Platform
The whole platform, on your hardware.
One deployable unit carries the agents, the orchestration, the models, the data connections and the audit trail — a single binary that runs inside your perimeter. Cloud is not required; it is available only when you decide.
Architecture, end to end
Everything below the dashed boundary runs on infrastructure you control. The hyperscale cloud sits outside it — no egress by default, reached only on your routing decision.
- Runtime & hardware
- Rust-native single binary · memory-safe · standard 16-CPU / 128 GB server · no GPU farm · scales to a full cluster
- Isolation
- Air-gap compatible · zero internet dependency
- Access control
- RBAC for people · PBAC for agents · least privilege by default
- Security
- Zero-trust (mTLS) · guardrails · human-in-the-loop gates
Orchestration
Agents — catalogue + build your own
Models · Knowledge
Models
internal · external · embedded sLLM · + upload your own (MLOps)
Ontology & skills
domain ontology · agent skills · + build your own skill
Operational data & integrations
Your hardware — the platform runs here
Your hardware
Rust-native · single-binary · 16-CPU / 128 GB · no GPU farm · scales to a full cluster · air-gap compatible
service-to-service traffic secured · zero-trust (mTLS)
Hyperscale cloud
external
no egress by default
routing optional — your decision
Common questions
Can it run fully air-gapped, with no internet?
Yes. The platform is a single self-contained binary with zero internet dependency — no telemetry, no callbacks, no egress paths. The hyperscale cloud sits outside your boundary and is reached only if you explicitly route to it.
Which models can we use — and can we bring our own?
Open-weight, national or cloud models, switchable at any time, plus an embedded small LLM for fully local inference. MLOps lets you upload and serve your own ML models. There is no provider lock-in and no model menu set by a vendor.
What does deployment actually require?
A standard 16-CPU / 128 GB server — no GPU farm. It installs as one binary inside your network and scales to a full cluster as you grow. Most first deployments start as a proof of value on a single machine.
How is access controlled — for people and for agents?
Two layers work together. RBAC (role-based access control) scopes what each person may see and do. PBAC (policy-based access control) governs what each agent may do, read and call — through policies evaluated as it runs, because an autonomous agent needs its own least-privilege envelope, not a borrowed human role. Every user, agent and dataset is scoped to least privilege and segregated across domains.
How is it secured and audited?
Service-to-service traffic is zero-trust: every call is authenticated and encrypted with mutual TLS, so nothing inside the deployment is trusted implicitly. And every prompt, retrieval, tool call and decision is logged and replayable for review or compliance evidence.
Explore the platform
See what teams build on it, where it runs, and why the architecture is the point.
Runs on your hardware or your data centre · cloud-ready into your own tenancy.