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JinaSRE
AI that monitors your app and fixes issues proactively
Jina proactively monitors your product and fixes issues before users face them. Unlike AI coding agents that operate blind in production, Jina maintains a live service topology and unified log intelligence — correlating signals across Datadog, Sentry, CloudWatch, and more into one timeline. It auto-generates monitors with every commit, groups noisy alerts into actionable issues, identifies root causes, and opens draft PRs with fixes.
We built Jina after running into the same problem again and again. Teams have monitoring everywhere but still miss real issues or get flooded with noise.
Monitors are manually set up and go stale as the code changes. When something breaks in production, you have to piece together logs, traces, recent PRs, and third party systems just to figure out what happened. That part is slow and messy.
We started with a simple question. What if monitoring stayed in sync with the code automatically, and every issue came with context, root cause, and a clear next step?
So we built Jina to:
* create monitors directly from code changes
* group signals across tools into one issue
* use logs, code, and system context to find root cause
* suggest fixes and open a PR when possible
The main shift for us was realizing this is not about better alerts. It is about going from alert to fix without the manual work.
Curious how others are handling this today. Are you still tuning monitors manually or trying to automate this layer end to end?
About JinaSRE on Product Hunt
“AI that monitors your app and fixes issues proactively”
JinaSRE was submitted on Product Hunt and earned 14 upvotes and 1 comments, placing #73 on the daily leaderboard. Jina proactively monitors your product and fixes issues before users face them. Unlike AI coding agents that operate blind in production, Jina maintains a live service topology and unified log intelligence — correlating signals across Datadog, Sentry, CloudWatch, and more into one timeline. It auto-generates monitors with every commit, groups noisy alerts into actionable issues, identifies root causes, and opens draft PRs with fixes.
On the analytics side, JinaSRE competes within Software Engineering and Artificial Intelligence — topics that collectively have 508.7k followers on Product Hunt. The dashboard above tracks how JinaSRE performed against the three products that launched closest to it on the same day.
Who hunted JinaSRE?
JinaSRE was hunted by Krish Chelikavada. 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 JinaSRE including community comment highlights and product details, visit the product overview.
Krish Chelikavada