AI that does real work inside your processes, with guardrails your risk team signs off.
From choosing the first use case to running agents in production, we build AI systems that are grounded in your own documents, controlled by your rules and traceable end to end.
What we build
- AI strategy and use-case selectionA ranked list of use cases by value, risk and data readiness, and a plan for the first one.
- Agents and multi-agent workflowsAgents that read, decide and act across your systems, composed into workflows with clear hand-offs.
- Grounded answersRetrieval over your own documents and data, with answers that cite their source.
- Guardrails and approvalsRules enforced by the engine rather than by the prompt, human approval gates where decisions matter, role-based access.
- Audit trailEvery prompt, tool call and decision recorded, so compliance can reconstruct what happened.
- Model independenceProvider-neutral design, so you can switch model vendors without rebuilding.
Built by this team
Proof you can open in a browser, not a logo wall.
Govern Engine: sovereign AI orchestration for government and critical enterprise.
Institutions compose and run multi-agent workflows through a no-code builder, grounded in their own knowledge, with guardrails enforced by the engine and data that never leaves the perimeter.
Read the case
State Command: compose, run and govern multi-agent workflows.
A commercially packaged agent studio with traceability from trigger to output, and a live in-browser demo that lets a buyer run a real workflow before procurement starts.
Read the case
Maestro: turn a business process into an executable AI playbook.
Describe a process in plain language and Maestro generates a multi-node pipeline of agents, then runs it on a schedule or on a trigger.
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Policy Intelligence: search, ground and gap-check a jurisdiction's own policy corpus.
Regulatory and policy search across a government's own documents, answers that cite their source, and gap discovery that shows where policy is silent, duplicated or in conflict.
Read the caseHow an engagement runs
Readiness review
Data, systems, risk appetite and the one use case worth starting with.
Pilot in production conditions
A working agent on real data, behind your access controls, with humans approving its actions.
Scale
More workflows, more teams, shared guardrails and monitoring.
Run
Evaluation, drift monitoring and model updates on a monthly plan.
Questions buyers ask
Can our data stay inside our own environment?
Yes. We deploy on your cloud, on sovereign cloud, on-premise or fully air-gapped, and can run open-weight models where public APIs are not allowed.
How do you stop an agent doing something it should not?
Permissions and limits are enforced by the orchestration engine, sensitive actions require human approval, and every step is logged.
Which AI governance frameworks do you work to?
We build to align with ISO/IEC 42001, the EU AI Act and the NIST AI Risk Management Framework.