazon* 555 709 150 731 620 207 47 474 2611 4827 9133 742 133 269 709 463 7 787 987 437 826
Cisco 3252 2581 301 309 175 718 7 100
Palantir* 41 3266 26 85 374 27 9455 763 460 14 947 1210 1532
Oracle 1875 933 294 267 293 684 825 388 642 2271 111 316 337 40 145 175
NVIDIA* 1104 3292 8097 2055 10,362 7238 18,956 168 26,173 1764 95 6969 3527 7990
Anduril* 163 1255 5789 100 49
Apple 1595 809 7401 1357 509 5382 19,126 20,849 13,641 3539 18,758 2040 1475 393 159
Google* 336 1197 1829 2545 745 755 963 5412 6859 6692 1928 540 1651 1363 793 390 123 2101
Facebook* 887 52,865 2807 2715 96
Twitter* 983 7833 254
Table 3: A restriction of Table 2 to tech companies.

The results of incorporating our subcontracting estimations are demonstrated in Table 2 and its restriction to tech companies, Table 3. The most significant qualitative difference is with Amazon, whose large numbers of Justice, DHS, and DoD cloud contracts are almost entirely through intermediaries, such as Four Points Technology, JHC Technology, and ECS Federal (who was also the prime contractor for Google's Maven contracts).

Another significant change is that Microsoft moves into the top 10 influencers within the Justice Department's Offices, Boards, and Divisions. As we explained in a previous section, this little-known agency is the current home for U.S. international policing program ICITAP. We also notice that Google has moved into the top 500 contractors with the FBI (through supplying FISMA-certified Google Apps for Government).

Google, Facebook, and Twitter's contracting with the U.S. Agency for Global Media -- which is formerly known as the Broadcasting Board of Governors, which itself grew out of the propaganda-focused Information Agency -- as well as USAID, and, to a lesser degree, The State Department, became more pronounced. As did minor amounts of contracts with the TSA.

The conservative estimation of relative financial flow between major tech companies and various military, prosecutory, law enforcement, and diplomatic organizations in Table 3 makes clear that each of these companies is playing at least a minor support role to the U.S. government. And, in the cases of: HP, IBM, Microsoft, Dell, Amazon, Cisco, Palantir, Oracle, NVIDIA, and Anduril, these roles are significant. In light of this data, continuing to claim that Silicon Valley has abandoned Washington would be disingenuous -- even if one technically excluded Microsoft, Amazon, and IBM.

Generating Contractor "Embeddings" and Nearest Neighbors

The original motivation for mirroring the entire U.S. federal procurement database was to answer the question:

"Are the description text fields and contracting/requesting agencies in procurement data enough to generate leads for companies similar to a given one?"
More specifically, the goal was to generate glue between otherwise siloed company profiles through the nearest neighbors resulting from the left factor of a weighted low-rank approximation to the co-occurrence score matrix between terms from the contract description, the vendor receiving the award, and the contracting and requesting agencies.

Variants of such an approach are at the heart of many commercial recommendation systems -- which have been frequently criticized as being both unacceptably opaque and detrimentally engagement driven. We repurpose a basic variant here for the purpose of exploring federal contracting. Given that the resulting recommendations only involve federally mandated records of corporate entities, and our site is not monetarily incentivized by engagement (we are a non-profit and we do not sell ads), we do not forsee any analogues of the typical failure modes.

We assert no conclusions about the resulting nearest neighbors, other than that they often contain companies which contract in similar areas to the generating company. They are simply useful for expanding one's breadth of knowledge of companies.

Our Approach to Generating Similar Contractor Lists

We built such a system on top of SciPy: a stand-alone Alternating Weighted Least Squares (AWLS) embedding and nearest neighbor extraction utility and a driver specific to the Federal Procurement Data System.

