AI that does the work, not a demo.
Specialized agents scoped to a single job, wrapped in guardrails that eliminate hallucination in the paths that matter.
The guardrail is the product, not the model.
Anyone can wire an API call to a frontier model and call it an agent. We design the workflow automation first — the exact task, its inputs, its failure modes — then route the actual reasoning to whichever model fits the job: a hosted frontier model where nuance matters, a local open-weight LLM where the task is narrow, the volume is high, and the cost or latency budget rules out anything else. Every agent sits behind deterministic guardrails — schema-validated outputs, retrieval grounded to your own data, and hard rules it cannot reason its way around — so hallucination is engineered out before deployment, not caught after a customer sees it. Permissions are scoped to the task, escalation is defined up front, and every action is logged, so an agent earns a wider remit only as its audit trail justifies it.
Capabilities
The engagement
Scope
Find the workflow worth automating and define what completion, failure, and escalation mean for that specific task, before any model gets picked.
Route
Match each step to the model that fits it: local open-weight LLMs for narrow, high-volume tasks; a hosted frontier model only where the nuance earns the extra cost and latency.
Guard
Wrap every agent in deterministic guardrails — schema-validated outputs, grounded retrieval, scoped permissions, and a human checkpoint on anything expensive to reverse.
Monitor
Ship with audit logging and a production monitoring dashboard, then widen the agent's remit only as far as its track record has earned.