Decipher – An AI powered error monitoring tool
Hi HN, we’re Rohan and Michael from Decipher (https://prod.getdecipher.com/docs) and we’re working on an AI-powered error monitoring tool that helps engineers quickly understand what went wrong, the user impact, and how to fix it. It’s an alternative to tools like Sentry and BugSnag. We noticed that when there’s an application error it often takes too much time to figure out which issues are important and how to fix them. Because the overhead is too high, people (including us…) sometimes just pay attention to bugs that come directly from a user complaint. We were initially…
Decipher – An AI powered error monitoring tool launched on March 18, 2024 with 7 votes, #1,840 of 4,270 launches that month and more than 75% of that year's launches. The site was not reachable when checked in September 2026.
What it does
In the maker’s words, at launch
Hi HN, we’re Rohan and Michael from Decipher (https://prod.getdecipher.com/docs) and we’re working on an AI-powered error monitoring tool that helps engineers quickly understand what went wrong, the user impact, and how to fix it. It’s an alternative to tools like Sentry and BugSnag. We noticed that…
Does a similar job
all alternatives →- AOAn open-source lib to summarize sessions (rrweb) when users hit bugs2024 · getdecipher.com · ▲11
Hi HN, Rohan and Michael here from Decipher (https://getdecipher.com/). We’re excited to introduce AI-generated session summaries and open source the pipeline. It processes raw rrweb events to produce plain English summaries of what happened leading up to and around an error. You can find the code here: https://github.com/decipherai/session-replay-analyzer We created Decipher because we were frustrated with noisy alerts, time-consuming error triaging, and customer churn due to bugs and session replay analysis is a powerful step forward. Here’s an…
TrailsJan 2026 · trails-red.vercel.app · ▲81Hey all, Justin here. I previously built Phind, the AI search engine for developers. One of the biggest problems we had there was figuring out what went wrong with bad searches. We had tons of searches per day, but less than 1% of users gave any explicit feedback. So we were either manually digging through searches or making general system improvements and hoping they helped. This problem gets harder with agents. Traces are longer and more complex. It takes more effort to review them, so I'm building a tool that lets you analyze LLM outputs directly to help developers of LLM apps and agents…
Ellipsis – Automated PR reviews and bug fixes2024 · ellipsis.dev · ▲121Hi HN, hunterbrooks and nbrad here from Ellipsis (https://www.ellipsis.dev). Ellipsis automatically reviews your PRs when opened and on each new commit. If you tag @ellipsis-dev in a comment, it can make changes to the PR (via direct commit or side PR) and answer questions, just like a human. Demo video: https://www.youtube.com/watch?v=X61NGZpaNQA So far, we have dozens of open source projects and companies using Ellipsis. We seem to have landed in a kind of sweet spot where there’s a good match between the current capabilities of AI tools and the actual needs of…


We built an AI to review your pull requests2025 · infinitcode.ai · ▲53Hey HN, We’re two developers (co-founders) with a team of 20 who got tired of spending hours reviewing PRs, so we built Infinitcode.ai, an AI-powered code reviewer that: - *Summarizes PRs in plain English*: No more deciphering 1,000-line diff jungles - *Catches more than bugs*: Security holes, performance pitfalls, code smells, even typos (yes, we’ll flag “vurnerabilities” and vulnerabilities) - *Zero onboarding*: Works instantly—no “let me learn your codebase for weeks” nonsense. Why we’re posting: We’re in alpha and need brutal honesty. Roast our tool, mock our UI, or tell us why AI will…
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