GitMir vs Port of Context

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 Port of Context
Detail	GitMir	Port of Context
What it does	AI model of your product's business logic accessible to people and AI agents	Context layer platform for regulated industries
Stage	Not given	Not given
Founded	Not given	Not given
Based in	GB	Not given
Pricing model	Freemium	Freemium
Pricing	Free: 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	Free: $0, includes up to 5 members, 100 context nodes, and 100 MB of indexed content. Team: $25 per seat per month (or $200 per seat billed annually), includes up to 25 members, 1,000 context nodes, and 1 GB of indexed content. Enterprise: custom pricing, includes Forward Deployed Engineers, Hybrid
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	Model-agnostic: runs on Claude, GPT, Gemini, or open-weight models Full observability: trace every tool call, retrieval, and reasoning step Isolated execution: tool calls run in isolated environments by default Code mode: reduces token usage to one-third of traditional approaches Self-hosted on your infrastructure: cloud, on-prem, or air-gapped MCP server integration: works with existing MCP servers unchanged Open source under MIT license Automatic model failover and switching
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	Isolated by default with no direct system access Reduces token usage to approximately one-third Runs end-to-end air-gapped with no external network calls Full transparency through open agent-observability spec (AVP) No vendor lock-in: switch models without rewriting agents
Free plan	Not given	Not given
Open source	Not given	Not given
Platforms	Not given	Not given
Public API	Not given	Not given
Community votes	0	0
DR (Domain Rating by Ahrefs)	27 no change since last check	38 no change since last check
Trust Flow (Majestic)	3	14
Citation Flow (Majestic)	28	28
Referring domains (Majestic)	50	102

5 details filled in for both companies.

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