Working notes on private AI architecture — written for the CIO, the CTO, and the security reviewer who has to sign off.
Hosting in-country is a contract. Sovereignty is a property of the architecture — and the difference decides whether a security review passes.
Read the noteThe most common objection we hear is that agents are not reliable enough for production. Here is what the six principles do about it.
Several LLM and ML models behind one interface, chosen against the task rather than a house preference.
Token volume becomes a hardware question answered once. That is what makes a three-year TCO predictable.
A free discovery call, then a paid assessment you own outright — whether or not you continue with us.
Hosting in-country is a contract. Sovereignty is a property of the architecture — and the difference decides whether a security review passes.
The model weights, your documents, the vector embeddings, the reasoning traces, and the audit logs all stay inside your boundary. No outbound network path is required for the system to function.
Components authenticate to each other over mTLS, every interface is behind RBAC, and audit logging is immutable. Fully air-gapped deployment is supported.
This is a property of the architecture, not a contractual promise about where a server happens to sit.
The most common objection we hear is that agents are not reliable enough for production. Here is what the six principles do about it.
We constrain agents with deterministic guardrails, scope every tool to a declared purpose, require explicit human approval for irreversible actions, and log every reasoning step immutably so a failure is diagnosable rather than mysterious.
Anomaly detection runs over the reasoning trace, not only the final answer.
Where a workflow cannot meet a reliability bar you need, we say so during the assessment — before the build starts.
Several LLM and ML models behind one interface, chosen against the task rather than a house preference.
It depends on what the agent has to do. Most deployments end up as a mixture-of-experts configuration with several LLM and ML models working together behind a single interface.
On the infrastructure side we standardize on Docker and Kubernetes, with LangGraph for agent orchestration.
Token volume becomes a hardware question answered once. That is what makes a three-year TCO predictable.
Every engagement is scoped to the project, so we do not publish a rate card. What we will commit to is that there is no per-token meter.
Token volume becomes a hardware sizing decision made once, which is what makes a three-year total cost of ownership predictable.
A free discovery call, then a paid assessment you own outright — whether or not you continue with us.
We start with a free 30-minute discovery call, and where there is a fit, a paid assessment that produces an operations audit and a prioritized roadmap you own outright — whether or not you continue with us for the build.
If the return is not there, you hear it during the assessment rather than after the invoice.