Bollard is the gate between hearing and hands: a voice-to-action interlock for robot arms. Every spoken command is transcribed by Speechmatics Realtime, parsed by a deterministic grammar, and judged by a safety policy before anything moves. Allowed commands execute on a bimanual dinner-table simulation; denied commands return named codes and human-readable reasons (the saucepan is hot, the candle is lit, glass never gets thrown). Every command, allowed or denied, appends to a SHA-256 hash-chained receipt recording what was heard, the transcription confidence, the parsed intent, the verdict with reasons, and the scene fingerprint afterwards. One click re-hashes the entire chain and prints VALID or the exact serial where it breaks. Why: the field ships hearing (speech-to-text) and hands (VLA policies and arms), but nothing ships the gate between them. Enterprise robot deployment stops at exactly this problem: certification and safety review demand an auditable artifact of what the machine acted on. Bollard is that artifact, and it is deliberately judgeable: open the cockpit, press a command chip, watch HOLD turn into ALLOW while the arm moves, then try to break it with a hazard command, then hit Verify chain. Engineering: Next.js + TypeScript on Vercel (static + one serverless function), Speechmatics Realtime over WebSocket with 120-second JWTs minted server-side so the API key never reaches the browser, custom vocabulary boosted for table terms, a deterministic intent grammar and policy engine with no LLM in the command path, and a canvas simulation with two arms, a bollard and a rope that holds while the policy reads, pays out on allow, and snubs on deny. Tracks: Intel online (Bimanual VLA Manipulation with Multi-Modal Reasoning, dinner-table challenge option, simulation-first) plus the Speechmatics Best-Use bonus award. Solo builder, agents-augmented.
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