AI-native data migration, and transformation.

A machinery and equipment services company — repairing, inspecting and overhauling units across more than a dozen facilities — ran every job on a paper file that physically traveled with the unit through roughly ten work centers. Hand-offs were manual, asset IDs were transcribed by hand, completed labor and materials often went uncaptured and unbilled, and neither customers nor managers could see where a unit was.

The firm runs its own internal AI platform, built in-house with multiple AI vendors side by side. It wanted production-grade document extraction — board decks, P&Ls, LP agreements and fund-administration documents into structured, template-mapped Excel — available across the firm inside that platform, not as another standalone tool.

A global corporate-services and fund-administration firm ran outsourced bookkeeping for thousands of end-clients across multiple countries — each invoice keyed by hand and coded to that client's own chart of accounts, across several accounting systems. The work was expensive to scale, and every reviewer's judgment evaporated after the close, so each similar invoice became a fresh review task.

A PE-owned Nordic software company had grown through repeated acquisitions — inheriting ~700 customers whose contracts lived across five formats and four languages, in scanned PDFs and handwriting. A prior external migration loaded the data by how it was invoiced rather than what the agreements said, so ~90% of legacy contract dates were wrong, quote-to-cash was breaking, and no link tied CRM records to the signed agreements that governed them.

An equipment manufacturer (~$400M revenue) builds highly customized hardware, but many subcomponents — its "platform technologies" — are reusable. Reuse ran at 60–70% within a business unit and far lower across them, because nobody could systematically search what already existed; Sales and Engineering relied on individual memory. A first quote for a new RFQ took two weeks to three months, as engineers re-developed components the company already owned — and time-critical tenders were being lost to faster competitors.