Pool Damage Reports & Estimates AI
Made by pool pros who hated wasting time on paperwork!
What it does
Turn hours of tedious insurance paperwork into a professional, ready-to-send document in just 15 minutes. This intelligent assistant learns from your previous reports, automatically pulls accurate historical weather data & adjusters names, analyzes your photos based on your instructions, writes in your personal style, and creates a complete editable estimate. The final branded PDF is formatted the way insurers prefer, helping you save time while increasing your claim approval rate and revenues.
Does the same job
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AI Prompts for Insurance AdjustersMay 2026 · cotonix.gumroad.com · ▲3Cut report writing time in half with copy-paste AI prompts
QuickQuote AIJul 2026 · quickquote-ai-woad.vercel.app · ▲7AI estimate generator for service contractors
- IBI built AI that turns 4 hours of financial analysis into 30 seconds2025 · duebase.com · ▲15
I built Duebase AI to solve a problem I kept running into in fintech - analyzing UK company financial health takes forever. The process usually goes: download PDFs from Companies House → manually extract data to spreadsheets → calculate ratios → interpret trends. Takes 3-4 hours per company and requires serious financial expertise. The technical challenge: Companies House filings are messy. Inconsistent formats, complex accounting structures, missing data, and you need to understand UK accounting standards to make sense of it all. My approach: Parse 15M+ UK company records from Companies…
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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, May 2026
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Parallel agents, diff reviewer, and multi-model comparisons
Dev tools · May 2026 · kilo.ai
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Hey HN, Henry here from Cactus. We open-sourced Needle, a 26M parameter function-calling (tool use) model. It runs at 6000 tok/s prefill and 1200 tok/s decode on consumer devices. We were always frustrated by the little effort made towards building agentic models that run on budget phones, so we conducted investigations that led to an observation: agentic experiences are built upon tool calling, and massive models are overkill for it. Tool calling is fundamentally retrieval-and-assembly (match query to tool name, extract argument values, emit JSON), not reasoning. Cross-attention…
Life & fun · May 2026 · github.com
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Dev tools · May 2026 · github.com