Cossistant – open-source and open components support widget for React

Hacker News

I built Cossistant as a lightweight, open-source alternative to Intercom/Zendesk for NextJS/React devs. You can embed it with a simple NPM command and under 10 lines of code. The goal was so far to be a very very good human to human support platform, the next goal is to enable AI agents to auto-handle 80% of queries (train on your docs and knowledge) and eventually escalate to humans when needed. Everything is customizable with Tailwind or your custom React components. Support tools are bloated, pricey and never FEEL / LOOK like your product, this is why it's being shipped as part of your stack and not coming from someone else's. It's already generally available! Feedback/debates are welcome, what's missing?

Visit product View on Hacker NewsNov 21, 2025

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Actual performance

6points

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: agents, agent, code · Missing: mac, macos, cursor

92%92% 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

63%63% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Missing: https docs, excited, just released

59%59% 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

43%43% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews

25%25% 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

20%20% 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

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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