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VernLLM
The resilience layer for LLM calls
VernLLM is a lightweight resilience layer for LLM clients that handles retries, timeouts, circuit breakers, caching, rate limiting, observability and cross provider fallbacks for your calls. Works with OpenAI, Anthropic, Bedrock, Gemini, and 30+ providers. Get schema-validated outputs, cache coalescing, tool calling, and streaming too. Framework agnostic and adapter-based, so you can swap providers easily. Built to save teams the sprints and incidents of maintaining LLM infrastructure.
Hey Product Hunt!
I built VernLLM after watching the same pattern repeat across every LLM project I touched. Someone ships a naive wrapper around the provider's chat completion call, it works fine in the demo, then a provider hiccups in production and the whole pipeline goes down because there was no retry, no timeout, no fallback.
VernLLM is my answer to that. It's a resilience layer, not a new SDK to learn. Bring your existing OpenAI, Anthropic, or any other client, wrap it, and get retries, circuit breaking, provider fallback, rate limiting, caching, and structured output validation for free.
A few things I'm especially proud of. Cache coalescing that actually prevents stampedes on concurrent misses, not just a wrapper around a key value store. Circuit breakers that are isolated per target, so one provider tripping doesn't affect another. And zero magic, every feature is opt in, fully typed, and documented with real API shapes, not marketing pseudocode.
I'm one engineer who got tired of writing this from scratch on every project, so I made it something the community can rely on instead. Would genuinely love to hear what you're running into with LLM reliability in your own stack, and what would make VernLLM a fit for it.
About VernLLM on Product Hunt
“The resilience layer for LLM calls”
VernLLM was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #35 on the daily leaderboard. VernLLM is a lightweight resilience layer for LLM clients that handles retries, timeouts, circuit breakers, caching, rate limiting, observability and cross provider fallbacks for your calls. Works with OpenAI, Anthropic, Bedrock, Gemini, and 30+ providers. Get schema-validated outputs, cache coalescing, tool calling, and streaming too. Framework agnostic and adapter-based, so you can swap providers easily. Built to save teams the sprints and incidents of maintaining LLM infrastructure.
On the analytics side, VernLLM competes within API, Developer Tools, Artificial Intelligence and GitHub — topics that collectively have 1.1M followers on Product Hunt. The dashboard above tracks how VernLLM performed against the three products that launched closest to it on the same day.
Who hunted VernLLM?
VernLLM was hunted by LakBud. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of VernLLM including community comment highlights and product details, visit the product overview.
LakBud