Pneumatic – free open-source workflow software

Hacker News

Hi HN, I'm one of the co-founders of Pneumatic, an enterprise-grade workflow software designed for small, fast-growing startups. Yesterday, we released Pneumatic under the Apache 2.0 license. If your team has used Trello, Basecamp, or Asana before and you're now looking to implement a more structured, mature approach by building repeatable task sequences, you should try Pneumatic. Here's what Pneumatic offers: - Task sequences defined by templates. Design a template once and run multiple instances of a process based on this reusable template—manually, via API, or with a public share kick-off form. - An intuitive, user-friendly Workflow Template Editor. - Workflow conditions to skip tasks or create branches. - Dynamic task performer assignment: defined by the template or variable, based on conditions. - Email, mobile, push, and REST notifications for all major events, such as when workflows start/stop, tasks start/stop, mentions, and more. - Support for parallel tasks. And much more. Some of the most popular use cases include chains of approvals, employee or customer onboarding, software development and design processes, and content creation workflows for teams. I’d love your feedback and questions. You can reach me at anton.seidler@pneumatic.app

Visit product View on Hacker NewsOct 24, 2024

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

89%89% 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: para · Missing: supports, reddit linkedin, podcasting

71%71% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

66%66% 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 · Strong signals: para · Missing: mobile apps, ios, personal

36%36% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

13%13% 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

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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