FA864924P0410
Purchase Order
Overview
Government Description
Ai-enabled rapid data exploitation for Department of the Air Force air and space intelligence analysis operations
Awardee
Awarding / Funding Agency
Place of Performance
Cambridge, MA 2142 United States
Pricing
Fixed Price
Set Aside
Small Business Set Aside - Total (SBA)
Extent Competed
Full And Open Competition After Exclusion Of Sources
Est. Average FTE
4
Related Opportunity
None
Analysis Notes
Termination This purchase order was terminated for convenience (partial or complete) in July 2025.
Amendment Since initial award the Potential End Date has been shortened from 12/22/25 to 08/08/25.
Unrealized Backlog This Purchase Order is complete with $211,148 of funded backlog and $211,148 of unfunded backlog unused, which is typically due to unexercised options.
Amendment Since initial award the Potential End Date has been shortened from 12/22/25 to 08/08/25.
Unrealized Backlog This Purchase Order is complete with $211,148 of funded backlog and $211,148 of unfunded backlog unused, which is typically due to unexercised options.
Lazarus Enterprises was awarded
Purchase Order FA864924P0410 (FA8649-24-P-0410)
for Ai-Enabled Rapid Data Exploitation For Department Of The Air Force Air And Space Intelligence Analysis Operations
worth up to $1,174,239
by Air Force Research Laboratory
in March 2024.
The contract
has a duration of 1 year 5 months and
was awarded
with a Small Business Total set aside
with
NAICS 541715 and
PSC AC32
via direct negotiation acquisition procedures with 692 bids received.
As of today, the Purchase Order has a total reported backlog of $211,148 and funded backlog of $211,148, though the contract is closed, so backlog may not be realized.
SBIR Details
Research Type
Small Business Innovation Research Program (SBIR) Phase II
Title
AI-Enabled Rapid Data Exploitation for DAF Air and Space Intelligence Analysis Operations
Abstract
The DAF Chief Information Officer s (DAF CIO) Public Strategy has identified Data & AI as a priority line of effort to operationalize data for decision advantage and to take advantage of machine-driven insights, enable rapid flow of decision-quality data to shorten every kill chain . The DoD and DAF currently have a capability gap limiting the ability to swiftly extract, understand, and correlate data from vast static and unstructured sources. In the event of a peer adversarial conflict, it is crucial for DAF to possess advanced intelligence gathering and command and control capabilities to maintain a strategic advantage. However, the current manual process for capturing, translating, documenting and transmitting information of intelligence value from military and intelligence operations is slow, manual, and insufficient to meet the demands of future warfare, necessitating the development of more efficient and effective solutions. Lazarus RikAI Family of Models, aims to close that technology gap by adapting our commercially proven Natural Language Processing (NLP) and Multimodal Large Language Models (MLLM) capabilities to efficiently extract insights from classified and unclassified repositories, unlocking valuable data regardless of document format, language, and without the need for model training. This data can then be better utilized to support operational tasks or mobilized to train other AI models, enabling the DoD to develop finely-tuned AI capabilities to respond swiftly and effectively to current and future adversarial threats. Lazarus conducted a feasibility study in partnership with Special Operations Command s (SOCOM) Visual Environment Translation, Joint Acquisition Task Force (JATF) utilizing the Ukrainian conflict as a case study. The case study highlighted challenges faced by Ukrainian forces related to equipment maintenance, repairs, and personnel training. RikAI FOM was able to provide rapid ingestion, translation, and analysis of operator and maintenance manuals enabling SOF units to provide support at the speed of relevance.
Research Objective
The goal of phase II is to continue the R&D efforts initiated in Phase I. Funding is based on the results achieved in Phase I and the scientific and technical merit and commercial potential of the project proposed in Phase II.
Topic Code
AFX244-DPCSO1
Agency Tracking Number
F2D-11328
Solicitation Number
X24.4
Contact
Meghan Scott
Status
(Closed)
Last Modified 7/25/25
Period of Performance
3/21/24
Start Date
8/8/25
Current End Date
8/8/25
Potential End Date
Obligations and Backlog
$963.1K
Total Obligated
$1.2M
Current Award
$1.2M
Potential Award
$211.1K
Funded Backlog
$211.1K
Total Backlog
Award Hierarchy
Purchase Order
FA864924P0410
Subcontracts
Activity Timeline
Transaction History
Modifications to FA864924P0410
People
Suggested agency contacts for FA864924P0410
Competition
Number of Bidders
692
Solicitation Procedures
Negotiated Proposal/Quote
Evaluated Preference
None
Performance Based Acquisition
Yes
Commercial Item Acquisition
Commercial Item
Simplified Procedures for Commercial Items
No
Other Categorizations
Subcontracting Plan
Plan Not Required
Cost Accounting Standards
Exempt
Business Size Determination
Small Business
Defense Program
None
DoD Claimant Code
None
IT Commercial Item Category
Not Applicable
Awardee UEI
RWPMHCNYD4T3
Awardee CAGE
84PD7
Agency Detail
Awarding Office
FA8649 FA8649 USAF SBIR STTR CNTRCTNG AFRL
Funding Office
F4FBEQ
Created By
kyle.west.10@us.af.mil
Last Modified By
kyle.west.10@us.af.mil
Approved By
kyle.west.10@us.af.mil
Legislative
Legislative Mandates
None Applicable
Performance District
MA-07
Senators
Edward Markey
Elizabeth Warren
Elizabeth Warren
Representative
Ayanna Pressley
Modified: 7/25/25