Pi
PipelineIQ – AI diagnoses CI/CD failures and sends fixes to Slack
Hacker NewsPipelineIQ – AI diagnoses CI/CD failures and sends fixes to Slack
I built this after watching engineers spend 30-60 minutes staring at pipeline logs. You add one step to GitHub Actions — when a pipeline fails, Claude analyzes the logs and sends the root cause + specific fix steps to Slack within seconds. Stack: FastAPI, Supabase, Claude API, Slack API. Free beta, looking for feedback from engineering teams.
Share cardActual performance
1points
Did not reach leaderboard
Launch Intel predictions
Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Strong signals: claude, slack · Missing: mac, agents, macos95%95% 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.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal38%38% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: pipe, io · Missing: https docs, excited, just released31%31% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue29%29% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting20%20% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive13%13% predicted probability of success on AppSumo, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto12%12% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
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