Contract facts
NONEIF- UNM COSMIAC MACHINE LEARNING TOOLSET is a federal NONE award for Fa9453 Afrl Rvk held by University of New Mexico, the. Estimated value $5.5M ($3.9M obligated). Current period of performance ends Sep 16, 2026. Last award drew 1 bidder. Place of performance: ALBUQUERQUE NM. Related solicitation FA945319S0002.
Recompete timing
PublicCurrent PoP ends Sep 16, 2026 (26 days remaining). Agencies typically plan 12–18 months ahead — at 0.9 months out, that window is already open. The buying decision is likely already in motion.
Incumbent footprint
Public recordUniversity of New Mexico, the — $14.0M obligated across 28 awards (firm-wide, all agencies) · lead buyer Department of Defense (DOD).
Related awards
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Frequently asked questions
What is contract FA945320C0042?
FA945320C0042 (If- UNM cosmiac machine learning toolset) is a Fa9453 Afrl Rvk award with a potential value of $5.5M, currently held by University of New Mexico, the. Figures are USASpending-sourced public-record facts plus SCOUT recompete analysis.
What is FA9453-20-C-0042?
FA9453-20-C-0042 is the dashed form of PIID FA945320C0042 (If- UNM cosmiac machine learning toolset), held by University of New Mexico, the. Same award — SCOUT canonicalizes compact, dashed, and parent-child identifiers to one brief.
Which office awarded FA945320C0042?
Fa9453 Afrl Rvk awarded FA945320C0042 to University of New Mexico, the (potential $5.5M).
Who is the incumbent on FA945320C0042?
University of New Mexico, the is the incumbent with $14.0M across 28 related awards in SCOUT’s public footprint. The current period of performance ends Sep 16, 2026.
When does University of New Mexico, the’s FA945320C0042 come up for recompete?
SCOUT tracks a period-of-performance end of Sep 16, 2026. Actual solicitation timing can shift with extensions, bridges, or consolidations.
Data: Showing contracts ≥ $100K from federal procurement records (FPDS-NG, SAM.gov, and related repositories), normalized by PrimeRFP SCOUT. Each row keyed by Award ID (PIID); task orders appear as independent rows.