After the \(m \times n\) co-occurrence score matrix, \(A\), is formed -- which, to be clear, is where most the "art" of this model resides [28] -- the objects of interest are the rows of the tall-skinny matrix \(X\) in the low-rank matrix \(X Y^T\), which approximates the co-occurrence matrix, in the sense of approximately, locally minimizing \[ \| \sqrt{W} \circ (A - X Y^T) \|_F^2 + \lambda (\| X \|_F^2 + \| Y \|_F^2), \] given a nonnegative weight matrix \(W\) with a particular sparse plus rank-one structure, \(\circ\) represents the entrywise product, \(\sqrt{W}\) is the entrywise square-root, and \(\| \cdot \|_F\) is the Frobenius norm.

More specifically, the weight matrix is required to be of the form \[ \left[(1 - \gamma)\, \text{binary}(A) + \gamma e_m e_n^T\right] \text{diag}(c), \] where:

  • \(\text{binary}(A)\) is a binary matrix with the same sparsity pattern as the co-occurrence score matrix, \(A\),
  • \(e_k\) is a length-\(k\) column vector of ones,
  • \(0 \le \gamma < 1\), and
  • The \(j\)'th entry of vector \(c\) is analogous to the tf-idf weighting for item represented by the \(j\)'th column.
We standardized on \(\gamma = 0.01\), \(\lambda = 0.01\), a rank of 150, and 10 alternating iterations. And to keep memory usage and runtimes in check, the rows of the co-occurrence matrix were restricted to the dominant 50,000 terms, 150,000 vendors, and 25,000 agencies. Likewise, the columns were restricted to the dominant 75,000 terms, 150,000 vendors, and 100,000 agencies.

Given such a structure for the weight matrix, it was shown by Hu, Koren, and Volinsky in 2008 -- incidentally, while working at two companies studied in this report, AT&T and Yahoo! -- that each factor update could be formed in linear time by precomputing a certain 'background' Gramian and sparsely updating it to solve the normal equations for each row's update.

After the final iteration of the minimization process is completed, we normalize each row of the matrix \(X\) to have unit Euclidean norm and then extract 20 to 30 of its nearest neighbors, in a cosine-similarity sense.

Examples of Generated Neighbors

Each of the "vendor" pages on the website associated with this report,, contains a list of "Similar Contractors" within the "US Federal Contracting" tab that are generated with the algorithm described above. We show a few of the examples from our most recently trained model, which was trained on roughly the last year and a half of procurement data.


Our first example is that of Cellebrite, a "mobile forensics" company which has allegedly been used by Michigan State Police to conduct unlawful searches. It has also been reported that Cellebrite sells its software to the governments of Turkey, the United Arab Emirates, and Russia.

The five closest neighbors produced for Cellebrite Inc., a subsidiary of Cellebrite DI Ltd., were:

  1. Cellebrite DI Ltd.
  2. Grayshift, LLC
  3. Pen-Link, Ltd.
  4. Avail Forensics LLC
  5. Berla Corporation
We note that these five neighbors were chosen out of the set of more than 130,000 companies kept by the truncation procedure described above. Given that the parent company was picked up as the nearest neighbor, and the other four are also forensics companies, we believe that these are quality results.

Palantir Technologies

We return to investigate the answers to our original question: "Which companies contract like Palantir [Technologies]?". Our top-five results are:

  1. XFinion Inc.
  2. Ardent Management Consulting, Inc.
  3. VIRE Consulting, Inc.
  4. iWorks Corporation
  5. Alethix, LLC

Anduril Industries

Similarly, the top-five results for Anduril are currently:

  1. Orbital Insight, Inc.
  2. Solid State Scientific Corporation
  3. Omni Fed LLC
  4. G2 Ops, Inc.
  5. Entheleon Technologies, Inc.
Orbital Insight markets itself with the blurb:
"Access the most current visibility, intelligence, and transparency of the world’s physical activity ... all on one secure, private geospatial data platform.
and Solid State Scientific Corporation appears to focus on applying machine learning to Air Force problems, much like Anduril.

Microsoft Corporation

Given that our nearest neighbors lists are generated entirely from contracting behavior, they produce lists of companies which contract similarly to the given company, rather than companies which are, in a vague sense, generally thought of as similar. This distinction becomes clear when we look at a very large tech company like Microsoft.

