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LLMtrack vs Backloop

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

LLMtrack compared with Backloop
DetailLLMtrack logo LLMtrackBackloop logo Backloop
What it doesReal-time AI cost tracking for every LLM call, broken down by feature, model and customer Catch where AI agents get stuck on your API or MCP server, rank problems by impact, and draft fixes as pull requests
StageNot given Not given
FoundedNot given Not given
Based inNot given US
Pricing modelFreemium Freemium
PricingFree: 3,000 events/month, full analytics dashboard, unlimited integrations, model savings recommendations, feature and per-customer cost breakdown, cost calculator, spend forecast, CSV export, 30-day data retention. Pro: $11.99/month, everything in Free plus 25,000 events/month, email alerts, busine Open source: free. Team: $199/month with 14-day free trial (1 API or MCP service, 25,000 reports/month, 15 coding-agent runs/month). Business: $799/month (up to 3 services, 250,000 reports/month, 60 coding-agent runs/month). Extra coding-agent runs: $6 each.
Key features
  • Real-time cost tracking with <1ms added latency
  • Breakdown of costs by feature, model and customer
  • Daily price synchronization from 428 models across 12 providers
  • No proxy in request path, fire-and-forget async integration
  • Prompts and completions never stored
  • Session replay for MCP servers to identify failed agent sessions
  • Clustering reports by agent goals and workflows
  • Priority ranking weighted by frequency, failed workflows, and affected accounts
  • Claude Code generates pull requests with tests
  • Review queue with diff, tests, agent reports, and evidence
  • Isolated git worktree prevents unauthorized code push
  • Schema validation and rate limiting for feedback
  • Open Agent Feedback Protocol with TypeScript and Python SDKs
  • GitHub integration for draft PR creation
What makes it different
  • One-line integration with no proxy or request path modification
  • Costs tracked the instant each request completes, not at month-end
  • Unit economics and per-customer profitability visibility no other observability tool provides
  • Only AI agent failures on successful HTTP responses get detected and ranked
  • Automated pull request drafts with your approval required before shipping
  • Session replay captures failures even when agents don't report them
  • Pay only for coding-agent runs, not feedback submission
  • Open protocol and SDKs can be self-hosted at no cost
Community votes00
DR (Domain Rating by Ahrefs)Not checked yet no change since last check1 no change since last check
Trust Flow (Majestic)01
Citation Flow (Majestic)014
Referring domains (Majestic)14

5 details filled in for both companies.

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