Turn messy bank transactions into clean, structured data
Raw bank transaction strings are a mess. "SQ VERVE", "AMZN MKTP USAB1234", "PP*SHOPIFY", nobody knows what these mean, and neither do your users. Triqai is a transaction enrichment API that transforms raw banking data into clean, structured merchant intelligence. One API call gives you everything you need.
Hey Product Hunt! đź‘‹ I'm Wes Dieleman, founder of Triqai. I built this because raw bank transaction data is essentially unreadable noise, and every fintech team was either solving it from scratch or locked behind enterprise walls. A dead-simple API with transparent pricing, built for startups and growing businesses that actually need this solved. One API call gives you: - Merchant names, logos and websites - Spend categories with subscription detection and mislabel correction - Store-level locati
Happy launch day, @wes_dieleman . The " raw bank transactions are unreadable noise " line hits the pain perfectly. I spent time on the site auditing the homepage. One thing stood out. You have a live demo in the hero showing "TICKETMASTER * CONCERT NY" turning into a clean card with logo, category, location. That's your strongest proof. I like it because it shows exactly what the product does in 3 seconds. But the demo is static. A visitor sees it but can't interact with it. Adding a simple "try
this is a great one, happy launch day! saw you mention automation tools alongside the API and SDK - which ones are supported? can you plug it into something like Make or Zapier without touching code?
A lot of enrichment vendors look good on top merchants but struggle with the long tail and new businesses—what does Triqai do operationally to stay current as merchants rebrand, change processors, or open/close locations, and how quickly do those updates show up in results?
When you hit a transaction string that doesn't match any known merchant, how does the confidence scoring work and what does the API return in those edge cases? Congrats on the launch!
The scores reflect launch-period engagement. Historical data is preserved and doesn't change retroactively. The build date at the bottom shows when the index was last refreshed.
Check the similar products section on this page, or browse the category pages linked in the tags above. Each category page shows all products for a given year, sorted by engagement.
A measure of community engagement at launch. Higher means more people noticed and interacted with the product. It's a traction signal, not a quality rating.
Discussion threads divided by interest score. Above 0.30 is strong. Below 0.15 suggests the product got clicks but not conversation.