Alternatives
Products that do what Quell – AI QA Agent Working Across Linear, Vercel, Jira, Netlify, Figma does
Hey HN! I've been building Quell, an AI QA testing agent designed to run tests directly triggered from issue trackers (Jira, Linear) or designs (Figma) or CI/CD platforms (Vercel, Netlify, GitHub), ensuring rapid and accurate acceptance testing without manual effort. What problem does it solve? As a product manager and founder myself, I constantly faced issues releasing a new feature only to discover critical bugs or that the build doesn't fully meet acceptance criteria. Bottlenecks in our QA and release process—tickets and issues stuck in manual testing, slow deployments due to delayed…
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Hey, Jared Palmer (creator of this playground) here. Really excited to ship this. I’ve been building this over the past few weeks to compare LLMs from different providers like OpenAI, Anthropic, Cohere, etc. At Vercel, I manage our Frameworks division (including Next.js, Svelte, and Turbo) and wanted to also dogfood some of the latest features in a slightly larger application. This playground takes a lot of inspiration from https://nat.dev and is built on Tailwind, ui.shadcn.com, and some upcoming Vercel products we’re announcing soon. We’re going to continue adding models to…
2023 · play.vercel.ai
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I'm Dan, and I built a CLI that lets AI agents design in Figma. What it does: 100 commands to create shapes, text, frames, components, modify styles, export assets. JSX importing that's ~100x faster than any plugin API import. Works with any LLM coding assistant. Why I built it: The official Figma MCP server can only read files. I wanted AI to actually design — create buttons, build layouts, generate entire component systems. Existing solutions were either read-only or required verbose JSON schemas that burn through tokens. Demo (45 sec): https://youtu.be/9eSYVZRle7o Tech…
Jan 2026 · github.com
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QA agent that tests apps the way you'd explain them
Jul 2026 · swiftscalesoftware.com
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GitHub - https://github.com/vostride/agent-qa Live Demos - https://vostride.com/demo/agent-qa
May 2026 · vostride.com
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Spelltest framework simulates conversations between AI ‘synthetic users' in an environment to test and refine LLM-based applications. It ensures your app converse with utmost accuracy and relevance. Post-chat, Spelltest assesses responses, providing qualitative and quantitative feedback on performance. Suitable for both chat and completion modes. When to use: - After modifying your prompt. - When your LLM provider updates. - As a CI step for you repo. All feedback and collaborations appreciated!
2023 · github.com
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I'm one of the creators of The Edge Agent (TEA). We built this because we needed a way to deploy agents that was verifiable and robust enough for production/edge cases, moving away from loose scripts. The architecture aims to solve critical gaps in deterministic orchestration identified by *Prof. Claudionor Coelho Jr. (Stanford alum, ML/DL Faculty at Santa Clara Univ., and Senior Fellow for AI at Majestic Labs)* during our work on the Kiroku project. *Key Technical Features:* * *Neurosymbolic Native:* We integrated Prolog to logically validate LLM outputs. This combines neural…
Jan 2026 · fabceolin.github.io
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I've spent the past few years building 50+ AI agents in prod (some reached 1M+ sessions/day), and the hardest part was never building them — it was figuring out why they fail. AI agents don't crash. They just quietly give wrong answers. You end up scrolling through traces one by one, trying to find a pattern across hundreds of sessions. Kelet automates that investigation. Here's how it works: 1. You connect your traces and signals (user feedback, edits, clicks, sentiment, LLM-as-a-judge, etc.) 2. Kelet processes those signals and extracts facts about each session 3. It forms hypotheses…
Apr 2026 · kelet.ai
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