Hey Product Hunt 👋 I built Vallience after repeatedly running into the same problem: competitor research was scattered across Google searches, alerts, bookmarks, spreadsheets, documents, and one-off AI conversations. Gathering information took hours, but the harder task was deciding what was credible, what actually mattered, and what to do about it. Many competitive-intelligence tools are excellent at monitoring activity. They tell you when a competitor changes a webpage, publishes an article, or announces a feature. But an alert is not necessarily intelligence. It rarely explains whether the development is strategically significant, independently supported, or simply marketing noise. Vallience started as a simpler competitor-monitoring product. During development, the focus shifted from collecting more information to producing better-supported conclusions. It now searches across multiple sources, removes duplication, identifies contradictions, separates facts from interpretation, and communicates confidence and evidence gaps. The resulting reports highlight developments, threats, opportunities, strategic direction, sentiment, and what to monitor next. Researching smaller, less-visible competitors shaped the product most. Sometimes the honest answer is that public evidence is limited. Vallience should make that uncertainty visible, not disguise it with a confident AI-generated narrative. I’d love to hear how others approach this work. What does your competitor-research process look like today—and where does it break down?

Vallience

Evidence-backed competitor intelligence, powered by AI

Evidence-backed competitor intelligence, powered by AI