The research your team couldn’t do before

Most AI tools retrieve from your files using vector search, which starts losing accuracy and hallucinating once you get past a few dozen documents. That’s the same ceiling you hit with most enterprise AI tools on SharePoint. Merciv works differently. When a file is uploaded, an agent reads it, understands what it covers, and maps how it relates to everything else in your library, then keeps that structure current on its own. That’s what lets Merciv reason across an enterprise-scale library instead of a handful of files, and it works on anything, from spreadsheets and CSVs to a deck that’s nothing but images.

Down to the page and paragraph. For a finding pulled from a report that runs hundreds of pages, Merciv points you to the exact passage it came from rather than the document it lives in, so you can verify it in seconds instead of scrolling.

Two ways. Answers aren’t generated by a single model. Merciv runs a set of LLMs that check each other’s work, and every output is grounded in your connected sources with confidence scoring and a full reasoning trail. The result is meaningfully more reliable than a single-model tool built in-house on one provider.

Yes. Load an old segmentation study, raw response data, or research transcripts, and Merciv turns them into living, chatable personas you can keep interrogating, including pressure-testing messaging or campaign ideas against each segment before you invest in qual. Static research becomes something your team keeps using.