Alternatives
Products that do what Airbolt – Call LLM APIs from your app with zero back end does
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…
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Howdy all. I'm Zack :wave:. I've been thinking about the problem of misguided AI pull requests and figured I'd throw a possible solution out there for feedback. Basically, CleverCrow lets supporters give tokens to a GitHub repo (or set of issues in that repo) for the maintainers to use to build/fix stuff. The fun implementation challenges have been around implementing the pooling dynamics and keeping the maintainers in charge while the backers are motivated to support their work.
Jun 2026 · clevercrow.io
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Hey there! At our company, Bit Complete [1], we use Airtable a bunch for managing operations. We really like how easy it is to throw up a form to collect information, or to build automations for offline processing like aggregations. One challenge we kept running into was how to build more complicated interactive apps using the API, while maintaining fine-grained access control to Airtable data. Airtable ties identity to API access control via API keys, which makes it very hard to build apps with realistic access control needs. So we built AirQL! [2] It’s a utility layer between Airtable’s…
2022 · airql.dev
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Hi HN, I was once given the advice: Don't waste expensive frontier model credits (GPT/Claude/etc.) on bulk work. Send the boring, repetitive, high-volume jobs to a smaller model, and save the expensive prompts for when you actually need frontier-level reasoning. I complained and told my manager that I shouldnt have to think about using certain models for certain coding tasks, and that one model should handle everything. Well, here we are anyway. If anyone needs a place to absolutely abuse an LLM with high-volume tasks, come beat ours up at https://yolo-auto.com. Here are…
Jul 2026 · yolo-auto.com
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Hi HN, I’m the creator of Cordum. I’ve been working in DevOps and infrastructure for years (currently in the fintech/security space), and as I started playing with AI agents, I noticed a scary pattern. Most "safety" mechanisms rely on system prompts ("Please don't do X") or flimsy Python logic inside the agent itself. If we treat agents as autonomous employees, giving them root access and hoping they listen to instructions felt insane to me. I wanted a way to enforce hard constraints that the LLM cannot override, no matter how "jailbroken" it gets. So I built Cordum. It’s an open-source…
Jan 2026 · github.com
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ArgusAI ▲7AI firewall for LLM calls, MCP tools, and agentic workflows
Jul 2026 · argusai-tau.vercel.app
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Hi everyone, Airstrip is an open-source platform for users to build internal AI agents. We've made some major changes since our last release. - Improved chat experience with a memory layer: For this, we are using Mem0. This can be configured when creating the agent. - Notion-style editing to configure agent: A sleeker UI and a familiar editing experience for our users. - Encrypted API keys and only decrypted at the point of usage. We are using Infisical to store our encryption keys, ensuring greater security. - Add knowledge bases to chat assistants. We are using Unstructured to handle the…
2024 · airstrip.pro
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Hi hacker news, My name is Dillion and I'm the creator of llm.report. A few months ago, I was frustrated by the lack of observability into the OpenAI API. All of us are left in the dark about API performance, latency, cost calculation, cost breakdown, and more. I just wanted to know more about how my AI app is performing in production and make data-driven decisions to improve the product. So I ended up just building it myself. There are three parts to the platform: 1. OpenAI API Dashboard (no-code) - Enter your OpenAI key and get access to detailed insights straight from the OpenAI API…
2023 · github.com
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I’ve spent the last 2.5 months building a product that runs LLM-powered code reviews on my pull requests — and I just launched it. The tool is built specifically for solo developers. You install it on your repo, trigger a scan by creating a pull request, and it leaves structured review comments using OpenAI under the hood. Funnily enough, I used the dev version of this app to review its own pull requests while building it. It helped me spot bugs, simplify structure, and keep quality high — all with minimal need for another human in the loop. Things I want to try out in the next months : -…
2025 · codii.dev
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Hi HN, Matvey, Ildar, Joey, and Dominik here. If you're building LLM agents that use tools, you're probably worried about prompt injection attacks that can hijack those tools. We were too, and found that solutions like prompt-based filtering or secondary "guard" LLMs can be unreliable. Our thesis is that agent security should be handled at the network level between the agent and the LLM, just like a traditional web application firewall. So we built Archestra Platform: an open-source gateway that acts as a secure proxy for your AI agents. It's designed to be a deterministic firewall against…
Oct 2025 · archestra.ai
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Hey HN! I am a developer working on a startup doing lots of payment integration stuff with payment providers like Stripe. I built a tool to talk to Stripe data, just so that I can answer questions from our team. I turned that into analytics tool (sort of) to answer questions about MRR, churn, revenue etc. (https://www.dataraccoon.io/). There is a two minute demo video on the page if you want to see how it works, or you can use free trial without needing a credit card. I was wondering if you would use such a tool directly in Slack or prefer receiving messages about your metrics…
2024 · dataraccoon.io
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The open AI canvas — your keys, your models, zero lock-in.
May 2026 · open-canvas-ashy.vercel.app
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Hello HN, we're Andrew and Stephen from Keyboard (https://www.keyboard.dev/). After building AI tools for the past year, we recently made a YouTube video on building MCP servers and realized MCP is a total game-changer. It essentially lets AI do anything by connecting to your apps. But the deeper we dove, the clearer it became that security and privacy were complete afterthoughts. Coming from backgrounds at Okta and Stripe, this made us pretty uncomfortable. We kept seeing the same pattern: every app needs its own MCP server, each storing sensitive tokens, with minimal…
2025 · github.com
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