Business information is often spread across a CRM, spreadsheets, sales systems and operational tools. We connect selected sources into automated reporting and, where useful, an interface where people can ask questions about the data in plain language.
AI can explain and summarise results. The numbers themselves come from validated calculations and agreed definitions.
What we deliver
- Data consolidation from selected sources
- Automated reports and scheduled summaries
- KPI dashboards
- Plain-language questions over your data
- Exception and anomaly flags
- Data quality checks
- Reporting documentation
Technology & implementation
The foundation is a reporting dataset: data pulled from each source, cleaned, and calculated with fixed definitions. Dashboards and scheduled summaries are built on top of it.
For a plain-language question, the model generates a read-only query limited to the reporting dataset. The system validates and runs it, then the model explains the result; the query remains visible for review. Metrics never come from a free-form model response; written summaries keep the verified figures visibly separate from the AI’s commentary.
Example use
An illustrative scenario, not a description of a completed project.
A business combines customer enquiries, quotations, completed jobs and revenue information into one management dashboard. A weekly summary highlights changes requiring attention.