AI can propose. FlightLaw decides. The record proves it.
Flightworks is the governance and evidence layer for autonomous drone operations.
Deterministic rules, edge enforcement, replayable audit trails, and principal authorization for mission-critical autonomy. Built for hardware partners, evaluators, and defense/public-safety teams who need to prove what happened, why it happened, and that it will happen the same way again.
Flightworks Control is built on two open source foundations: the SwiftVector enforcement kernel and the GeoVector geospatial layer. Both are available under MIT license. Evaluation starts with the code.
GitHub →You need governed autonomy with pre-loaded authority, degraded-mode discipline, and tamper-evident audit trails. ISRLaw and FireLaw were designed for exactly this problem.
You have drone hardware or a flight platform and need a governance layer that doesn't compete with your GCS. Flightworks governs the mission. You fly it. MAVLink-compatible from day one.
The SwiftVector kernel and GeoVector spatial layer are open source under MIT. The architecture papers are public. Start with the SwiftVector spec and the Conformance Contract. Evaluation starts with the code, not the pitch.
You have access to approved airspace, MAVLink-compatible hardware, or operational contexts where governed autonomy needs field-level validation. We bring the governance kernel. You bring the aircraft and the mission.
Start the conversation →Same inputs, different outputs. Black-box autonomy cannot be certified, audited, or trusted in safety-critical operations.
When something goes wrong, there is no deterministic record of what the system decided, why it decided it, or who authorized it.
Safety checks added after the fact, not baked into the architecture. The result is safety that can be bypassed and compliance that is performative.
Mission-critical operations routed through cloud infrastructure. When connectivity fails, governance fails. Edge operations are unprotected.
Defensible post-mission review. Every finding has a chain of custody. Every principal decision is timestamped and hash-chained. If a regulator, insurer, or commander asks what happened — you can prove it, replay it, and hand them the evidence packet.
Safer autonomy boundaries. AI operates within the authority envelope you pre-authorize. Laws enforce the boundaries architecturally — not as bolted-on checks, but as constitutional constraints that cannot be bypassed.
Cleaner separation between AI and authority. The AI proposes. You authorize. The audit trail records both. Accountability is never ambiguous.
Evaluator-ready artifacts. Open-source kernel, deterministic replay, SHA256 audit chain, and field-tested workflows. Technical evaluation starts with the code.
The market gap is not autonomy — it is trust in autonomy. Operators need to know what the system decided, why it decided it, and that they can prove it after the fact. The product that closes this gap wins the regulatory race and the operator's confidence.
FlightLaw is the constitutional safety kernel — nine laws (0–8) inherited by every jurisdiction. Deterministic reducers, SHA256 audit chains, and mandatory principal authorization at every risk threshold. The laws are structural — they cannot be bypassed at runtime.
Transparent MAVLink v2 forwarding. Zero-copy parsing.
Geofence, deviation, battery, altitude, time window, no-fly, RTH reserve, operator auth.
AUTO_ALLOW, AUTO_DENY, ESCALATE_TO_OPERATOR.
Deterministic replay of any audit log. Identical results, every time.
Two platform components provide the operational infrastructure. Mission modules are composable FlightLaw jurisdictions that load into Flightworks Control based on operational context. The same safety kernel — battery management, geofencing, operator authority, audit trail — operates identically across every mission type. The module defines the domain-specific constraints.
The place where the operator exercises authority over the governed AI system. Pre-flight authorization, in-mission monitoring, and post-flight evidence review. Mac, iPad, and iPhone.
RustVector enforcement kernel at wire speed. Evaluates every MAVLink frame against deterministic rules before it reaches the autopilot. Governance at the edge with zero cloud dependency.
AI proposes damage candidates from onboard RGB + thermal imagery. Operator approves each finding. Documentation pack generated with full chain of custody. No cloud dependency, no hallucinated findings.
Engineering-grade spatial accuracy with deterministic verification. RTK precision enforced at 2cm horizontal. Grid adherence, GSD compliance, and gap detection run as laws — not suggestions.
First jurisdiction to exercise multi-asset governance and degraded-mode discipline. When comms fail, autonomy contracts — never expands. Hotspot detection through a 4-tier escalation model from Routine to Wake-the-IC.
Designed for environments where communication denial is the expected operating condition, not a failure state. Pre-loaded authority model. EMCON governance. Classification-aware state transitions. Every autonomous decision pre-authorized at T-minus.
Flightworks governs the authority envelope before launch, enforces bounded rules at the edge during execution, and governs evidence review after flight. The GCS executes the flight plan. Flightworks governs the mission.
The Mission Package is a GeoPackage file — asset layer, authorized plan, mission ID. On MAVLink hardware, Watch Station executes the mission directly. No GCS required.
Every principal decision is timestamped, immutable, and hash-chained. Prototype goal: signed post-flight report in under 25 minutes. The audit trail is the product.
Proposed BVLOS rules and growing defense procurement requirements point toward the same need: bounded autonomy, traceable decisions, and reviewable evidence. Flightworks is built to meet that need architecturally.
Proposed BVLOS frameworks point toward requirements for deterministic behavior, bounded authority, and auditable decision chains. FlightLaw is designed to satisfy these requirements architecturally — not as a compliance checklist.
Growing defense procurement requirements emphasize NDAA-compliant UAS with auditable governance. ISRLaw and FireLaw target this class of requirement — pre-loaded authority envelopes with hash-chained evidence.
GCS platforms execute flight plans. Nobody governs them. The accountability gap between autonomy and oversight is where safety incidents, regulatory exposure, and trust failures accumulate.
Technical evaluation starts with the code, the architecture papers, and the running Sentinel relay — not a slide deck. We are actively seeking hardware partners and defense-adjacent organizations to co-develop field evidence before SBIR Phase I submission.
If you have MAVLink-compatible hardware, access to approved training grounds, or a defense use case that needs governed autonomy with a traceable audit trail — that is the conversation we want to have.
Current engagement model: technical evaluations, field-validation partnerships, and SBIR-aligned co-development.
ISRLaw and FireLaw target DoD and public safety problem sets. Pre-loaded authority envelopes, degraded-mode governance, and tamper-evident audit chains address the core accountability gap in autonomous operations.
MAVLink-compatible drone hardware + Flightworks governance = field-demonstrable governed autonomy. We bring the kernel, the laws, and the evidence layer. You bring the aircraft and the operational context.
The SwiftVector kernel and GeoVector geospatial layer are open source under MIT license on GitHub. The architecture papers are at agentincommand.ai. FlightLaw and the Flightworks Control application suite are proprietary. No NDA required to evaluate the open source foundations.