Describe any market situation and Reprisa finds the closest parallels from 120+ years of history, scored across 15 structural factors. Plus an AI ticker terminal that reads any stock with a 0β100 bullish score, a live news feed ranked by market impact that turns any story into an instant brief, backtested trade-signal alerts, watchlist alerts, and an end-of-day market recap. Know what happened last time.
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Maker
π
Hey Product Hunt π I'm Izan, maker of Reprisa.
I built this because every time markets did something extreme, I had the same question: "when has this happened before, and what happened next?" β and answering it properly took days of digging.
Reprisa does it in about 5 minutes. Describe current conditions (or ask an open question) and it searches 120+ years of market history for the closest structural parallels β scored across 15 factors, with outcomes, bull/bear scenarios, and dated watchpoints. It grew from that one question into a full terminal: ticker analysis, impact-ranked news, and pattern alerts on your watchlist β but every feature answers to the same idea: context beats prediction.
Under the hood, reports are assembled from a locked fact table before a single sentence is written, every live number is timestamped, and when data isn't available it says so instead of inventing specifics.
Free tier is 2 reports/month, no card. I'd love to hear what setups you'd want to run β I'll be here all day.
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Solid take on the historical parallels feature, the match scoring across 15 factors felt way more grounded than just keyword searching. The bullish ticker score on a few names I follow lined up pretty well with how I've been reading the setups too.
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Maker
@keremsbrnΒ Thanks Kerem, really appreciate you digging into it. The 15-factor scoring was exactly the thing I wanted to get away from keyword-matching on β a setup can "sound" like 2008 and score nothing once you weight the actual factors. Curious which names lined up for you? Always want to know where the ticker score matches how people are already reading a setup vs where it surprises them.
Solid take on the historical parallels feature, the match scoring across 15 factors felt way more grounded than just keyword searching. The bullish ticker score on a few names I follow lined up pretty well with how I've been reading the setups too.
@keremsbrnΒ Thanks Kerem, really appreciate you digging into it. The 15-factor scoring was exactly the thing I wanted to get away from keyword-matching on β a setup can "sound" like 2008 and score nothing once you weight the actual factors. Curious which names lined up for you? Always want to know where the ticker score matches how people are already reading a setup vs where it surprises them.