Five stages. One method. Every engagement follows the Hyperion Lifecycle from diagnostic through production to continuous operations — with your team owning the result. Physical AI for the machines that move the real world: robots · factories · vehicles · aircraft · critical infrastructure. Sovereign-first: Mistral open-weight → on-prem → edge. (Advise · Build · Train: the three engagement modes within the Lifecycle.)
Filtered by lifecycle stage
Build — 5 services in this stage
Eight weeks. A fine-tuned open-weight model — Mistral, Llama 3, or Qwen — trained on your proprietary industrial data (maintenance manuals, MES/PLC logs, technical documentation) and running on infrastructure you control, not a frontier API you rent
Twelve weeks to a production-grade multi-agent system that serves as the software and control-plane complement to your cyber-physical stack — fleet intelligence, SCADA-adjacent orchestration, or autonomous operations — with the eval harness, the observability stack, and the SRE handoff your team needs to operate it
Sixteen weeks to AI running on the edge — inside a robotics cell, an AGV/AMR fleet, an ADAS or AD stack, a UAS/drone autonomy system, or a substation — with the safety evidence, the SRE handoff, and the integration your operations team will accept
Turn cameras, LiDAR, radar, and IMUs into one trustworthy world-model — the Sense layer of the Physical AI Stack, engineered for the edge and degraded conditions.
Functional-safety evidence for AI in safety-critical machines — HARA, ASIL/DAL/SIL decomposition, and assurance cases mapped to ISO 26262, DO-178C, and IEC 61508. A notified body certifies; I engineer the evidence they assess.
Book a discovery call. No pitch, no pressure — just an honest conversation about your situation and whether I can help.