Merciv turns your connected sources into a cited research brief for a brand or category team. Ontevo scans your locations and funnels from the outside, prices what is broken in dollars, and drafts the fix.
Merciv is a strong research layer: GraphRAG brand memory on Neo4j, multi-LLM verification, and citations down to the page and paragraph, pulled from social, reviews, syndicated panels like Circana and NielsenIQ, and whatever internal documents a team uploads. Its Personas feature, which turns segmentation studies into chatable stand-ins for pressure-testing messaging, is the closest thing on the market to Ontevo's Simulation Engine. But the loop ends at a brief, a deck, or an alert with a recommended action. Nothing on Merciv's public site quantifies financial impact per finding, and there is no outside-in scan, no competitor cohort, and no agent that drafts the work. Ontevo starts from a URL, not a file upload: a Full Diagnostic runs 50 analyzers across 5,000+ signals, benchmarks the business against a cohort of up to 10 direct competitors, and hands every finding to an agent that drafts the fix for a human to approve.
If you run a brand, category, or research team at a large CPG, retail, or apparel company and need to reconcile syndicated panel numbers, internal decks, and social sentiment into a board-ready brief with citations, Merciv is the right tool and Ontevo does not replace it. Ontevo starts from a different question: not what consumers think, but where one business is losing revenue right now, at the location or funnel level, with a dollar figure attached and a drafted fix waiting for approval. If your problem is validating a white-space hypothesis before you brief an agency, Merciv is the right tool. If your problem is that one location's reviews, site, and local search presence are costing it revenue this month, Merciv's research workflow is not built to find that or fix it. Some operators run both: Merciv for the category read, Ontevo for the revenue leaks at the door.
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