
Certifai
Catch AI hallucinations before they reach your users
What it does
Most AI hallucination tools check if content is true. But the failures that actually break agent pipelines are often structural: invented JSON fields, mismatched tool outputs, or prompt injections hidden in retrieved content. This suite runs four suppressors in one API call: grounding checks, injection detection, JSON schema validation, and tool‑response verification. Available as a REST API and MCP server. Free tier (500 requests/month) at certifai.dev
Does the same job
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TestMyPrompt25d ago · testmyprompt.net · ▲4Find vulnerabilities in your AI prompts before your users do

Truth MirrorJun 2026 · wuyijia.gumroad.com · ▲2Real-time AI hallucination detection. Don't trust, verify.

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I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
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Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
AI · 27d ago · cactuscompute.com


Launched alongside, March 2026
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Switch from ChatGPT to Claude with import memory feature
AI · Mar 2026 · claude.com


