I built an AI workforce platform with a Notion-like editor

Hacker News

Hi HN, I built a platform for creating an AI workforce. It allows you to create and deploy AI agents with a Notion-like, no-code editor. I started working on it because current AI agent builders, like n8n, felt too complex for the average user. Since the goal is to enable an AI workforce, it needed to be as easy as possible so that busy founders and CEOs can deploy new agents as quickly as possible. We support 2500+ integrations including Gmail, Google Calendar, HubSpot etc We use our product internally for these use cases. - Reply to user emails using a knowledge base - Reply to user messages via the chatbot on acris.ai. - A Slack bot that quickly answers knowledge base questions in the chat - Managing calendars from Slack. - Using it as an API to generate JSON for product features etc. Here is the demo: https://www.youtube.com/watch?v=Yu7baf7RkWM We would appreciate your feedback and are excited to see what you will build with it!

Visit product View on Hacker NewsMay 20, 2025

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

98%98% 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 · Strong signals: started, including · Missing: supports, reddit linkedin, podcasting

73%73% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: excited, io, including · Missing: https docs, just released, exist

67%67% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRFits verified-revenue profile · Strong signals: google, answers · Missing: mobile apps, ios, personal

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

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

26%26% 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

17%17% 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.

Incorrect prediction on native model

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