The most recently produced top-five list of vendors who contract similarly to Microsoft was:

  1. Four Inc.
  2. Dynamic Systems, Inc.
  3. Forcepoint Federal LLC
  4. Emergent LLC
  5. Accelera Solutions, Inc.
According to Forcepoint Federal's own brochure, they are a subsidiary of weapons manufacturer Raytheon formerly known as Websense.

Future Extensions of Embeddings

There exist namebrand tech companies -- for example, Google -- which do very little direct federal contracting, but perform a large amount of registered lobbying. We can therefore expect to improve the quality of "similar companies" recommendations by extending from our current procurement-only approach to one which includes Senate OPR LD-1/LD-2 and LD-203 filings. We have already included said filings in our website, but have not yet worked them into the embedding/neighbor generation pipeline.

Conclusions and Future Work

We have demonstrated a framework for converting the Federal Procurement Database System (FPDS) into a set of rankings meant to indicate the degree of (financial) influence of a company, including its subsidiaries, within a particular government agency -- including some which are only indirectly indicated in procurement data. When we applied this methodology to major tech companies, and augmented the award amounts with conservative estimates of subcontract passthrough amounts, we demonstrated that recent narratives decrying a massive divide between Silicon Valley and the military are anecdotal and qualitatively false.

We also demonstrated a recommendation system for automatically generating lists of similar contractors for the vast majority of -- more than 130,000 -- U.S. federal contractors. We plan to extend these "embeddings" to incorporate U.S. registered lobbying data, and provide a similar map of tech company lobbying influence, in a future report.

One of the fundamental missing features of our website is a means of accepting user-contributed corrections and additions -- ideally coupled with citations that could be verified before their inclusion. We hope to begin experimenting with such interfaces alongside our incorporation of more datasets (e.g., Canadian and European procurement records).

Lastly, as a means of both connecting our work to that of Mijente's "Who's Behind ICE?" report and demonstrating the breadth of our database's coverage, we provide a subsection of the appendix that links to our profile page for each company mentioned in their report. A similar map is provided from a collection of contractors with the Defense Innovation Unit -- and its spin-out, Kessel Run -- that we curated. An autocomplete interface is also provided for each via the "DIU" and "Who's Behind ICE?" radio options on We have also incorporated the Project on Government Oversight's Pentagon Revolving Door and Federal Contractor Misconduct databases but refrain from listing them in this report.


The author would like to thank Irene Knapp (@ireneista) for detailed help with this project's database (Postgres) and the web server's operating system configuration (NixOS). He would also like to separately thank Liz O'Sullivan (@lizjosullivan) and Shauna Gordon-McKeon (@shauna_gm) for detailed suggestions that significantly improved an early draft of this document. Lastly, he would like to thank Cornell's Center for Applied Mathematics, and the Balsillie School of International Affairs, for hosting him to talk about very early versions of this work.

Conflict of Interest Disclosure

This work was entirely self-funded. The author acknowledges that they were formerly an employee at Google, as was Irene Knapp. Likewise, Liz O'Sullivan formerly worked at Clarafai.


