How it works.
An AI-operated process is an engineered, autonomous system. It receives incoming work, decides what to do within your rules, acts in your systems and records the evidence for each step. We call each one a process line.
Every case goes through four steps.
A process line completes a case only when it is confident and permitted to. Otherwise it stops and passes the case to a person, together with everything it has found so far.
Every case starts from what your company already knows.
The quality of AI-operated work depends as much on its data as on its model. We connect your systems through MCP (Model Context Protocol, the open standard for connecting AI to data and tools) and combine their data, so each case is handled with the complete picture rather than fragments.
- Connected sources: CRM, ERP, help desk, document stores, databases and internal APIs.
- One answer per fact: records from different systems reconciled, dated and sourced.
- Shared learning: what one process learns or a colleague corrects is available to others, within their permissions, through EtchMem, our learning layer.
- Controlled access: each part of a process reaches only the data its task requires, enforced with Pact.
- Traceability: every decision links back to the records it was based on.
- Open standards: connections work with commercial and open-weight models alike.
A process is only valuable when it runs reliably.
Behind every process line are models, connections, knowledge, permissions, infrastructure, monitoring and fallback paths. We engineer all of it, deploy it where your data needs to be and remain responsible for running it.
Everything it takes to run AI-operated work safely.
- Process design and rules
- Connections to your systems
- Company knowledge and memory
- Permissions and safe action limits
- Human approval steps
- Audit trails and evidence
- Infrastructure and deployment
- Monitoring and corrections
- Long-term operational responsibility