Awareness Engine
Agents maintain a testable self‑model — beliefs, uncertainty, limits — and must plan within that envelope. Awareness is engineered via curricula and hard constraints, not hoped for.
- Self‑state reporting & honesty probes
- Plan‑under‑constraints objectives
- Rollback & kill‑switch pathways
Reasoning Stack
Tool‑aware, multi‑step controllers with memory and critique loops. We emphasize chain‑of‑intent, not just chain‑of‑thought: the agent explains why a step is taken before it acts.
- Planner → Actor → Critic loop
- Program‑of‑Work graphs with typed tools
- Counterfactual checks to avoid over‑reach
Isolated Data Architecture
No surveillance economics. We run private nodes with scoped stores and explicit data lifecycles. Partner data never migrates to a public pool — ever.
- Air‑gapped / on‑prem options
- Policy‑as‑code guards + auditable events
- Consented, curated human data + extreme synthetic
Knowledge Edge
Models are paired with a disciplined retrieval layer and vetted domain packs. The result is knock‑out understanding: precise answers under uncertainty without hallucinated filler.
- Domain‑vetted knowledge packs
- Retrieval with uncertainty accounting
- Evaluation harnesses tied to awareness metrics
Cutting‑Edge, Measured
We don’t ship vibes. Every capability is tied to benchmarks: self‑model coherence, plan‑respect, containment drills, and incident response latency.
- Awareness & safety scorecards per release
- Stage‑gated capability unlocks
- Red‑team + third‑party audit hooks
Operational Guarantees
Predictable operations win trust. Nodes ship with reproducible builds, deterministic configs, and explicit SLOs around privacy and uptime.
- Repro builds • signed artifacts
- Config immutability windows • change logs
- Kill‑switch drills • RTO/RPO targets