Proof, not promises.

A UK renewables operator was drowning in spreadsheet requests — every question to the data team took days. We rebuilt their reporting estate on a clean semantic model, added paginated reports for regulators, and layered a natural-language query interface so anyone could ask questions in plain English.

The data team went from report factory to strategy partner. The board went from monthly PDFs to live answers.

A motor auction business was running lead management across inboxes, spreadsheets, and memory. We ran discovery with their sales team, designed a custom lead pipeline that matched how they actually work, and built it with AI-assisted development — first demo in week one, live in a quarter.

Automated handover flows and vehicle status tracking meant nothing fell between the cracks anymore.

Hundreds of supplier invoices, compliance documents, and job reports arriving weekly — all triaged by hand. We built a set of AI agents with human-in-the-loop controls: documents classified, data extracted, exceptions flagged to a person, everything else flowing straight through.

The team kept full oversight. The busywork disappeared.

The board wanted "an AI strategy." What they needed was a filter. We audited their data estate, mapped twenty candidate use cases, and — crucially — killed fourteen of them. The six survivors got a sequenced pilot plan with real success metrics, and their team got hands-on enablement so the capability stayed in-house.

Two pilots are now in production. Zero were built on hype.

A multi-brand B2B group had data in six systems and answers in none. We built a governed semantic layer with a text-to-SQL chat interface on top — sales, ops, and finance teams now ask questions in plain English and get charts back with the SQL shown for trust.

A profile-based architecture keeps costs flat even as data volume grows, and every query respects row-level security. GDPR-compliant by design.