Post by RevOps Co-op

AI is going to make your data problem really expensive. Every RevOps operator we know have some version of this: → Leads coming in with misspelled emails and missing fields → Enrichment vendors formatting data differently from each other → Lists getting loaded manually into CRMs already full of duplicates → Executives saying "we need to add AI to everything" And underneath all of it? Fractured, siloed, unstandardized data that no AI tool is going to magically clean up. That's the problem Openprise was built to solve. In this episode of RevOps Demos That Don't Suck, Matthew Volm sat down with Laura Marzola 🐙 from the Openprise solutions engineering team to walk through how the platform actually works. Here's what stood out: 🔁 The automated pipeline — no-code recipes that take a record from raw input to CRM-ready output: cleansing, deduplication, enrichment, AI-powered field extraction, scoring, routing. All of it, in sequence, before anything hits production. 📋 List loading at scale — Adobe runs 700+ lists per month through Openprise. Palo Alto Networks saved 2,400+ hours a year and cut a point solution from their stack entirely. 💧 Waterfall enrichment — multi-vendor (Cognism, Dun & Bradstreet, Sales Intel) under one contract, with Openprise normalizing the output format across all of them. 🤖 AI that's actually grounded — embedded model for structured data tasks, connect-your-own (OpenAI, Claude soon) for web-based research. And a security-friendly option that doesn't send data to the web. This is the "last mile" problem that nobody talks about enough: after your AI tools and enrichment providers do their thing, someone still has to make that data actionable. Openprise is that layer. Peep the highlight reel below ⬇️ 📺 catch the full demo + write-up on the RevOps Co-op site: https://lnkd.in/gUu6p99t #revops #revenueoperations #dataorchestration #gtmops #marketingops

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