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ReliaMesh
Open-source reliability infrastructure for AI agents
ReliaMesh detects reliability regressions in AI agents using application-reported outcomes. Track failures, performance changes and incident recovery without collecting prompts or responses. Open-source and self-hostable.
Hi everyone, I'm the founder behind ReliaMesh.
I started working on this because traditional infrastructure monitoring doesn't always capture whether AI agents are actually completing their tasks.
An API can return HTTP 200 while an agent produces malformed output or starts failing after a model or prompt update.
ReliaMesh is my attempt to make those regressions easier to detect and investigate.
The current v0.2.0 release includes a Python SDK, self-hosted server, deterministic regression detection, and incident recovery tracking.
There's also a reproducible synthetic demonstration in the repository.
It's early-stage software, and I'm particularly interested in feedback from engineers operating AI agents in production.
GitHub: https://github.com/PrefilerLabs/...
Would love to know how others are approaching agent reliability today.
About ReliaMesh on Product Hunt
“Open-source reliability infrastructure for AI agents”
ReliaMesh was submitted on Product Hunt and earned 2 upvotes and 1 comments, placing #147 on the daily leaderboard. ReliaMesh detects reliability regressions in AI agents using application-reported outcomes. Track failures, performance changes and incident recovery without collecting prompts or responses. Open-source and self-hostable.
On the analytics side, ReliaMesh competes within Open Source, Artificial Intelligence, GitHub and Web3 — topics that collectively have 599.5k followers on Product Hunt. The dashboard above tracks how ReliaMesh performed against the three products that launched closest to it on the same day.
Who hunted ReliaMesh?
ReliaMesh was hunted by Karan Sahu. 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 ReliaMesh including community comment highlights and product details, visit the product overview.
Karan Sahu