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DeciFlow

Turn text data into structured AI decisions

Developer Tools
Artificial Intelligence
GitHub
Visit WebsiteSee on Product HuntGithub ⧉

Hunted by정정인정정인

Apply custom AI criteria to text and JSONL data from local files, SSH, or HDFS. Combine classification, scoring, and yes/no judgments, review predictions, record human corrections, and automate follow-up with Python Actions. Run manual or scheduled batches, or monitor local and SSH files in realtime. HDFS supports batch reads. Use self-hosted Laya or the optional paid Jev API. Includes Docker Compose setup and sample datasets.

Top comment

Hi Product Hunt! I'm the developer of **DeciFlow**, an open-source AI-powered decision and workflow automation platform. I built DeciFlow to solve a practical problem: organizations generate enormous amounts of logs, operational events, and structured data, but turning that information into actionable decisions often requires complex pipelines, manual analysis, or expensive AI infrastructure. **What if we could turn raw data into structured AI decisions and automatically trigger the next steps?** That's the idea behind DeciFlow. DeciFlow connects to local or remote data sources, processes events using Laya or Jev decision engines, and produces configurable classification, scoring, and probability-based results. **Key capabilities:** - Analyze logs and JSONL datasets in batch or real time. - Define custom decision criteria for different use cases. - Use self-hosted Laya or the hosted Jev API. - Review AI predictions and record human corrections. - Connect decisions to downstream workflows through customizable Python Actions. - Deploy quickly with Docker, with optional GPU acceleration. My goal is to make AI-powered decision automation more accessible, flexible, and practical for developers, system engineers, and data teams. DeciFlow is still evolving, and I'd appreciate feedback from the community. **What kinds of operational data or business workflows would you want to automate with AI-driven decisions?** GitHub: https://github.com/call518/DeciFlow Thanks for checking it out!

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About DeciFlow on Product Hunt

“Turn text data into structured AI decisions”

DeciFlow was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #376 on the daily leaderboard. Apply custom AI criteria to text and JSONL data from local files, SSH, or HDFS. Combine classification, scoring, and yes/no judgments, review predictions, record human corrections, and automate follow-up with Python Actions. Run manual or scheduled batches, or monitor local and SSH files in realtime. HDFS supports batch reads. Use self-hosted Laya or the optional paid Jev API. Includes Docker Compose setup and sample datasets.

DeciFlow was featured in Developer Tools (521.6k followers), Artificial Intelligence (481.7k followers) and GitHub (41.4k followers) on Product Hunt. Together, these topics include over 252.7k products, making this a competitive space to launch in.

Who hunted DeciFlow?

DeciFlow was hunted by 정정인. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.

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