Company Summaries

  • HP Inc. / Hewlett Packard Enterprise Company (HPE) / Perspecta Inc.: Each of these three companies has roots in the (now defunct) Hewlett-Packard Company, which formed its HP Enterprise Services division after acquiring the remnants of Ross Perot's Electronic Data Systems in 2009; HP formally split into a personal computer business (HP) and an enterprise IT company (HPE) in 2015. The following year, HPE acquired the remains of the high-performance graphics company, SGI. And in 2017, HPE spun off its enterprise services segment, and merged it with the Computer Sciences Corporation, to form DXC Technology. About six months later, DXC spun out its public sector business and merged it with Vencore, which had previously acquired the North American division of a privatized British intelligence agency, QinetiQ, to form Perspecta. In mid 2019, HPE acquired supercomputer manufacturer Cray.
        Rather than summing the award amounts from HP, HPE, and Perspecta, we individually rank them and then take the highest ranking result (in almost all cases, that result is from Perspecta).
  • Deloitte: Deloitte Touche Tohmatsu Limited is a British accounting firm considered one of the "Big Four". In 2002, Deloitte acquired both the British and Canadian branches of Arthur Andersen, which was convicted of destroying documents in the Enron scandal. Deloitte has subsequently been under investigation by the UK's Financial Reporting Council for failing in its role as an external auditor of, Autonomy, which was the largest software company in the UK at the time of its 2011 acquisition by Hewlett-Packard. Almost immediately after Autonomy was acquired by HP, most of its value was written down as a loss, partly due to said accounting irregularities (in 2017, HP sold Autonomy to Micro Focus, and, in 2019, Autonomy's former CFO was given a five year prison sentence in the US for fraud).
  • Accenture plc: Accenture was the consulting division of Arthur Andersen from the 1950s until it became a separate unit called Andersen Consulting in 1989, then an independent company in 2000, and then officially became Accenture at the beginning of 2001. After the Enron scandal became public at the end of 2001, Accenture issued a statement clarifying this timeline of its separation from Arthur Andersen. In 2002, the Government Accountability Office issued a report critiquing Accenture as one of the four publicly traded federal contractors incorporated in a tax haven -- alongside McDermott International, Foster Wheeler (now John Wood Group), and Tyco International (now Johnson Controls). In April of 2019, the DHS's Customs and Border Protection terminated a contract with Accenture's subsidiary, Accenture Federal Services, over having paid 297 million dollars for the company to process just 58 job applicants.
  • IBM: International Business Machines Corporation (IBM) is one of the largest employers in the world, and its IBM Cloud platform is a major competitor for federal cloud contracts. Some of IBM's inventions include the relational database and the Structured Query Language, which are both employed in this project. But the company has a history of profiting from severe human rights abuses. IBM's most famous founder, Thomas J. Watson, personally spearheaded the company's role in Nazi Germany's cataloguing systems for exterminating its Jewish population. More recently, IBM's international sales of "safe city" technology have involved the construction of video surveillance networks for strongman Rodrigo Duterte.
        In 2011, IBM acquired military intelligence software company i2 Group, which received $10M from Palantir after alleging fraudulent theft of its intellectual property. Conflicts with IBM's i2 intensified over Palantir's attempted replacement of the Army's intelligence integration software, DCGS-A -- members of the Army, and Congress, suggested DCGS-A weaknesses were the cause of the U.S. bombing of a Doctors without Borders hospital in Kunduz. Palantir ultimately won DCGS-A.
