Why NASA is buying AI in 2026
NASA's AI appetite has expanded across every mission directorate. On-board autonomy is mandatory for deep-space missions where light-speed delay kills teleoperation. Earth-observing constellations now produce more imagery in a day than analysts can review in a month, and the Agency is explicit that ML is the leverage. Mission operations, clinical support for long-duration crewed missions, spacecraft health monitoring, and science-archive analytics are all AI line items in the current budget cycle.
Precision Delivery Federal LLC is an AI/ML small business aimed at NASA AI/ML scope. We are SAM.gov active, NAICS 541512 primary, SBIR-registered, and we carry a production federal ML past performance anchor at a federal health agency. Our stack spans frontier LLMs on FedRAMP paths, open-weight models for constrained environments, and scientific ML for the PDE-governed systems that dominate NASA work.
NASA — Space and Science AI Applications — Capability Fit Score
NASA centers we target
- Jet Propulsion Laboratory (JPL) — Robotic planetary exploration, deep-space missions, on-board autonomy, Earth-science instruments. Caltech-operated FFRDC with extensive small-business partnering.
- Ames Research Center (ARC) — AI, autonomy, air-traffic management, astrobiology. Heart of NASA's applied AI work.
- Goddard Space Flight Center (GSFC) — Earth observation, heliophysics, astrophysics, Landsat and MODIS data pipelines.
- Langley Research Center (LaRC) — Aeronautics, atmospheric sciences, entry-descent-landing systems.
- Glenn Research Center (GRC) — Propulsion, power systems, communications.
- Johnson Space Center (JSC) — Human spaceflight, crewed mission operations, life sciences and medical.
- Marshall Space Flight Center (MSFC) — Launch systems, propulsion, SLS and Artemis.
- Kennedy Space Center (KSC) — Launch operations, ground systems, payload processing.
NASA vehicles and opportunity paths
NASA SBIR / STTR
Annual solicitations with AI/ML topics across every mission directorate (SMD, ARMD, STMD, SOMD, ESDMD). Post-April-2026 reauthorization the program is funded through 2031. We are DSIP-adjacent, SBIR-registered, and ready to submit.
ROSES (Research Opportunities in Space and Earth Sciences)
SMD's omnibus research solicitation. AI/ML elements in most recent cycles, especially for Earth-observing data analytics.
Center-specific BAAs and SAAs
JPL, Goddard, and Ames each run targeted calls. Small-business-friendly.
SEAS (Solutions for Enterprise-Wide Procurement)
NASA's IT services IDIQ; AI/ML scope rides as task orders under prime holders.
STMD BAA
Space Technology Mission Directorate's BAA funds technology maturation — including AI autonomy.
SEWP VI via partners
hardware-adjacent AI deployments across centers.
JPL subcontracts
JPL runs its own procurement system and contracts extensively with AI/ML small businesses.
AI/ML scope that fits NASA the best
On-board autonomy
Decision-making for spacecraft, rovers, and landers where light-speed delay prevents human-in-the-loop control. Includes autonomous target selection, hazard avoidance, opportunistic science, and fault recovery.
Earth observation ML
Land cover classification, deforestation and wildfire detection, flood and disaster response, methane and CO2 plume detection, agriculture monitoring. Our machine learning team is Kaggle-Top-200 caliber and built on computer-vision workloads of exactly this shape.
Mission planning optimization
Constraint-satisfaction and reinforcement-learning approaches to observation scheduling, trajectory planning, and resource allocation under operational constraints.
Spacecraft and instrument health
Anomaly detection on telemetry, predictive maintenance for ground systems and flight hardware.
Astronaut decision support
Clinical ML for long-duration crewed missions, onboard knowledge retrieval, procedural assistance. This intersects directly with our a federal health agency clinical-data experience.
Satellite constellation analytics
Cross-constellation fusion, gap-filling, super-resolution, and data-product assembly pipelines.
Scientific ML over NASA archives
Foundation-model adaptation to astrophysics, heliophysics, and planetary datasets; retrieval-augmented research assistants for NASA scientists.
Agentic AI for mission operations
Multi-agent systems that monitor telemetry streams, correlate with operational playbooks, and draft response actions for flight controllers with provenance and human-in-the-loop gating on every action.
Why a small business on NASA AI
NASA has real socio-economic goals and a culture that genuinely values small-business innovation — NASA SBIR is one of the most mature SBIR programs in the federal ecosystem, with Phase III commercialization pathways that actually close. A prime or FFRDC partnering with a SAM-registered, NAICS 541512 small business with AI/ML depth and production federal past performance gets specialized capability and small-business credit in one move.
NASA technologists also move fast. A JPL principal investigator working against an SBIR Phase II technical volume or a Goddard science team drafting a ROSES response does not have capacity to wait on a big prime's capture committee. We respond in days, not weeks.
Past performance and what we bring
Our confirmed federal past performance is a production ML system at a federal health agency (HHS) — a live system inside a federal ATO boundary, with NIST 800-53 controls, federal security review, and ongoing operations. That discipline is directly transferable to NASA ATO environments. Pre-Precision, Bo delivered cloud migration and data platform engineering at federal consulting firms supporting multiple civilian agencies, and competes as a Kaggle Top 200 data scientist — the computer-vision and ML competition muscle that NASA Earth-observing and planetary-imagery work demands.
For NASA-specific scope, we target and pursue rather than claiming delivered past performance at any NASA center. That distinction matters, and we will always state it clearly.
Stack for NASA workloads
Computer vision
Modern transformer-based backbones (ViT, Swin, DINO-v2), segmentation (SAM-class), detection (DETR, YOLO-family), super-resolution, self-supervised pretraining on unlabeled remote-sensing corpora.
Scientific ML
Physics-informed neural networks, neural operators (FNO, DeepONet), graph neural networks for orbital-mechanics and molecular work.
Autonomy
Reinforcement learning, model-predictive control augmented by learned dynamics, constraint-satisfaction solvers.
Foundation models
Claude, GPT-4, Llama, Mistral on appropriate federal paths; parameter-efficient fine-tuning on NASA-domain corpora.
Data platforms
Lakehouse architectures for Earth-observation pipelines, experiment tracking, provenance tagging.
Cloud and on-prem
AWS GovCloud, Azure Government, on-prem center HPC, hybrid burst patterns.
Security
NIST 800-53 by default, audit logging, provenance on every generation, adversarial robustness testing.
Why a small-business AI firm fits NASA
NASA SBIR is explicitly structured around small-business innovation, and the AI/ML centers — JPL, Ames, Goddard, Langley — routinely reach to small firms for agility on focused technical problems. A founder-led AI/ML small business with production federal-health delivery, SAM-active posture, and SBIR approval is exactly the profile these centers pursue when scoping autonomy, EO, and mission-automation topics.
How to engage
If you are a NASA technical lead, a JPL PI, a center contracting officer, or a prime scoping an AI/ML subcontractor, email bo@precisionfederal.com. Include the center, the vehicle or topic number, and the scope. We respond within 24 hours with a fit assessment, rough level of effort, and a teaming construct.