Devrim Ozcay's profile on Product Hunt

About

I work as a backend engineer, focusing mainly on Java and Spring Boot. Most of my experience revolves around building and maintaining microservices, working with REST APIs, handling performance issues, and improving system reliability. Outside of my full-time role, I’m building ProdRescue AI(https://www.prodrescueai.com/), a side project focused on turning messy production logs into structured incident reports. It’s something I started after seeing how chaotic incident documentation can become in many teams. I’m particularly interested in: Backend architecture Performance optimization Production debugging Writing clearer technical documentation I also share what I learn about backend engineering and real-world system problems on Medium.

Links

ProdRescue AI

Badges

Tastemaker

Gone streaking

Gone streaking 5

Maker History

ProdRescue AITurn 3 AM Slack chaos into board-ready reports & auto-fixes

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Joined Product HuntJuly 12th, 2024

Forums

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1d ago

Autonomous Incident Reports & Fixes - AI Workflow Automation

Stop spending 4 hours manually writing incident postmortems. ProdRescue AI reads your Slack threads, correlates logs, and generates board-ready RCAs in 2 minutes. What’s new in v2.0: • Autonomous Mode: AI searches your GitHub repo to suggest code fixes. • Evidence Mapping: Every claim is linked to source logs [1]. • Security-First: PII redacted locally; no log retention. From 3 AM chaos to a Pull Request—without losing sleep.

p/prodrescue-ai

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16d ago

How we handle log privacy and eliminate AI hallucinations in incident reports?

Hi everyone! As we launch ProdRescue AI today, I wanted to open a dedicated thread for the two most common questions we get from engineering leads: Data Privacy and Accuracy.

1. Data Privacy & Security: We know logs are sensitive. Our engine is designed to be ephemeral we process logs to generate the report and then they are gone. We don t store your raw logs, and we certainly don t use them to train any AI models. Plus, we have built-in PII masking to scrub sensitive data before it even hits the analysis layer.

2. Evidence-Backed Accuracy: The biggest fear with AI is "hallucination." We solved this by building an Evidence Mapping system. Every claim in a ProdRescue report (like a specific error or a timeline event) includes a direct reference to the exact log line it came from. If the AI can't find the evidence in your logs, it won't put it in the report.

I d love to hear your thoughts:

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16d ago

ProdRescue AI - Turn 3 AM messy logs into board-ready incident report in 1m

Turn messy logs and Slack threads into board-ready incident reports in 2 minutes. Evidence-backed RCA, no log retention, secure. Built for CTOs, VP Engineering, and SRE.