AI Process Check
Map the current workflow, identify automation opportunities, risks, integrations and a realistic pilot scope.
Start with one repetitive task, measure where time is lost, validate the technical solution on a small scope and move to production only after the workflow proves useful.
It is a structured analysis of one workflow: inputs, manual steps, tools, frequency, errors, constraints, data sensitivity and the points where automation may create measurable value. Coding is not required to discover that the process should not be automated.
Input → manual steps → systems → bottlenecks → automation
The goal is not to sell “AI transformation”. It is to find one concrete workflow where automation can save time, reduce manual copying or improve consistency.
Map the current workflow, identify automation opportunities, risks, integrations and a realistic pilot scope.
Test the critical technical assumption on a small sample before building a complete workflow.
Build a limited working flow in an isolated environment and validate it with real or anonymised examples.
Deploy robust auth, permissions, monitoring, integrations and production infrastructure, preferably under client ownership.
Extract fields from orders, reports or forms, validate them and send clean data to the next system.
Turn technician notes, photos or forms into structured records, summaries and follow-up actions.
Search internal documents and answer grounded questions with controlled access to company information.
Classify incoming requests, prepare structured drafts and route each case to the right person or system.
60–90 min session + process map + automation opportunity + pilot scope and estimate.
Small technical validation on a limited sample where the main uncertainty is technological.
A limited working workflow in an isolated test environment, with validation of results.
Production deployment, integrations, security, monitoring and handover based on the approved pilot.
A pilot can run on an isolated Astera environment to avoid weeks of setup before the idea is proven. For production, infrastructure can be deployed under the client’s own cloud/API accounts so ownership, billing and access remain clear.
Pilot: isolated test environment
Production: client cloud / API accounts + documented access + clear billing.
No. It produces a concrete process map, automation hypothesis, constraints, pilot scope and estimate. The conclusion can also be that AI is unnecessary or that the process should not be automated.
Not always. A limited pilot can run in an isolated test environment. Production infrastructure can then be moved or rebuilt under the client’s accounts.
Yes when appropriate, but data sensitivity must be reviewed first. Anonymised, synthetic or restricted samples are preferable during early validation.
Then the project can stop before a larger production investment. That is exactly why the pilot exists.
Describe what enters the process, what people do manually, which tools are involved and how often it happens. That is enough to decide whether a Process Check is a sensible first step.