Before
~1 week
- 4–5 people
- 160–200 hours of work
- Every week and every month
C-level reporting for a client: data from more than a dozen people and four kinds of sources, unified by AI, validated, visualised and published online.
~1 week
~1 hour
It was more than a dozen people, each sending numbers in their own format, from four kinds of sources.
Completeness
Every person and source delivered data for the period.
Consistency
The same metric agrees across sources.
Anomalies
Sudden jumps or drops against previous periods are flagged.
Format and schema
Columns, types, units and dates are correct.
Formats from a dozen people never match: different column names, units and layouts. That is where rules break and a language model does well, so the LLM unifies the data. Everything after it, validation, charts and publishing, is deterministic, so every number in the report can be traced and audited.
The live report opens in a browser. Same structure as the real one, with demo numbers.
Leadership report · Week 41
All checks passed · Published 07:02
Weekly revenue, last 12 weeks (€k)
Days 1–30
Map your recurring reports, their sources and who builds them. Pick the one that costs the most time.
Days 31–60
Automate that report end to end, with validation checks your team agrees on.
Days 61–90
Publish it, hand it over with documentation and measure the time it saves. Then pick the next one.