TrustStack
Vendor reviews in hours: Evidence Pack, Diff & Approval log
What it does
Stop chasing PDFs and spreadsheets. Upload a vendor packet—or just a questionnaire—and get evidence-backed drafts, a PDF Evidence Pack, a Diff report, and an Approval log. What's different: - Evidence-first: every answer cites its source. No evidence = Unknown. - Diff-first: annual renewals show only what changed. - Approval-log-first: who approved what, and why. Try Mode 0 instantly. Mode 1: questionnaire only. Mode 2: NDA + secure upload.
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- DBDiffing Binary FilesAug 2026 · withkord.com · ▲19
My partner reviews a lot of P&IDs (piping and instrumentation diagrams) and the adjacent files involved (excel, docx, pdfs, acd/l5x, etc). In his company, these are usually done in Bluebeam. It's really hard to see the diff + keep track of all the revisions resulted by these iterations. They end up storing files like "rev3_final_redlined.pdf". We've been looking for something close to Github to do these reviews, but haven't found one easy enough for folks with no CLI experience to understand and use (happy to check out more tools if you know any). So I built withkord.com to help with…
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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.
AI · 17d ago · simedw.com
Astute▲585Automate your B2B brand going viral, with new media creators
AI · 19d ago · company-app.joinastute.com
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
