A stream-based runtime-verification framework for generating hard real-time C code.
Controlled PyTorch experiments testing xLSTM-style streaming forecasting and runtime assurance under telemetry faults, distribution shift and guarded adaptation.
Trusted autonomy T&E runtime that links mission needs, hazards, scenarios, telemetry, evidence, verification reports, and hash-chained ledgers so AI/autonomous decisions can be reviewed instead of merely trusted.
A runtime assurance kernel for LLM-based systems: graded verdicts, hashed commitments, bit-identical replay.
Read-only deterministic anomaly detection for mission-critical infrastructure using variance, allocation velocity, and amplification signals.
Source-available governed AI cognition architecture for bounded episodic execution, reality-corrected world modeling, evidence-gated skill synthesis, transfer challenge, replay validation, and human review. No AGI claims.
A layered architecture for running autonomous AI agents under deterministic safety constraints — a trusted, hard-coded harness that validates and bounds the output of a probabilistic model.
AI proposes. Humans decide. Source-available AI assurance and live authority control plane for governed AI-produced code change: MCP/API pre-tool enforcement, authenticated agents, scoped authorization, evidence-conditioned authority, human-gated execution, revision-bound verification, chained receipts, and auditable replay.
Governed cognition substrate for AI engineering agents: mission envelopes, evidence-bound belief/plan graphs, quarantined memory, model-role review, sentinel checks, and BlackFox handoffs under human authority.
Geometric reachability-based safety filtering for air traffic control
Physical causal evidence for autonomous fault diagnosis — open-world mechanism hypotheses, safe discriminating tests, independently adjudicated recovery. Authority-separated, receipted.
Vendor-neutral control family (ARA-1..8) for deterministic, tamper-evident, independently-verifiable runtime assurance of AI agents. Proposed for NIST CAISI / OWASP GenAI / ISO SC42.
Open Verification Kernel (OVK) is an open-source, solver-agnostic verification layer for AI-agent engineering workflows.
Deterministic postcondition verification for AI agents and autonomous systems using independent observed state.
Source-available, measurement-first pulsed-energy testbed for tri-sector storage/discharge control, derated storage, phase authority, sensor-truth checks, energy accounting, kill criteria, evidence bundles, and human-reviewed scale-up gates.
Curated research, tools, benchmarks, standards, and open-source systems for assuring autonomous systems.
A governed world-model evidence layer for AI agents: simulate bounded scenarios, track assumptions, score prediction-vs-reality error, and produce human-reviewable execution evidence.
Runtime behavioral assurance and drift detection for AI agents. Monitors CloudTrail/Bedrock traces. Detects control violations and policy breaches. Maps to NIST AI RMF, ISO 42001.
Security-first programming language for building high-assurance services, secure communications, privacy-aware networking tools, policy-enforced runtimes, secret-safe data pipelines, and auditable least-authority systems.
Signal-Time-Authority (STA): a pre-commitment controllability framework for runtime AI oversight.
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