Hey Product Hunt! 👋
I want to share a story that led to building ReliAPI.
I was working on automating spam filtering for a bot, and I needed to get SQL responses from OpenAI's API. Everything seemed fine in development, but when I started processing real data... disaster struck.
Due to a bug in my code, most of the responses from OpenAI were invalid SQL queries. But I was still getting charged for every single API call - even the ones that were completely useless. The same invalid queries kept getting retried, and I was paying OpenAI for answers I couldn't even use. I lost way more than $200 before I realized what was happening.
I spent the entire weekend writing retry logic, implementing caching, adding idempotency checks, and setting up budget controls. It was 2 AM on Sunday when I realized: "Why am I rebuilding this every time? This should just exist."
So I built ReliAPI - a reliability layer that sits between your app and LLM APIs. It handles all the boring stuff: retries, caching, idempotency, budget caps. You just send your request, and ReliAPI makes sure it's reliable and cost-effective.
**What makes ReliAPI different from other API proxies:**
Unlike generic HTTP proxies, ReliAPI is built specifically for LLM APIs (OpenAI, Anthropic, Mistral) and HTTP APIs with features you won't find elsewhere:
- **Smart caching** - Reduces costs by 50-80% on repeated requests. Same question = instant response, no API call, no charge.
- **Idempotency protection** - Prevents duplicate charges when users click twice or retries happen. Same request with same key = only one charge.
- **Budget caps** - Automatically rejects expensive requests before they execute. No more surprise bills.
- **Automatic retries** - Exponential backoff and circuit breaker handle failures gracefully. No more manual retry logic.
- **Real-time cost tracking** - Every LLM response shows actual cost in USD. Track spending in real-time.
- **LLM-specific understanding** - Unlike generic proxies, ReliAPI understands token costs, streaming, provider rate limits, and LLM-specific error handling.
- **Works with OpenAI, Anthropic, Mistral, and any HTTP API** - No configuration needed for LLM providers, works with any REST API.
- **No code changes** - Just change the endpoint URL. Your existing code works as-is.
Since launching, we've helped developers save thousands of dollars on duplicate charges and failed requests. One user told us they reduced their OpenAI costs by 70% just by using caching.
**100% refund guarantee** - Try up to 10% of your requests, not satisfied? Full refund, no questions asked.
Try it on RapidAPI (link above) - no installation needed. Or use our SDKs (JavaScript, Python) or Docker image if you prefer.
I'd love to hear your stories! Have you ever lost money on API failures? What reliability features do you wish existed?
Let's make LLM API calls more reliable together! 🚀
Great product! I'm curious about the smart caching mechanism. Is the time to live for cached responses configurable, or is there a fixed default duration?
Automatic retries with proper backoff feel super helpful. no more writing the same logic again and again.
Impressive launch, ReliAPI team. From a clarity & onboarding lens: when a developer integrates this engine for the first time, what’s the one belief you want them to walk away with in the first 10–15 seconds? Is it: • “My API calls won’t fail or cost me surprise bills.” Or: • “This tool aligns with how I build—it doesn’t constrain me.” Because with infrastructure tools the adoption hinge often isn’t feature count—it’s trust that the system matches my workflow. Curious how you’re framing that for early users.
Wore solutions like this are needed - limit our waste on AI tools.
Thank you!
Great work. ReliAPI solves a real pain and does it cleanly. Congrats to you and the team.
