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FixBugs vs SunsetLint

A side-by-side comparison built from both listings. Blank cells mean the company has not given that detail; we never guess.

FixBugs compared with SunsetLint
DetailFixBugs logo FixBugsSunsetLint logo SunsetLint
What it doesAI debugging for modern engineering teams Find retiring AI model IDs in your code before the shutdown date
StageStartup Not given
Founded2025 Not given
Based inUS IN
Pricing modelFreemium Freemium
PricingFree Trial: 3 bug fixes per month. Pro: $33/month for 15 bug fixes per month (or $24.75/month billed as $297/year with annual discount). Super User: $60/month for 30 bug fixes per month (or $45/month billed as $540/year with annual discount). Enterprise: Custom pricing with custom bug fix volume. Free: All public repositories and first 3 private repositories. Pro: $29 per month or $290 per year per GitHub account, includes every private repository, scans on every push, and pull request checks.
Key features
  • Automated alert triage from monitoring stack
  • Root cause analysis across distributed systems
  • Issue reproduction in controlled environment
  • Validated fix generation with test cases
  • VS Code extension for local debugging
  • GitHub App for automated analysis
  • Self-hosted deployment option
  • Integration with logs, traces, metrics and alerts
  • Visible reasoning chain for every fix
  • Triage sessions shareable and reloadable
  • Scans code repositories for retiring AI model identifiers
  • Reports file path, line number and shutdown date for each match
  • Person-verified rules checked against provider notices
  • Scans Python, TypeScript, JavaScript, Go, Java, Ruby, PHP, C#
  • Uses literal strings and patterns, never sends code to AI
  • Covers Anthropic, OpenAI, Bedrock, Vertex, Azure, Stripe, Twilio
What makes it different
  • Validation-first approach with reproduction tests and regression verification
  • Built specifically for debugging existing bugs, not writing new code
  • Handles complex distributed systems with stateful, auditable workflows
  • No hard upper limit on context, processes automated log and trace ingestion
  • Local deployment keeps code on user's machine
  • Finds exact file and line numbers where retiring models are used, not just which models are retiring
  • Verifies every rule against provider's official notice before shipping
  • Free for all public repos and first 3 private repos
  • Never modifies code, has read-only access to repositories
Community votes00
DR (Domain Rating by Ahrefs)36 −1 (down) since last checkNot checked yet no change since last check
Trust Flow (Majestic)00
Citation Flow (Majestic)130
Referring domains (Majestic)730

6 details filled in for both companies.

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