  • AT&T Inc.: As chronicled in The Idea Factory, AT&T played a foundational role in the development of computing and communication equipment, beginning with its deployment in the early twentieth century of vacuum tubes as a means of amplifying long-distance telephone call signals. The company's long-running monopoly was partially due to its large-scale construction of US communication networks during both World Wars. One of the positive byproducts of their monopoly was a golden era of innovation at its Bell Labs, whose end loosely coincided with the 1984 antitrust decree breaking up the Bell System (the pieces have since reassembled into: AT&T, Verizon, and CenturyLink). The past two decades have revealed a darker side to AT&T's close relationship with the US government: numerous documents and whistleblowers have shown that the company has been eager to comply with large-scale warrantless surveillance and call monitoring.
  • Microsoft Corporation: One of the "Big Five" tech companies, it famously won the -- still heavily contested -- Joint Enterprise Defense Infrastructure (JEDI) cloud competition with its Azure platform. Along with Google and Yahoo (now Verizon), it cofounded the Global Network Initiative (GNI) in 2008, partially to avoid Congressional intervention in response to numerous international human rights violations. Despite its GNI membership, Microsoft followed Google's lead by complying with Chinese government censorship and surveillance demands when it launched its search engine, Bing, in China in 2009. Microsoft further took stewardship of the dissent suppression mechanisms in professional networking site LinkedIn after acquiring it in 2016. A 2010 report had similarly revealed that Bing was extensively suppressing LBGT-related content in Arab countries. And, after Google pulled back from proactively suppressing dissent in its Chinese localization of its Search product in early 2010, Microsoft's founder, Bill Gates, personally attacked Google's principled stand as hypocritical.
  • Verizon Communications Inc.: Verizon has its roots in one of the "Baby Bells" resulting from the 1984 breakup of AT&T: Bell Atlantic. It expanded into Silicon Valley through the purchase of AOL in 2015, and then the non-Alibaba assets of Yahoo! in 2016, and the combined the two into a subsidiary known as Oath, which then rebranded as Verizon Media Group. In 2006, Nobel Peace Prize laureate Liu Xiaobo wrote an open letter to Yahoo!'s then chairman, Jerry Yang, arguing that the company had caused the arrest of journalist Shi Tao as part of their negotiations for their stake in Alibaba. As was widely reported in 2013, Verizon's Business Network Services division had been turning over "all call detail records" to the National Security Agency. Similar "warrantless wiretapping" had previously been reported. We also note that subsidiary Verizon Business performed an analysis of the hacking of intelligence consulting company Stratfor that is "key" to the Department of Justice's current indictment of WikiLeaks.
  • Dell Technologies, Inc.: Dell Technologies is the result of the 2016 merger between Dell and enterprise storage company EMC Corporation (now Dell EMC); before going public at the end of 2018, it was the largest privately held company in the world. Reuters reported that whistleblower Edward Snowden began downloading documents while working as a contractor for Dell, and Snowden's memoir stated that he arrived at Dell through its acquisition of Perot Systems (which was sold to NTT Data in 2016). Pivotal Software, a subsidiary of virtualization company VMWare, which is in turn majority owned by Dell Technologies, has built drone strike and fuel allocation tools in collaboration with the Defense Innovation Unit spin-off, Kessel Run. These contracts are the subject of our near year-long FOI process that should complete in the coming weeks.
