Merciv

Merciv is an AI-native research platform for consumer brands, built for the part of the job no tool has owned: synthesis. Insights teams already have syndicated data, social listening, past decks, project reports and a dozen browser tabs. What they don't have is one place to ask a question across all of it and get an answer they can defend. Merciv sits above those sources. You set up your brand context once — your brand, your competitors, your category — and Merciv builds a persistent knowledge graph across your own documents and research alongside licensed external consumer, social, search and demographic data. From there you ask questions in plain language, run repeatable workflows (competitive briefs, category landscapes, audience snapshots, social pulse, daily briefs), and stand up trackers that keep running between waves instead of starting from zero each time. Every output is built to survive scrutiny. Findings carry page-level citations you can click through to the underlying source, plus confidence scoring, so a senior analyst can spot-check the work and a CMO can pressure-test the number before it reaches a board deck. General-purpose chatbots can't reach licensed sources and can't show you where an answer came from. That gap is why Merciv exists. What we don't do: synthetic respondents. Merciv reports on real licensed consumer data and on your own material, and it tells you when the evidence is thin rather than filling the gap. Merciv is SOC 2 compliant, your data is never used to train models as a matter of policy, and every workspace is tenant-isolated. Trust documentation is public at trust.merciv.com. Who we work with: consumer brands across food and beverage, beauty and wellness, fashion and apparel, and retail — insights and CMI leaders, data and analytics teams, and lean teams carrying a category on their own. Want to see it on your own brand? We'll run Merciv on your category and walk you through the output, citations included.