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CauseFlow AI
Find why your app broke in minutes, not hours
CauseFlow AI automates production incident investigation. Connect your stack (Slack, GitHub, Jira, CloudWatch) and let AI do the root cause analysis that used to take your team hours. Built for SMBs and small engineering teams who don't have a dedicated SRE. Privacy-first: a Docker agent masks sensitive data (PII, API keys, logs) before anything leaves your infrastructure. Usage-based pricing — no per-seat fees. Currently in beta.
Hey Product Hunt! 👋
I'm Vinicius — 13 years in engineering, the last stretch leading SRE, security, and platform teams. I've been the one in the war room at 3am, scrolling through dashboards, logs, and Slack threads trying to figure out why production just broke.
That investigation process — the one where you're jumping between CloudWatch, GitHub commits, Jira tickets, and Slack messages trying to piece together what happened — that's what CauseFlow AI automates.
🔍 What it does:
→ Connects to your existing stack (Slack, GitHub, Jira, CloudWatch)
→ AI investigates the incident automatically
→ Delivers root cause analysis in minutes instead of hours
🔒 Privacy-first:
We deploy a Docker agent in your infrastructure that masks sensitive data (PII, API keys, debug logs) before anything reaches our AI cloud. Built for GDPR/LGPD compliance from day one.
💰 No per-seat pricing:
Usage-based model. Your whole team can use it without worrying about seat count.
🎯 Built for:
Small and mid-size engineering teams (10-100 engineers) who don't have a full SRE team but still deal with production incidents regularly.
We're in early beta and I'd genuinely love your feedback — what would make this useful for YOUR team? What integrations would you need first?
Use code PRODUCTHUNT for priority beta access.
About CauseFlow AI on Product Hunt
“Find why your app broke in minutes, not hours”
CauseFlow AI was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #41 on the daily leaderboard. CauseFlow AI automates production incident investigation. Connect your stack (Slack, GitHub, Jira, CloudWatch) and let AI do the root cause analysis that used to take your team hours. Built for SMBs and small engineering teams who don't have a dedicated SRE. Privacy-first: a Docker agent masks sensitive data (PII, API keys, logs) before anything leaves your infrastructure. Usage-based pricing — no per-seat fees. Currently in beta.
On the analytics side, CauseFlow AI competes within Developer Tools, Artificial Intelligence and Development — topics that collectively have 984.8k followers on Product Hunt. The dashboard above tracks how CauseFlow AI performed against the three products that launched closest to it on the same day.
Who hunted CauseFlow AI?
CauseFlow AI was hunted by Vinicius Carvalho. 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.
For a complete overview of CauseFlow AI including community comment highlights and product details, visit the product overview.
Vinicius Carvalho