  • Cisco Systems, Inc.: A networking company founded by two Stanford computer scientists and named after San Francisco, Cisco was the most valuable company in the world just before the dot-com bubble burst. In the early 2000s, Cisco sold the Chinese government routers that served as the backbone of its "Great Firewall" -- allegedly going so far as designing a custom video surveillance and censorship module to target a dissident religious group. And, in 2013, documents released by whistleblower Edward Snowden detailed the NSA's process for implanting malware into Cisco products, leading to substantial declines in international revenue.
  • Palantir Technologies, Inc.: Founded in Palo Alto in 2003 by Peter Thiel as an extension of PayPal's fraud detection tools into military and law enforcement contracting, the company ended up paying $10M to IBM's intelligence subsidiary, i2 Group, to settle allegations that Palantir fraudulently stole i2's intellectual property. As noted above, Palantir intensely competed -- and ultimately won -- against a consortium of defense contractors (including IBM's i2) to replace the Army's DCGS-A intelligence synthesis tool with its Gotham software (our FOI for Palantir's DIU contract to build a LOGistics Common Operating Picture (LOGCOP) is for analogous functionality).
        In the early days of the company, Gotham was presented as a tool for data-driven civic engagement -- which are disturbingly similar to some of the goals of the website behind this report -- via their (now defunct) procurement and lobbying analysis website AnalyzeThe.US. One of their other products, Metropolis -- which they ultimately replaced with Foundry -- was used by JPMorgan to spy on its employees' emails, phonecalls, web-browsing patterns, and GPS locations to attempt to predict disgruntled employees ("insider threats"). And, as reported by LatinX organizing group Mijente, Palantir, through its contracts with ICE's Homeland Security Investigations (HSI) unit, has "played a key role" in the Trump administration's accelerated arrest and deportation of immigrants. One can find a detailed explanation of the history of the company's products from their CTO here.
  • Oracle Corporation: Oracle, was incorporated in 1977 and named after the founders' work with the CIA -- who was their first customer -- on the Project ORACLE data storage system. As detailed by numerous sources, surveillance work remained critical to the company's growth, with $2.5B of its 2003 revenue coming from federal contracts. Oracle's intense growth led to a major downfall in the integrity of the U.S. Justice Department when the former Attorney General, John Ashcroft, left office in 2005 to form a lobbying shop, The Ashcroft Group, LLC (now TAG Holdings LLC), which accepted $220,000 from Oracle to help reverse an anti-trust hold on an acquisition that he had put in place.
        In 2012, Oracle was banned from a General Service Administration procurement vehicle after paying $200M to the GSA the previous year to settle an overbilling lawsuit through the False Claims Act (five years earlier, Oracle's PeopleSoft paid $99M to the GSA due to another overbilling case). Nevertheless, Oracle has been a litigious participant in the ongoing Joint Enterprise Defense Infrastructure bid protests, having hoped that its Oracle Cloud platform would be at least partially adopted rather than the award going entirely to one of its rivals.
  • Anduril Industries, Inc.: Roughly three years after Palmer Luckey's virtual reality company, Oculus, was acquired by Facebook in 2014, Facebook was ordered to pay $500M to ZeniMax Media for his failure to comply with a non-disclosure agreement -- so they fired him.[Edit: Palmer Luckey has recently publicly disputed ZDNet's reporting.] He was subsequently inspired by Peter Thiel's Founders Fund to transition into weapons contracting. One of the first projects of his new company, Anduril, was a contract with the Department of Homeland Security building surveillance systems for the U.S.-Mexico border. And, after Google publicly cancelled its work building object tracking AI's on top of drone surveillance footage for the Air Force's Joint Artificial Intelligence Center -- called Project Maven -- Anduril was one of the companies to take over the work. Other work has included counter-UAS and satellite surveillance systems.

