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Airbolt – Call LLM APIs from your app with zero back end

Hacker News

Airbolt – Call LLM APIs from your app with zero back end

Hi HN! We love the "backend-less" stack: Stripe for payments, Supabase for data, Clerk for auth. But the moment we add AI features, we're forced to spin up a backend to hide API keys, implement per-user token-based rate limits and graceful degradation, etc. So we built Airbolt. What it does: Drop in our SDK and start making OpenAI calls directly from your frontend. Your keys are AES-256-GCM encrypted on our servers, never exposed to the client. We provide token-based per-user rate limits and origin allow lists to address inference abuse. Short-lived JWTs and bring-your-own-auth are coming soon (like this week). Why this matters: Current tools solve fragments. Teams still build custom backends. The cost compounds: more code, more bugs, slower shipping, and worse AI-coding tool performance as context grows. We provide a TypeScript API, React Hooks, and React Component. Coming soon: - Multi-provider support (OpenRouter, Anthropic, Gemini, and more) - No-redeploy upgrades: we want our self service dash to be your "control plane" so you cane change providers, models, context and more without changing your project source and redeploying - Native mobile SDKs - Bring-your-own-auth integration (Auth0, Clerk, Auth.js, etc) - RAG/vector search Built this after implementing the same proxy pattern for the 10th time. When we consider ease of use and speed vs flexibility tradeoffs, we're intentionally choosing extreme ease and speed (when it seems everyone else is building more ways to define complex agents). Try it out: https://www.airbolt.ai/ mark@airbolt.ai

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Product HuntOn track for Day 1 leaderboard · Strong signals: agents, agent, model · Missing: mac, macos, cursor
98%98% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
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