One governed AI stack.
Three ways to put it to work.
Model-calibrated inference, decisions you own, and ship-check before production — on the infrastructure you already run, inside your customer partition.
Model-calibrated inference
HELIX is not a model — it is the inference engine that runs the model you choose. Calibrated for speed, tool-call accuracy, and a 0–100% confidence score on every response. GPU, CPU, edge, and IoT. Your app: deliver, confirm via API, or block.
- Engine calibrated to the model you deploy
- 0–100% confidence · app-owned policy
- Text · vision · audio · dense · MoE paths
- Customer-partition / air-gap deploy
Decision ownership
Domain-scale Decision Transformers own the decision — same inputs, same outcome, full audit trail. The LLM narrates; it never decides. For operations where “maybe” is not a policy.
- Repeatable, auditable decisions
- Full operational state in the policy
- LLM proposal layer never decides
- Continual adaptation with safety constraints
Ship-check
The MCP server gates AI coding output against reality — invented APIs, weak plans, and integrity failures are caught before they reach production. Connect Cursor, Claude, Windsurf, or any MCP client.
- generate_code · validate_plan
- analyze_code · validate_ai_output
- Single-user, rate-limited keys
- 30-day trial, then monthly subscribe