Building the governance layer for autonomous drones
Flightworks Aerial is a technology company building Flightworks Control — a governance-first ground control station where every autonomous decision is deterministic, auditable, and attributable. We validate through real-world FAA Part 107 operations.
Why deterministic governance matters
Autonomous drone systems face a fundamental tension: they need AI to handle complex, dynamic environments, but the organizations deploying them — fire agencies, defense, infrastructure — need decisions that can be audited, replayed, and defended after the fact.
Most approaches treat governance as a compliance layer bolted on after the fact. Flightworks Control treats it as the architecture itself. The SwiftVector framework separates the stochastic world (sensors, ML, predictions) from the deterministic governance layer (state transitions, escalation decisions, authority chains). AI proposes. Reducers authorize. State is truth.
This separation means every escalation decision, every task assignment, and every coverage gap is deterministically reproducible. Feed the same inputs, get the same outputs. The audit trail is not a diagnostic afterthought — it is the primary product.
Dual-track: technology and field validation
Technology Track
GCS development and SwiftVector framework
- Flightworks Control — governed autonomy GCS built on SwiftVector
- FireLaw jurisdiction — overnight wildfire perimeter monitoring (lead demo)
- Deterministic reducer architecture with SHA-256 audit chains
- Simulation-first development (SITL before hardware)
- Open-source framework with public research documentation
Field Track
FAA Part 107 operations for domain validation
- Thermal inspection pilots — validate governance in real-world thermal workflows
- UAV mapping pilots — validate mission planning and audit trail generation
- Field operations inform GCS requirements and expose governance gaps
- Domain expertise from actual operations, not just simulation
- FAA Part 107 licensed with active flight operations
The field track is not the business — it is the feedback loop. Real operations surface governance requirements that pure simulation cannot reveal.
Evaluation-ready artifacts
Flightworks Control is designed from the ground up for technical evaluation. SBIR reviewers and potential partners can assess the architecture through concrete, reviewable artifacts — not slide decks.
SwiftVector Whitepaper
Published framework specification for deterministic governance of AI-assisted autonomous systems.
Read whitepaperFireLaw HLD + PRD
Complete high-level design and product requirements for the fire perimeter monitoring jurisdiction.
Fire monitoring pageAgent in Command
Research site documenting the governed autonomy framework, including published papers and architecture notes.
Visit research siteArchitecture Diagrams
Determinism boundary, escalation tiers, jurisdiction composition, and control loop diagrams.
Governed autonomyStephen Sweeney
FAA Part 107 certified remote pilot and software engineer. Author of the SwiftVector deterministic governance framework. Building Flightworks Control to prove that governed AI scales to safety-critical autonomous operations.
Get in touch
Interested in SBIR topic alignment, domain validation partnerships, or the governed autonomy approach? We are actively seeking collaborators.