We build AI systems as software engineering problems: clear objectives, explicit failure modes, and governance that matches your risk profile.
Scope
- Agentic workflows orchestrated with review gates where needed
- Retrieval and knowledge systems grounded in your data and contracts
- Evaluation: offline metrics, regression suites, and human-in-the-loop where appropriate
- Tooling integration including MCP servers and internal APIs—designed for least privilege and auditability
Outcomes you can verify
- Reduced manual workload in operations and customer support pipelines
- Faster iteration cycles with measurable quality bars
- Architectures that do not collapse when models or vendors change