AAIS named Prime on SHIELD Golden Dome IDIQ
$200B ceiling, ten-year vehicle. Positions AAIS to deliver edge-first autonomy across homeland, strategic, and tactical domains.
Huntsville · 03 · 2026
Initializing · Edge Mesh
Edge intelligence for the warfighting force. Sensor-to-decision in under twenty milliseconds — offline, on-platform, uncompromising.
Each tier runs autonomously at the edge, passing only consensus upward. Scroll to trace the path from sensor photon to command decision.
The platform resolves to a small, hardenable set of primitives — each benchmarked against adversarial conditions, not lab conditions.
Distributed inference across heterogeneous edge nodes. No backhaul required. Consensus emerges locally; the cloud is an audit sink, never a dependency.
Seven-layer agent stack from sensor ingest to command consensus. Agents negotiate bounded claims; every inference is receipt-stamped for after-action review.
Designed for disconnected, intermittent, low-bandwidth RF. Graceful degradation is the baseline — every node keeps fighting when the mesh fractures.
Measured against mission-representative datasets in contested RF, on battery, at altitude. Not marketing-grade; mission-grade.
The architectures that served Iraq and Afghanistan cannot win against a peer adversary in a contested electromagnetic environment. The gap is structural, not incremental.
Milestones tied to vehicle access, sponsor evaluations, and security gates. Dates are representative for planning discussions.
Accreditation posture, integration surfaces, prerequisites, and the right point of contact — filtered for the environment you are deploying into.
CMMC Level 2 · In progress (SDA-class data)
CCSDS-derived payloads · S-band / Ka downlink opportunistic · cFS-compatible services
On-orbit compute envelope · defined confidence thresholds · sponsor IRAD window for RF contest
The platform does not change across mission profiles. Only the sensor mix, the agent configuration, and the consensus threshold do.
Stress the edge budget. Outputs are planning-grade estimates from the same constraints we use in sponsor benchmarks.
Situation. Peer ICBM threat surveillance in arctic low-bandwidth RF. Ground-based interceptors require sub-second track consensus across dispersed radars.
AAIS in role. Edge fusion mesh across five radar sites. Agents negotiate track confidence without backhaul. Commander sees single consensus track with confidence tensor.
Situation. Contested littoral with peer A2/AD. Heterogeneous unmanned surface & air assets need to hunt cooperatively at the edge of RF range.
AAIS in role. Agent stack hosted on each platform. Swarm-local consensus with opportunistic uplink. Commander tasks intent; swarm resolves assignment.
Situation. Proliferated LEO constellation for missile warning / tracking. Tens of thousands of tracks, ground station bandwidth limits, high-latency downlink.
AAIS in role. On-orbit perception and track stitching. Only consensus tracks with confidence thresholds reach ground. Bandwidth reduced 92%.
Situation. Predictive sustainment across forward-deployed platforms. Readiness loss is a near-peer advantage we cede every day we defer this.
AAIS in role. On-platform anomaly detection with fleet-level consensus. Maintenance prioritized by mission-criticality, not by last-failure heuristics.
$200B ceiling, ten-year vehicle. Positions AAIS to deliver edge-first autonomy across homeland, strategic, and tactical domains.
On-orbit perception and consensus — operationalizing autonomy for proliferated LEO under contested RF.
Independent red-team evaluation. Full receipts published to sponsor. Benchmarks replicable.
Coverage across homeland strategic defense, deterrence, industrial base, and space warning mission sets.
Recognized for edge autonomy and mesh-consensus architectures aligned to the 2025 National Defense Strategy.
Full DFARS 252.204-7012 compliance. Security-first posture matched to the sensitivity of the missions we serve.
Each button opens the request form with the selected artifact prefilled. We respond with current redacted collateral suitable for government evaluation.
Dismounted Soldier Edge AI mission need, local-agent stack, C2 integrity layer, and 15-month demonstration envelope.
Request one-pagerBoundary model, local processing posture, CMMC alignment, and data handling for sponsor and CUI-adjacent discussions.
Request security summaryHow local-agent response, C2 integrity recognition, degraded-link operation, and mission-impact recommendations are measured.
Request methodologyAll inference, agent orchestration, and mesh consensus run on-platform. The stack does not require cloud connectivity; uplinks are opportunistic for reporting and fleet learning, never for real-time engagement decisions.
A defined sensor interface, compute envelope, and security boundary. AAIS ships as containerized services with deterministic timing budgets and integration playbooks per platform class (air, space, land).
Each inference carries lineage metadata: model version, calibration set, and confidence tensors suitable for sponsor review and CMMC-aligned evidence collection.
Briefings and task-order scoping start with a written request. AAIS responds with redacted collateral and a ninety-day execution plan aligned to your unit scenario and security class.
Statement of work templates, bench criteria, and RF-contest receipts are prepared so a sponsor can issue a task order without re-deriving technical milestones.
Demonstrable sub-20ms closure in contested RF. Receipts on request. Task-order ready under current vehicle.