Partenit | Reasoning & Safety Layer for Robots jobs and careers

About Partenit | Reasoning & Safety Layer for Robots

Partenit — Reasoning & Safety Layer for Robots Partenit is a deterministic decision-making layer for robots operating in real-world, safety-critical environments. We sit between high-level task planning and low-level execution, validating every robot action before it happens. Modern robots increasingly rely on LLM-based planners, but pure LLMs hallucinate, break safety constraints, and cannot be audited. Classical rule-based systems are safe but brittle and slow to adapt. Partenit combines the strengths of both. Our approach uses a Propose → Validate architecture: LLMs generate candidate actions, while Partenit enforces hard safety rules, operational policies, and physical constraints using ontologies and deterministic validation. Unsafe or non-compliant actions are blocked by design and replaced with safe alternatives — with a full explanation of why. Partenit provides: - Deterministic, hallucination-free robot decisions - Explainable reasoning traces suitable for audits and incident analysis - Rule-based guarantees for safety, compliance, and operations - Hardware-agnostic integration with existing robot stacks (ROS / skills) We do not replace perception, control, or motion planning. We provide the missing layer that decides what a robot is allowed to do, when, and why. Partenit is designed for warehouses and other regulated environments where robots must operate reliably among people, follow strict procedures, and handle unexpected situations without unsafe behavior. Our mission is simple: make AI-powered robots deployable in production, not just impressive in demos.