HR001124C0497↗
Accelint Ai, LLC received this contract from Def Advanced Research Projects Agcy, Defense Advanced Research Projects Agency: $4.18M obligated so far for national defense r&d services; department of defense - military; basic research. Its period of performance ended 2026-06-30.
Key facts · data as of Oct 26, 2026
- Recipient
- Accelint Ai, LLC
- Awarding agency
- Defense Advanced Research Projects Agency (Department of Defense)
- Contracting office
- Def Advanced Research Projects Agcy (HR0011)
- Obligated to date
- $4.18M
- Potential value
- $6.22M
- Ends
- 2026-06-30
Source: USAspending.gov prime award records (obligations: money committed, not outlays), data as of Oct 26, 2026.
Cite this page: SpendQuery, Award HR001124C0497, data as of Oct 26, 2026, https://spendquery.com/award?id=CONT_AWD_HR001124C0497_9700_-NONE-_-NONE-
Accelint Ai, LLC: all federal awards · Department of Defense: spending · Def Advanced Research Projects Agcy: what it buys
OBJECTIVE PREDICTION OF TEAM EFFECTIVENESS VIA MODELS OF PERFORMANCE OUTCOMES (OP TEMPO)PHASE 1 (BASE)
What it is
- Product or service
- National Defense R&D Services; Department of Defense - Military; Basic Research (PSC AC11)
- Industry
- Research and Development in Biotechnology (Except Nanobiotechnology) (NAICS 541714)
- Contracting office
- Def Advanced Research Projects Agcy (HR0011)
- Competition
- Full and open competition · 21 offers received
- Pricing
- Cost plus fixed fee
- How it was bought
- Standalone contract
- Solicitation
- HR001124S0006
- Where the work is
- Washtenaw, MI · district MI-06
Obligations by fiscal year
SpendQuery holds FY2023 on; earlier years are on USAspending.gov.
Subcontractors: where the money went next
3 subawards totaling $937.6K (22.4% of what was obligated), as Accelint Ai, LLC reported them. Primes report subawards of $30,000 or more; smaller ones and unreported ones aren't here.
| Subcontractor | Amount | Subawards | Where | First | Last |
|---|---|---|---|---|---|
| William Marsh Rice University | $573.8K | 1 | TX | 2024-09-09 | 2024-09-09 |
| Advanced Brain Monitoring, Inc. | $232.0K | 1 | CA | 2024-12-31 | 2024-12-31 |
| Deep Science LLC | $131.8K | 1 | FL | 2024-12-09 | 2024-12-09 |
The largest single subawards
| Date | To | Amount | For |
|---|---|---|---|
| 2024-09-09 | William Marsh Rice University | $573.8K | TECHNICAL SERVICES. |
| 2024-12-31 | Advanced Brain Monitoring, Inc. | $232.0K | TECHNICAL SERVICES. |
| 2024-12-09 | Deep Science LLC | $131.8K | TECHNICAL SERVICES |
Every action
8 actions since 2024-09-25. Each is a modification or amendment with the money it added or took back.
| Date | Modification | Kind | Amount | What the agency wrote |
|---|---|---|---|---|
| 2025-12-22 | P00007 | Funding only | $1.05M | OBJECTIVE PREDICTION OF TEAM EFFECTIVENESS VIA MODELS OF PERFORMANCE OUTCOMES (OP TEMPO) PHASE 1 (BASE) |
| 2025-07-23 | P00006 | Administrative change | $660.9K | OBJECTIVE PREDICTION OF TEAM EFFECTIVENESS VIA MODELS OF PERFORMANCE OUTCOMES (OP TEMPO) PHASE 1 (BASE) |
| 2025-03-11 | P00005 | Administrative change | $0 | OBJECTIVE PREDICTION OF TEAM EFFECTIVENESS VIA MODELS OF PERFORMANCE OUTCOMES (OP TEMPO) PHASE 1 (BASE) |
| 2025-02-14 | P00004 | Funding only | $1.00M | OBJECTIVE PREDICTION OF TEAM EFFECTIVENESS VIA MODELS OF PERFORMANCE OUTCOMES (OP TEMPO) PHASE 1 (BASE) |
| 2024-11-25 | P00003 | Funding only | $820.0K | OBJECTIVE PREDICTION OF TEAM EFFECTIVENESS VIA MODELS OF PERFORMANCE OUTCOMES (OP TEMPO) PHASE 1 (BASE) |
| 2024-10-31 | P00002 | Administrative change | $0 | OBJECTIVE PREDICTION OF TEAM EFFECTIVENESS VIA MODELS OF PERFORMANCE OUTCOMES (OP TEMPO)PHASE 1 (BASE) |
| 2024-09-27 | P00001 | Administrative change | $0 | OBJECTIVE PREDICTION OF TEAM EFFECTIVENESS VIA MODELS OF PERFORMANCE OUTCOMES (OP TEMPO)PHASE 1 (BASE) |
| 2024-09-25 | 0 | $656.9K | OBJECTIVE PREDICTION OF TEAM EFFECTIVENESS VIA MODELS OF PERFORMANCE OUTCOMES (OP TEMPO)PHASE 1 (BASE) |
Source: USAspending.gov prime award transactions and FSRS subaward reports, as loaded by SpendQuery (data as of 2026-10-26). Amounts are obligations (money committed), not outlays. The official record on USAspending.gov ↗