Exploring Mijente's "Who's Behind ICE?" Report

Exploring DIU (and Kessel Run) contractors

General Dunford has since retired from his position as the Chairman of the Joint Chiefs of Staff and joined the board of weapons manufacturer Lockheed Martin. Michael Bloomberg, the billionaire owner of Bloomberg LP, launched a presidential bid over a year after writing the linked article. During his campaign, his news company's blockage of a story critical of Chinese Communist Party elites, for fear of its impact on sales of Bloomberg terminals to China, came to national attention. One is left with the impression that op-eds are a cheap means of compensating for private concessions. Of course, the company in question was Google. It has subsequently been reported that both Palantir and Anduril Industries picked up after Google's withdrawal from the Joint Artificial Intelligence Center's Project Maven. The inconsistency of the simultaneous claims that Silicon Valley as a whole is disconnected from weapons contracting, but that only Google has crossed a national security line with its lack of contracting, is obvious. But we focus this report on a data-driven refutation of the former claim. Our study focuses on: Facebook, Apple, Amazon, NVIDIA, Google, Twitter, Microsoft, IBM, Dell Technologies, Intel, Cisco, AT&T, Verizon, Oracle, and HP (which we affiliate with Hewlett Packard Enterprise and its spinoff, Perspecta). Despite their lack of recent weapons contracts, Twitter, Facebook, and Google each have numerous advertising (sub)contracts with the U.S. Agency for Global Media and, to a lesser degree, the State Department. Cf. Bharat Rao and Adam Harrison's book, Defense Technological Innovation. As reported by The Intercept, Google's senior vice president for global affairs, Kent Walker, clarified in an internal email that Google would still be supporting another Maven contractor through "off-the shelf Google Cloud Platform (basic compute service, rather than Cloud AI or other Cloud Services)". Controversy over Project Maven was not limited to major tech companies -- AI startup Clarafai also had an employee revolt, but it responded to the concern by doubling down on federal contracts. Given that the Defense Innovation Unit -- by Director Michael Brown's own account, which is backed up by their partial client list in our appendix -- primarily contracts with startups, this case appears more representative. The Executive Director of the Defense Innovation Board (DIB) that Google directly hired into its Cloud division, Joshua Marcuse, had been critical to the DIB recommending its own "AI Principles" to the Department of Defense. In a January 2019 article in Defense One, in the context of the recent Google protests of Maven, Marcuse stated:
"If we show leadership, responsibility, show that we're circumspect and cautious where we need to be, and rigorous in our testing and making smart tradeoff decisions, I think that we will address a lot of the concerns that partners and potential partners have raised."
The Google/Schmidt milieu going directly into business with its civil service partners is a bona fide trend. Beyond the direct hiring of the ED of the DIB, ProPublica reported in detail on former Defense Digital Service leader Chris Lynch transitioning from a civil servant critiquing Googlers for not building weapons systems into the CEO of a weapons company with Eric Schmidt on its board. Such a position should not be a surprise, as it was essentially directly stated in Sundar Pichai's June 7, 2018 overview of Google's new AI Principles:
"We want to be clear that while we are not developing AI for use in weapons, we will continue our work with governments and the military in many other areas. These include cybersecurity, training, military recruitment, veterans’ healthcare, and search and rescue."
Our comments on Accenture apply equally well to Deloitte and its subsidiary, Deloitte Consulting. Google may dominate a recent research ranking of AI publication rates, but we disagree with the notion that civilian institutions should be morally, or legally, obligated to militarize simply because they house prominent researchers. In an interview with the Fox Business Network, Oracle co-founder Larry Ellison stated "Jeff Bezos and I absolutely's very important that U.S. tech companies support our country, our government. We are a democracy: if we don't like our leaders, we can throw them out. If you don't like the leaders in China, you can...fill in the blank...I don't see how a company like Google can...aggressively pursue business in China and stay away from doing anything with the U.S. military...we'd like to see our democratic/capitalist system emerge victorious in this competition versus communist/socialist systems." As Brad Smith argued in conversation with New York Times journalist David Sanger: The difference between Microsoft and Google culture is that "at Microsoft, employees expect a voice, but not to decide." This distinction was given to help explain why Microsoft was comfortable accepting billions of dollars to support weapons systems -- another was that the U.S. is a democracy. Although, as Brown and Smith make clear, they do not think that democracy should be participatory in any meaningful sense, except, perhaps, through corporate lobbying (in Smith's words, "corporate citizenship").

As we show in Table 2, the tech companies performing the most defense contracting are: HP/Perspecta, IBM, Microsoft, AT&T, Verizon, and Dell Technologies -- and, while not nearly as well-known outside of the geospatial community, we would add ESRI to this list due to its close affiliation with the NGA.

An underdiscussed component of the Defense Innovation Initiative is the rivalry between Silicon Valley oriented companies and the traditional defense contracting base, which includes national laboratories (e.g., University of Chicago-led Argonne and Johns Hopkins-led Applied Physics Laboratory) and the tech-oriented major defense contractors. If names such as: ManTech, CACI, Leidos, SAIC, GDIT, and Booz Allen are unfamiliar to you, we strongly recommend Tim Shorrock's trendsetting book on the privatization of the U.S. weapons and intelligence community.

