AI Engineering and Agentic Automation
AI applications that call tools, retrieve source material and return structured results. Tests, permissions and approval steps are part of the build.
Work in this area
We choose the parts that fit the users, operating environment and constraints.
- 01Custom AI applications and structured generation
- 02Agent orchestration, tool use and Claw or ZeroClaw-style automation patterns
- 03Retrieval, knowledge systems and evaluation suites
- 04Human approval workflows and failure handling
- 05Local, cloud, private and self-hosted inference
- 06Observability, security and cost controls
Controls for AI workflows.
Execution. Choose the model, tools, retrieval source and output schema for each job.
Testing. Run evaluation and regression suites. Restrict access and send sensitive steps for approval.
Operation. Trace calls, set cost limits and define what happens when a model or tool fails.