No-Code AI-Powered Workflow Builder

Hacker News

I’ve been working on this app for about half a year and am very excited to share it with you all! How it works: 1. Connect with the tools your business uses (currently Slack or Gmail). 2. Create workflows by dragging and dropping nodes onto the canvas. 3. Listen to incoming events or trigger workflows manually. Behind the scenes: 1. Each workflow runs as a durable, long-running execution. 2. AI agents within the same workflow share memory. 3. AI agents associate different channels, such as Slack threads or Gmail email threads, with workflows and can understand when replies are linked to specific workflow executions. Try it out: https://tryworkloop.com There will be bugs!! But I’d really appreciate your feedback.

Visit product View on Hacker NewsDec 18, 2024

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

90%90% 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

70%70% 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: excited, io · Missing: https docs, just released, exist

42%42% 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

40%40% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

19%19% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

17%17% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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