A read-only AI workflow pilot

Which workflows fit?

Good first candidates repeat often, draw on identifiable data sources, and produce a result that a reviewer can check. Examples include investigating a margin change, reconciling records across billing and CRM, or preparing a lead brief from supplied facts. A fixed calculation or simple rule may be enough for some steps; the pilot tests where an agent adds value.

Browse our synthetic demonstrations to see source references, blockers and review boundaries. They are examples, not customer results or promises about your data.

What to bring to discovery

• One question or decision your team currently works through.
• Representative exports or sample records, with their source and date.
• Definitions for the measures involved, such as revenue or margin.
• An example of a correct result and a difficult exception.
• The person who can review findings and explain current practice.

We check whether access, coverage and data quality are sufficient before proposing an integration. Sensitive data can be minimized or replaced with agreed samples during early scoping.

How the pilot stays controlled

A read-only first pass prepares findings without changing source records, sending messages or taking other operational actions. We define the permitted sources, the output format, missing-data behavior and who may approve a result. Any later write action needs a separate scope and approval path.

How to evaluate it

Before a run, agree a small set of representative cases and expected checks. Review whether the output cites the right source lines, matches known totals, flags missing or conflicting inputs, and leaves uncertain decisions for a person. Record reviewer corrections, elapsed time and operating cost where measurable. A pilot succeeds only against criteria agreed for that workflow; its results do not imply the same outcome elsewhere.