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Splat, an Affinity Diagramming Tool in a Single HTML File

Hacker News

Splat, an Affinity Diagramming Tool in a Single HTML File

Hi HN, I built a single-file, open-source affinity diagramming tool for qualitative analysis in the browser, called Splat. You can use it to cluster and organize notes on a board. It runs entirely in the browser as a single HTML file: – no install, no build step – works offline – optional semantic search with HF Transformers.js and AI assistant with Ollama (local) or OpenAI (for more power) – JSON export/import for analysis elsewhere I built Splat while manually clustering 1400+ notes of interview data for a research project. I wanted something I could email to collaborators and use and extend without worrying about accounts or bloat from proprietary services. We're using this internally in our research lab for affinity diagramming qualitative data. Would love feedback, especially from people doing qual research, UX, or synthesis work. Feel free to build on or extend!

Visit productView on Hacker NewsDec 29, 2025
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Product HuntOn track for Day 1 leaderboard · Strong signals: email, openai, single · Missing: mac, agents, macos
95%95% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
73%73% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: llama, io · Missing: https docs, excited, just released
47%47% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
38%38% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
36%36% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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