AEGIS Initiative vs GitMir

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

AEGIS Initiative compared with GitMir
Detail	AEGIS Initiative	GitMir
What it does	Governance-first security framework for autonomous AI systems	AI model of your product's business logic accessible to people and AI agents
Stage	Startup	Not given
Founded	2026	Not given
Based in	Not given	GB
Pricing model	Open source	Freemium
Pricing	Not given	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
Key features	Constitutional governance charter with 11 articles defining AI autonomy boundaries ATX-1 threat matrix taxonomy for agentic AI systems Python runtime implementation of AGP-1 for policy evaluation TypeScript and Python SDKs for governance integration Federation protocol for cross-domain AI governance Versioned, citable, openly licensed specifications Standards engagement with NIST, IEEE, and NCCoE	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
What makes it different	Governance-first approach where policy is evaluated before action, not after Deterministic enforcement with transparent audit trails and non-bypassable human oversight Non-partisan engagement with policymakers regardless of jurisdiction or political orientation Human-directed with transparent AI collaboration in research and development Deny by default principle: anything not explicitly authorized is prohibited	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
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)	28 +14 (up) since last check	27 no change since last check
Trust Flow (Majestic)	0	3
Citation Flow (Majestic)	22	28
Referring domains (Majestic)	6	50

4 details filled in for both companies.

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