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Alternatives

Products that do what Decipher – An AI powered error monitoring tool does

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…

  1. 1
    Agnost AI287

    Catch agent failures your evals miss

    12d ago · agnost.ai

  2. 2

    Open-source monitoring for machine learning models

    2021

  3. 3

    Trace, evaluate, and improve AI agents in production

    Aug 2026 · telerik.com

  4. 4
    Sentry265

    Stop hoping your users will report errors

    2018

  5. 5

    Debug like never before with the power of AI

    2023

  6. 6

    Complete Frontend Error Tracking at an Affordable Price

    2024

  7. 7
    Takipi75

    Error Analytics - see a replay of the code causing an error

    2014

  8. 8
    Repodex118

    Automatically find and fix errors

    2023

  9. 9
    Tracea80

    Datadog for AI agents with traces, RCA, and team memory

    May 2026

  10. 10

    Let machine learning catch software problems

    2020

  11. 11

    Visual feedback and bug reporting for busy product teams

    2024

  12. 12AB

    Hey everyone, My friend and I built a simple bug fixing app that listens for alerts/issues from Sentry, contextualizes it against your codebase, and any other data sources you wish to connect (right now we support Notion, Google Docs, and Slack), and deploys an ai agent to write a PR for review in Github or Gitlab to solve the bug. Our current demo shows the end-to-end process for a trivial bug fix, but we have been testing it with open source python repos like http-pie, comparing how our agent solves a bug compared to a human engineer and it gets fairly close. We are working on adding…

    2023 · resolvd.ai

  13. 13

    Every tool sees errors. Only debugai knows your codebase.

    Jun 2026 · debugai.io

  14. 14
    OurBase24

    AI finds the bug. You ship the fix.

    Jun 2026 · ourbase.ai

  15. 15

    Hey HN, I’m Abhishek. I'm building Opslane, an open-source agent that identifies user-facing issues and investigates them. It only creates a PR if it can verify the fix. Demo: https://youtu.be/ccuOTYQMeYg Docs: https://docs.opslane.com At my last job at Robinhood, we used to do a quarterly bug bash. We would go through our Sentry backlog and try to fix as many of them as possible. We only fixed bugs we knew were reported by customers. We had hundreds of bugs, and Sentry’s default priority levels made no sense. After the bug bash, we would declare bankruptcy - select…

    10d ago · github.com

  16. 16

    AI code reviews & Pipeline debugging

    2024

  17. 17IN

    Tl;dr: I trained a classifier to route to the least expensive model and reasoning depth to complete the request. Coupling that with additional automated token efficiency techniques has yielded 3x usage for the same spend. For anyone interested in trying it themselves: https://nerfguard.com Various teammates and I switched over to Codex from Claude Code recently. We still bounce between the tools, but Codex’s speed and steerability coupled with performance gains were hard to ignore. One of the downsides was that the per token pricing kicked in way sooner. This is happening across…

    Jun 2026

  18. 18
    Bugsly2

    AI error tracking that explains and suggests bug fixes

    27d ago · bugsly.dev

  19. 19

    For websites & apps to self-heal themselves.

    Jul 2026 · faultfixer.com

  20. 20GY

    Hi all, I've been working on this devtool for 1 month now for myself at first and I'll be curious to see if it's something that could work for you as well. So basically, it detects bugs in your website in production from real user sessions, an llm clusters them by severity and it provides the complete context of the issue that you can copy-paste into your coding agent to fix it in one go. Why did I create it? I've been shipping fast with tools like Cursor and Claude Code. The problem? When bugs happen in production, these tools have zero context about what actually went wrong. Sentry is…

    Nov 2025 · sonarly.dev

  21. 21

    Instant bug reports your AI agent can actually debug

    Jul 2026 · tracebug.dev

  22. 22AB

    Hi everyone! My team and I just open-sourced a bunch of cool agent dev tools: Invariant Explorer to visually inspect and understand AI traces and a testing framework, building on pytest.

    2024 · github.com

  23. 23GO
  24. 24WV

    Hi HN, I'm the CEO at https://replay.io. We've been working on time travel debugging for web development for a while (https://news.ycombinator.com/item?id=28539247) and more recently an AI app builder that uses that debugger to get past problems instead of spinning in circles (https://news.ycombinator.com/item?id=43258585). We've gotten to where we can pretty easily build apps to replace business-critical SaaS tools, some of which we're now using internally: * We built our own issue tracker to keep track of all our development projects, tickets, bug…

    Dec 2025

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