Bring AI into production, make its running costs understandable, and connect it to the systems your team already uses.
We build and improve AI applications and agent workflows. An engagement can focus on getting a prototype into production, reducing unnecessary token usage and repeated work, or integrating AI with existing applications and business data.
Useful AI depends on more than the model's answer. Data needs to be current and accessible to the right people, tool calls need to recover from failure, and usage needs to fit the budget. We review the complete workflow and agree on the changes that will make it useful to your team.
Define acceptable behavior with representative tasks and known failure cases. Build monitoring and recovery around the workflow, then roll out in stages with a way to spot regressions and reverse changes.
Trace tokens, context, retries, tool calls, and model choice through the whole task. Assess caching, context improvements, and model routing against quality and response-time requirements so the tradeoffs are clear.
Integrate through supported APIs and a dependable data path. Apply permissions before information reaches the model, keep sources current, and put controlled execution and approval steps around actions where needed.
AI is part of how we research, build, test, and document the engagement. Our lean structure keeps delivery focused. We agree on the scope, fee, and acceptance criteria before implementation.
Yes. We review its architecture, data dependencies, and failure patterns, then agree on the changes needed. The engagement can focus on one release blocker or a broader path to an operational workflow.
Quality is part of the evaluation. We compare changes against representative tasks and agreed acceptance criteria, including failure cases. The opportunity depends on the current system; any savings claim should come from a measured comparison.
We begin with the systems, APIs, and data access routes you have. We agree on data handling, provider choices, and permissions before implementation, then design retrieval and actions around those requirements. Please keep confidential project details out of the initial inquiry.
Tell us what you are building or using, which systems it needs to work with, and what you are seeing in quality, running costs, or reliability.
Discuss this work