DARPA AI for high-risk research.

Precision Federal is pursuing opportunities at DARPA

Precision Federal is pursuing opportunities at the Defense Advanced Research Projects Agency across BAAs, AI Exploration (AIE) opportunities, SBIR/STTR, and subcontractor roles on larger DARPA programs. DARPA is the Department of Defense's apex research arm — roughly $4.4 billion in annual budget authority distributed across six technical offices, with a mandate that is explicitly to pursue high-risk, high-payoff technology that the services would not otherwise fund. A substantial share of that portfolio is now AI, autonomy, and ML-adjacent.

Precision Delivery Federal LLC (UEI Y2JVCZXT9HP5, CAGE 1AYQ0, NAICS 541512) is SAM-registered, DSIP-active, and structured to engage DARPA as prime on small efforts and as AI/ML subcontractor on larger performer teams. Led by a Kaggle Top 200 data scientist with production federal ML past performance at SAMHSA, we bring the rare combination DARPA performer teams need: someone who can both publish-grade model and ATO-grade deploy.

How DARPA contracting actually works

DARPA is not a standard DoD buyer. Its contracting differs from the services in three material ways:

• Office-centric solicitation — most demand originates from individual technical offices (I2O, DSO, MTO, STO, BTO, TTO) via standing BAAs and program-specific amendments, not from a single acquisition calendar.
• AIE (AI Exploration) — a standing construct inside I2O that lets program managers solicit short, focused proposals with award target within 90 days of proposal receipt and funding typically up to $1M over 18 months. Designed specifically to invite non-traditional performers and small businesses.
• OTAs and Section 845 — many DARPA efforts execute through Other Transaction Authority, bypassing FAR-based contracting when speed or non-traditional participation is the goal.

DARPA also runs its own SBIR and STTR pipeline on DSIP, typically releasing topics outside the larger DoD 26.x and 26.x cycles. Those topics are smaller than AIE awards and often act as feeder pipelines into larger DARPA programs.

DARPA technical offices we target

AI Next and the programs we align to

DARPA's AI Next investment (multi-billion, multi-year) frames a generation of programs whose alumni and successors drive today's demand. We align to several explicitly:

• GARD (Guaranteeing AI Robustness against Deception) — adversarial ML robustness. We build production-grade defense against evasion, poisoning, and backdoor attacks, including in LLM prompt-injection contexts. Directly relevant to the growing set of DoD deployments that need audit trails and adversarial testing.
• ACE (Air Combat Evolution) — decision AI for air combat, now evolving into broader autonomous-decision programs. Our agentic systems practice — multi-agent orchestration, tool-calling with human-in-the-loop, auditable action logs — belongs here.
• SCORE (Systematizing Confidence in Open Research and Evidence) and descendants — confidence, reproducibility, and trust in open research. Our data engineering practice fits: lakehouse architectures with provenance, reproducible pipelines, governed analytics.
• XAI successors — explainable AI tooling, now evolving into model-behavior auditing and interpretability-at-scale. Relevant for LLM deployments that need human-reviewable reasoning.
• AI Forward / AI Next follow-ons — the program office's rolling portfolio for frontier AI research, often routed via AIE.

AIE — the fast-lane for small business AI

The AI Exploration (AIE) construct is arguably the single most accessible DARPA vehicle for a SAM-registered small business with strong AI capability. AIE opportunities are solicited by I2O program managers as short, focused calls under standing BAAs. The defining features:

• Proposal-to-award target: ~90 days.
• Funding ceiling: typically up to $1M over 18 months per award.
• Contract type: typically OT, enabling speed and non-traditional participation.
• Intended performers: non-traditional small businesses, academic teams, and niche specialists.

We monitor open AIE solicitations continuously and pursue those where our capability stack — agentic AI, LLM engineering, adversarial ML, federal deployment discipline — matches the program manager's intent. Our prior-art differentiator is federal production experience, not an academic publication record; that means we position well on AIE calls where the program manager wants a prototype that survives beyond the lab demo.

STTR and university teaming

DARPA STTR requires a research institution performing at least 30% of the work. We actively pursue university teaming for DARPA STTR topics, particularly where the PI holds ongoing AI, ML, autonomy, or cyber research that benefits from industrial productization. Our role in STTR teams: take the PI's research prototype and wrap it in the architecture, data engineering, deployment discipline, and test infrastructure that let it transition to a DARPA program or DoD component.

Capability map for DARPA scope

• Agentic AI / LLM systems — multi-agent orchestration, RAG over technical corpora, tool-calling with human-in-the-loop, prompt-injection hardening. See Agentic AI.
• Machine learning and data science — adversarial robustness, time-series forecasting, anomaly detection, CV on ISR-like data, deep ML on structured and semi-structured federal data.
• Cloud architecture, IL4/IL5 — Azure Government, AWS GovCloud, on-premise air-gapped. ATO-minded from day one.
• Data engineering — lakehouses with provenance, reproducible pipelines, governed analytics, multi-classification handling. See Data Engineering.
• DevSecOps and cybersecurity — STIG compliance, NIST 800-53 mapping, prompt-injection hardening for LLM deployments.

Past performance and honest positioning

We will not invent DARPA past performance. Our confirmed shipped work:

• SAMHSA (HHS) — production ML system on federal health data, through full ATO, real users.
• Federal health IT data platform — lakehouse architecture, governance-first.
• Multi-agency cloud migration — delivered through prior consulting employers.

For DARPA specifically we are targeting and pursuing through AIE, BAAs, SBIR, STTR, and subcontractor roles. Why this still matters to DARPA program managers: the biggest gap on DARPA performer teams is usually not novel research — it is the engineer who can take the research prototype through security review, deployment, and operational hand-off. That engineer is us.

Vehicles, NAICS, and engagement

• Primary NAICS 541512 — Computer Systems Design Services. SBA small business.
• Adjacent — 541511, 541519, 541690, 518210, 541715 (R&D).
• DARPA vehicles we're positioned for — open BAAs (especially I2O), AI Exploration (AIE) opportunities, DARPA SBIR/STTR on DSIP, OTAs via performer teams, and subcontractor roles on multi-performer DARPA programs.

If you are a DARPA program manager, a university PI building a DARPA team, or a prime performer looking for an AI/ML specialty small business subcontractor with SAM registration and production federal past performance, email [email protected]. See also SBIR/STTR partnering and Teaming.