The work this solves.
A number means little when the source, definition, and refresh date are unclear. Manual exports and inconsistent attribution windows make it difficult to compare results or spot missing data.
What the project can include.
AiXCEL connects the business workflow to the implementation. We agree on the first useful outcome before expanding the scope.
- An agreed metric dictionary and source inventory
- Scheduled collection and normalization for a bounded dataset
- A dashboard or recurring report with freshness indicators
- Checks for missing, duplicate, and inconsistent records
- Documented refresh, failure, and handover procedures
The checks matter.
Acceptance is based on the agreed workflow. Useful tests include:
- Reconcile a sample number to its source records.
- Simulate a missing refresh and confirm the report shows it.
- Check that different date ranges and definitions are not combined silently.
A sensible first scope.
Start with a small set of decisions and the metrics needed to support them.
Who this fits.
Teams rebuilding recurring reports across CRM, advertising, spreadsheets, or delivery systems.
What happens before you quote?
We review the workflow, its owners, the tools involved, and the access needed. The proposal defines the scope, assumptions, responsibilities, and acceptance criteria.
Do we have to replace our current tools?
Often the first improvement can use existing platforms and APIs. Tool changes are considered when the current setup cannot meet the agreed requirements.
What happens after handover?
Documentation and an operating checklist are part of the agreed delivery. Ongoing monitoring, improvements, and support are scoped separately.
Can the AI send messages or change records on its own?
External actions need explicit authorization and tested rules. Drafting, review, and execution are separate steps when the decision has consequences.