Create personalized AI Assistants driven by Notion (with no code)

Hacker News

We just shipped updates to our platform to make it super easy for users to connect their personal Notion workspace for using with LLM assistants (like ChatGPT). This means that you can do things like question answering on your notes, docs, code etc. for any use case you can think of. We built an Investor bot that answers common questions about our fundraising X-D https://app.algovera.ai/workflows/view?id=algovera-investor-... Some more ideas: job seeking bot, user feedback bot, dating bot, ... You can check out a demo video on our recent twitter post https://twitter.com/AlgoveraAI/status/1621243837246046209 More integrations coming soon like Discord and Slack. We use LangChain and GPT Index in the backend :) Would love to hear how it works for you. Oh and btw, if you're interested in getting funded to build an LLM app we run a $10k monthly microgrants program (sponsored by Ocean Protocol). You don't need to be technical to apply. The grants are a public good (no strings attached, equity free). Feel free to reach out if you want to brainstorm on ideas https://handbook.algovera.ai/docs/Handbook/Grants/Proposal%2...

Visit product View on Hacker NewsFeb 3, 2023

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Actual performance

4points

Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: slack, user, chatgpt · Missing: mac, agents, macos

87%87% 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

80%80% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: personal, video, month · Missing: mobile apps, ios, entrepreneurs

62%62% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

50%50% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

38%38% 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

16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency

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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