Microsoft's role as a founding member of the Global Network Initiative (GNI) has not stopped them from engaging in the very behavior the organization was designed to prevent. In some cases, Microsoft has claimed its compliance with censorship and surveillance demands have the support of the GNI. Google recently did the same after rolling back its 2010 stance on international human rights protections. The interested reader might investigate the history of Amnesty International refusing to join due to the organization's lack of accountability mechanisms; numerous organizations later resigned, such as the Electronic Frontier Foundation (EFF), The NYU Center for Business and Human Rights, and Human Rights in China. For more information on George Tenet's straddling of the public and private components of the weapons and intelligence industry, see Tim Shorrock's 2008 book, Spies for Hire. One finds an even more glaring contradiction in one of the principal architects of the US's national security strategy on China, Retired General H.R. McMaster, who joined the board of Zoom months before the company publicly defended its blockage of a conference organized by Humanitarian China to commemorate the 31st anniversary of the June Fourth Incident. Users who are not seeking the original, raw data feed are strongly encouraged to instead browse procurement data through In addition to having frequent bouts of downtime, its search results have numerous bugs leading to missing results, and provides some curation. Numerous procurement records relating to the FBI seemingly accidentally published numerous For Official Use Only (FOUO) using the identifier "u//fouo". These results include FBI discussions of: Companies that their subsidiaries are bought, sold, split, and merged far faster than their DUNS information is updated. For this reason, and others, some companies have several DUNS numbers, and some DUNS numbers apply to multiple companies. The existence of such a large award for surveillance towers with CBP was publicly predicted by Mijente -- through an analysis of budget line items -- the day before this $250M award was signed. The conversation took place in response to a July 1, 2020 profile of Anduril in Bloomberg. One can find related reporting on this Indefinite Delivery/Indefinite Quantity (IDIQ) award -- with PIID FA8726-19-D-0010 -- from Breaking Defense. Because DARPA has a much smaller budget than the Air Force, such joint awards to both DARPA and the Air Force lead to significantly higher influences within DARPA. We compute co-occurrence scores between terms within the same award description using a triangle-shaped window, along the same lines as Pennington, Socher, and Manning's Global Vectors for Word Representations. All other co-occurrences within an award (for example, between a vendor and a requesting agency, or between a contracting agency and a description term) contribute a constant value. After summing up all contributions, we squash the result using the entrywise transformation \(x \mapsto \log(x + 1)\). Palantir's CEO, Alex Karp, penned an op-ed in the Washington Post which -- despite the title's implication of only applying to CEOs -- argued that software developers should not take "elite" ethical stands at their workplace and should instead contain any moral influence to the ballot box. Yet, the Senate's Office of Public Records shows that Palantir spends millions of dollars lobbying each year. While it is not recorded in the table, the top rankings from the HP / HPE / Perspecta trio came from Perspecta in essentially every case except DISA, where the top ranking was from HP. Google's drone warfare contract, which was subcontracted through prime ECS Federal, LLC, was part of the Joint Artificial Intelligence Center (JAIC)'s Project Maven, which subsequently involved an award to Anduril Industries, LLC. The JAIC has been referred to as the Air Force's "Maven Factory", and can be seen as a pathfinder organization for incorporating AI within the Joint Forces. Kessel Run is a similar organization within the Defense Innovation Initiative: a 'software company within the Air Force' that is spun out of the Defense Innovation Unit. See Tim Shorrock's ground-breaking 2008 book, Spies for Hire, and the closely related 2010 expose and book from The Washington Post's Dana Priest and William Arkin, Top-Secret America. Shorrock argued that, despite Reagan's rhetoric, he did not perform any significant privatization of the DoD; rather, Bill Clinton and Al Gore did so under the motivation of 'increasing efficiency'. The Joint Enterprise Defense Infrastructure (JEDI) project, which was the focus on an extensive ProPublica expose in August 2019, was originally awarded to Microsoft. It has since been subject to numerous bid protests, primarily from Microsoft's major competitor on JEDI, Amazon. Google publicly withdrew from the JEDI competition in October, 2018; the other major competitor was Oracle. Roughly two weeks after the Executive Director of the Pentagon-led Defense Innovation Board, Joshua Marcuse, was directly hired away by Google Cloud, their sibling organization, the Defense Innovation Unit, awarded Google Cloud a contract for a secure cloud management solution. Cf. the Center for a New American Security report Beating the Americans at Their Own Game. Only publications from Neural Information Processing Systems (NeurIPS) and the International Conference on Machine Learning (ICML) were counted. See the May 16, 2020 Financial Times article by Katrina Manson, which quoted Anduril's Chief Strategy Officer, Chris Brose, as stating "You could have hundreds and thousands of engagements every single day in a fight against China. We are just not fast enough, dynamic enough or scalable enough to handle that challenge." Brose is said to have argued satellites as being particularly vulnerable to sabotage. Cf. the Federal Procurement Data System and