Sublingual: LLM Observability with zero changes to your code

▤ Summary

It works across a wide range of environments, capturing extensive logs including LLM interactions, inputs, outputs, and server call data. Through conversations with numerous founders, weve learned that theyre often too busy building to establish robust evaluation systems. So, they end up relying on a couple vibe tests before crossing their fingers and pushing to prod.Thats why we built Sublingualeffortless LLM observability that works out of the box. Minimize onboarding overhead: Weve hacked away at the complexity of automating integration so you can start collecting insights instantly. of DefenseMatthew (CEO): previously TikTok ML on the recommendation algorithm and ads engine, LLM research for rec-sys at Nextdoor

▦ Linked Companies