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GitMir vs Exabase

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

GitMir compared with Exabase
DetailGitMir logo GitMirExabase logo Exabase
What it doesAI model of your product's business logic accessible to people and AI agents Context infrastructure for AI agents
StageNot given Startup
FoundedNot given Not given
Based inGB GB
Pricing modelFreemium Freemium
PricingFree: 10,000 starting credits plus 1,000 per month. Engineering: $29 per active developer per month with 30,000 pooled credits each month. GitMir Vibe: $9 per person per month. Cloud Compute: $99 per project per month. MeetAI: $49 per project per month. GoBots: $99 per venture per month. Market: $49 Not given
Key features
  • Builds features, rules and customer paths and keeps them current with every push
  • Shows what each commit changed in the business logic, not only in the code
  • Provides change impact analysis before merge showing what could break
  • Checks PRDs and specifications against the product
  • Delivers understanding to AI agents over MCP
  • Runs locally on your machine with GMM Local
  • Finds risky patterns and problems in the product
  • Enterprise deployment inside your security boundary
  • Integrates with Claude Code, Cursor, Codex and VS Code
  • MCP access for agents with 1-10 credits per answer
  • Memory system with self-managing advanced memory
  • Isolated per-tenant instances with version rollback
  • Portable context server with files, notes and links
  • Sub-document multi-modal hybrid search
  • Structured data extraction from PDFs, websites and images
  • Autonomous agents for knowledge base automation
  • 99.9% uptime SLA
  • AES-256 encryption at rest and SSL in transit
  • TypeScript SDK and REST API
  • Model-agnostic and framework-agnostic
What makes it different
  • Nearly 3× fewer errors on Benchmark 001 compared to alternatives
  • 8.4K tokens per question instead of 27.4K for competitors
  • Results published and measurable; method is proprietary
  • Reduces AI cost per completed agent action from $0.35 to $0.08
  • Cut token spend by up to 81% through persistent agent memory instead of full context window stuffing
  • State-of-the-art on two leading AI memory benchmarks
  • Full-stack data layer eliminating need for multiple services
  • Production-tested at scale powering Fabric platform
  • Self-improving memory that tracks relationships and resolves contradictions
Free planNot given Not given
Open sourceNot given Not given
PlatformsNot given Not given
Public APINot given Not given
Community votes00
DR (Domain Rating by Ahrefs)27 no change since last check29 no change since last check
Trust Flow (Majestic)311
Citation Flow (Majestic)2832
Referring domains (Majestic)50122

5 details filled in for both companies.

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