DoD Awards $118.6M AI/ML R&D Contract to ECS Federal for Prototype Development

Contract Overview

Contract Amount: $118,579,059 ($118.6M)

Contractor: ECS Federal, LLC

Awarding Agency: Department of Defense

Start Date: 2020-04-23

End Date: 2026-03-11

Contract Duration: 2,148 days

Daily Burn Rate: $55.2K/day

Competition Type: FULL AND OPEN COMPETITION

Number of Offers Received: 999

Pricing Type: COST PLUS FIXED FEE

Sector: IT

Official Description: RESEARCH AND DEVELOPMENT EFFORT TO DESIGN AND DEVELOP PROTOTYPES TO ARTIFICIAL INTELLIGENCE/MACHINE LEARNING ALGORITHMS.

Place of Performance

Location: FAIRFAX, FAIRFAX County, VIRGINIA, 22031

State: Virginia Government Spending

Plain-Language Summary

Department of Defense obligated $118.6 million to ECS FEDERAL, LLC for work described as: RESEARCH AND DEVELOPMENT EFFORT TO DESIGN AND DEVELOP PROTOTYPES TO ARTIFICIAL INTELLIGENCE/MACHINE LEARNING ALGORITHMS. Key points: 1. Significant investment in advanced AI/ML capabilities for defense. 2. ECS Federal, a large business, secured the contract. 3. Potential for high-impact technological advancements. 4. Contract duration extends to March 2026.

Value Assessment

Rating: good

The contract value of $118.6 million for R&D in AI/ML appears reasonable given the scope and duration. Benchmarking against similar complex R&D efforts is challenging without more specific details on deliverables.

Cost Per Unit: N/A

Competition Analysis

Competition Level: full-and-open

The contract was awarded under full and open competition, suggesting a robust price discovery process. This method typically leads to more competitive pricing.

Taxpayer Impact: Taxpayer funds are being invested in cutting-edge technology with potential long-term national security benefits.

Public Impact

Advancement of AI/ML capabilities for national defense. Potential for new technologies to be integrated into military systems. Investment in research that could have broader civilian applications.

Waste & Efficiency Indicators

Waste Risk Score: 50 / 10

Warning Flags

Positive Signals

Sector Analysis

This contract falls within the IT and R&D sectors, specifically focusing on advanced algorithms. Defense spending on AI/ML is a growing benchmark, with significant investments being made across agencies.

Small Business Impact

The contract was not awarded to a small business, indicating a focus on established large contractors with proven capabilities in complex R&D. There are no specific small business subcontracting goals mentioned.

Oversight & Accountability

The Department of the Army is overseeing this R&D effort. Oversight will be critical to ensure milestones are met and funds are used effectively, especially with a cost-plus contract type.

Related Government Programs

Risk Flags

Tags

research-and-development-in-the-physical, department-of-defense, va, definitive-contract, 100m-plus

Frequently Asked Questions

What is this federal contract paying for?

Department of Defense awarded $118.6 million to ECS FEDERAL, LLC. RESEARCH AND DEVELOPMENT EFFORT TO DESIGN AND DEVELOP PROTOTYPES TO ARTIFICIAL INTELLIGENCE/MACHINE LEARNING ALGORITHMS.

Who is the contractor on this award?

The obligated recipient is ECS FEDERAL, LLC.

Which agency awarded this contract?

Awarding agency: Department of Defense (Department of the Army).

What is the total obligated amount?

The obligated amount is $118.6 million.

What is the period of performance?

Start: 2020-04-23. End: 2026-03-11.

What are the specific performance metrics and deliverables for the AI/ML prototypes?

The specific performance metrics and deliverables for the AI/ML prototypes are not detailed in the provided data. A thorough review of the contract statement of work would be necessary to understand the expected outcomes and how success will be measured. This information is crucial for assessing the true value and effectiveness of the R&D effort.

What is the government's strategy for transitioning these AI/ML prototypes into operational systems?

The provided data does not detail the government's strategy for transitioning these AI/ML prototypes into operational systems. This is a critical risk factor, as significant R&D investment may not yield practical benefits if a clear transition path is not established. Further information on future integration plans is needed.

How will the effectiveness of the developed AI/ML algorithms be validated against defined mission requirements?

The effectiveness validation process for the AI/ML algorithms is not specified. It is essential that the Department of Defense establishes rigorous testing and validation protocols that directly align with defined mission requirements. Without clear validation metrics, it's difficult to ascertain the true impact and return on investment for this significant R&D expenditure.

Industry Classification

NAICS: Professional, Scientific, and Technical ServicesScientific Research and Development ServicesResearch and Development in the Physical, Engineering, and Life Sciences (except Nanotechnology and Biotechnology)

Product/Service Code: RESEARCH AND DEVELOPMENTDEFENSE (OTHER) R&D

Competition & Pricing

Extent Competed: FULL AND OPEN COMPETITION

Solicitation Procedures: BASIC RESEARCH

Solicitation ID: W911NF17S0003

Offers Received: 999

Pricing Type: COST PLUS FIXED FEE (U)

Evaluated Preference: NONE

Contractor Details

Parent Company: Asgn Incorporated

Address: 2750 PROSPERITY AVE STE 600, FAIRFAX, VA, 22031

Business Categories: Category Business, Corporate Entity Not Tax Exempt, Limited Liability Corporation, Not Designated a Small Business, Special Designations, U.S.-Owned Business

Financial Breakdown

Contract Ceiling: $173,699,547

Exercised Options: $149,049,787

Current Obligation: $118,579,059

Actual Outlays: $4,671,161

Subaward Activity

Number of Subawards: 47

Total Subaward Amount: $64,431,647

Contract Characteristics

Commercial Item: COMMERCIAL PRODUCTS/SERVICES PROCEDURES NOT USED

Cost or Pricing Data: YES

Timeline

Start Date: 2020-04-23

Current End Date: 2026-03-11

Potential End Date: 2026-03-11 00:00:00

Last Modified: 2025-07-31

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