The proof is in what reaches production and moves a number.
A look at the kinds of problems we solve and the outcomes they produce. The engagements below are representative — named client case studies will replace them as references are approved.
Invoice reconciliation, automated
Challenge. A finance team spent days each month matching invoices to purchase orders and chasing mismatches by hand.
What we did. Built a document-AI pipeline that reads invoices, matches them against the PO and ledger, and routes only true exceptions to a person.
Result. ~45% of the manual hours recovered and a sharp drop in keying errors, live within a quarter.
One trusted set of numbers
Challenge. Operational reporting was rebuilt by hand across spreadsheets, with teams arguing over which version was right.
What we did. Modernised the data pipeline and automated the recurring reports, with an AI-drafted narrative reviewed by analysts.
Result. Days of monthly effort cut to minutes; a single source of truth across sites.
A proposal assistant that wins time back
Challenge. Senior staff spent hours drafting proposals from scratch, reusing past work inconsistently.
What we did. Built an assistant grounded in past winning proposals and pricing rules that drafts a first version for review.
Result. Proposal turnaround dropped from days to hours, with quality consistent across the team.
Less admin, more care
Challenge. Administrative load on clinical staff was high, with repetitive intake and documentation tasks.
What we did. Automated intake handling and drafted documentation with strict human review and privacy controls.
Result. Meaningful admin time returned to staff, with every output checked by a person.
Representative engagements for illustration. We’ll publish verified, named-client outcomes here as they’re approved.