The Navy's AI problem is a data problem
The Department of the Navy operates over 290 battle-force ships, roughly 3,700 aircraft, and more than 330,000 active-duty sailors. That fleet generates oceans of telemetry, maintenance records, sensor feeds, logistics transactions, and acoustic data. Very little of it gets to a model in a usable form. The Navy's most valuable AI/ML opportunities are almost all downstream of a data engineering problem that nobody has the clean-sheet time to solve.
That is the gap Precision Delivery Federal LLC (UEI Y2JVCZXT9HP5, CAGE 1AYQ0) targets. We pair production data engineering with production machine learning and wrap it in an architecture that survives federal security review. Small business, deep specialization, SAM-registered, DSIP-active, ready for Navy 26.1.
Navy commands and innovation arms we target
- NAVSEA — Naval Sea Systems Command. Ship construction, maintenance, modernization. ML opportunities in corrosion prediction, component failure forecasting, logistics depot optimization, welding and inspection computer vision.
- NAVAIR — Naval Air Systems Command. Aircraft maintenance, avionics, weapon systems. ML opportunities in predictive maintenance on legacy airframes (F/A-18, P-8), flight data anomaly detection, parts obsolescence forecasting.
- ONR — Office of Naval Research. BAAs on basic and applied research across AI, autonomy, undersea, human systems. STTR-friendly paired with university partners.
- Naval Research Lab (NRL) — corporate research lab of the Navy. CRADAs, BAAs, and subcontractor engagements. Deep science, long time horizon.
- NavalX — Navy's agility office. Tech Bridges across the country. Non-traditional performer pipeline, SBIR topic sponsorship.
- SPAWAR-successor commands (NAVWAR, NIWC Pacific, NIWC Atlantic) — C4ISR, cyber, space. AI/ML relevant across cyber anomaly detection, SIGINT processing, network monitoring.
- Marine Corps Systems Command (MCSC) — the Navy department's second service. Ground-force AI/ML analogous to Army scopes.
Navy mission areas mapped to our capability
Fleet logistics optimization
Parts availability, maintenance scheduling, inventory forecasting. ML forecasting and optimization on Navy logistics data. Our federal health data platform past performance translates directly: governed analytics, lakehouse architecture, reproducible forecasting pipelines.
Predictive maintenance (ships and aircraft)
Anomaly detection on sensor streams, remaining-useful-life modeling, maintenance demand forecasting. Kaggle Top 200-level time-series and anomaly detection practice, architected for operational fleet data.
Undersea autonomy and acoustic ML
Signal classification in noisy undersea environments, underwater vehicle autonomy (UUV), acoustic target recognition. CV and DSP-adjacent ML with open-weight deployment for disconnected operations.
ISR exploitation
Multi-INT fusion, report triage, OSINT synthesis with agentic LLM systems. See Agentic AI.
Sailor-facing decision aids
Operator-grade interfaces that make AI accessible to sailors and petty officers without ML training. Full-stack development plus LLM tool-calling.
SBIR 26.1 and Navy-specific positioning
The April 13, 2026 SBIR reauthorization (S. 3971) extends SBIR/STTR through 2031 and released 115 new DoD open and pre-release topics on DSIP the same day, including a substantial Navy block. The compressed 30–45 day topic windows favor firms that were ready before the reauthorization. We were.
- 83 Navy topics in our current proposal draft library.
- DSIP active with firm certifications complete.
- Strategic Breakthrough Phase II — new category for high-spend agencies. Navy qualifies at the department level via DoD aggregation.
- Per-firm submission caps — rewards firms like us that prioritize tight topic-to-capability fit over volume.
Past performance and honest positioning
We will not invent Navy 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, including federal workloads.
Why this matters for Navy buyers: the engineering discipline — ATO, NIST 800-53, audit logging, surviving security review — translates directly. For Navy scope specifically, we are targeting and pursuing work through SBIR 26.1, ONR BAAs, and subcontractor partnerships.
Relevant NAICS and vehicles
- Primary NAICS 541512 — Computer Systems Design Services. SBA small business.
- Adjacent — 541511, 541519, 541690, 518210.
- Vehicles — Navy SBIR/STTR via DSIP, ONR BAAs, NAVSEA and NAVAIR task orders (typically via prime IDIQs), NavalX Tech Bridge engagements, subcontracting on GSA MAS.
How Navy primes, program offices, and POCs engage us
Three primary patterns:
- SBIR prime submission — on Navy AI/ML topics where we can carry full scope. Phase I $150–300K typical; Phase II $1–2M typical; Strategic Breakthrough Phase II materially larger.
- SBIR or BAA subcontractor — on AI/ML portions of larger efforts where the prime needs deep ML expertise and a SAM-registered small business subcontractor.
- Direct teaming on primes' Navy IDIQ task orders — AI/ML scope as a specialty subcontractor.
Navy program offices, primes, and PIs: email [email protected] with the topic number or scope description. We respond within 24 hours with a fit assessment.