AI Engineering
Start with a concrete workflow, not a model. We assess where AI is useful, integrate it with the right systems and data, and design for evaluation, permissions and ongoing operation.
Controlled access to documentation and internal knowledge. Where useful, targeted retrieval supplies relevant sources for answers — retrieval-augmented generation (RAG). Source attribution and permission boundaries inform the design.
Connect APIs, existing business applications, IT service workflows and document processes. Plan human approval for consequential actions.
Clearly bounded steps with tool integrations, defined handovers, quality checks and error handling. Make results and decisions traceable.
We set up the AI solution in the cloud or on your own infrastructure — with appropriate access permissions, protected credentials and a clear plan for monitoring, costs and maintenance.
Assess a concrete process for useful AI integration and, where appropriate, define a bounded pilot.
Conventional automation may be the better outcome of the assessment.
A short project description is enough: the systems involved, your goal and an approximate timeframe. I read your enquiry and agree the next steps with you.