AI automation that touches the real workflow
We use AI where it can remove repetitive work, not where a normal rule or API would be cheaper. The result is a production workflow with auditability, fallbacks and a human path when the model is uncertain.
You can point to the handoff that keeps costing time.
The process does not need to be documented perfectly. It needs enough repetition, clear business ownership and a safe way to handle exceptions.
The end state should be obvious to the operator.
We design around the business event: what should happen automatically, what should stop, and what should appear in front of a human only when the system cannot safely decide.
A production workflow, not a clever demo.
Discovery, data mapping, business rules, integrations, interfaces, evaluation, monitoring and an explicit recovery path are part of the implementation.
Workflow map and automation boundary
Model and vendor selection
Integrations and business rules
Evaluation set and guardrails
Production deployment and handover
Tools follow the workflow.
Bring the screen recording, export or spreadsheet.
We can usually tell quickly whether this needs integration work, AI, a small internal tool, hardware—or no new system at all.