Reva

🤔 "But our evals look good!" There are well-established frameworks for testing software. But these frameworks do not work for LLM-powered systems. Testing LLM products requires more than just evals and eyeballing outputs 👀 In our latest post we take a look at: 🚫 Why traditional testing approaches fall short 📊 Where evals make sense, and where they don't 🔄 Why teams need comprehensive testing at real scale 🎯 The shift from deterministic to probabilistic testing https://lnkd.in/e3MpJr2x We've seen teams move from "we think this works" to "we know this works" 🚀 If you want to be in the latter camp, sign-up to our Beta.

Building AI products? Your dev process might be holding you back. LLMs aren't just features - they're part of the product. But traditional product development processes don't work when inputs & outputs are unpredictable. Here's why systematic testing infrastructure is crucial for shipping AI with confidence. https://lnkd.in/exDphmJi

Shipping LLM products at scale? The biggest challenge isn't building - it's knowing if they'll perform on the specific task at hand. Without reliable testing, you're flying blind. Especially at scale. That's why we built Reva: Our backtesting infrastructure helps teams validate and measure LLM performance against business outcomes. Now you can ship with certainty, not vibes. https://lnkd.in/eX5HgATP

🔍 New Analysis: We've just published an in-depth benchmarking study comparing customer service LLMs, specifically examining Intercom's transition from OpenAI to Anthropic. https://lnkd.in/efUxXxmG We've just launched our Alpha product and we're looking to talk with companies serious about driving real returns on their AI investment. #AI #LLM #OpenAI #Anthropic