GitMir vs ActionBox

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 ActionBox
Detail	GitMir	ActionBox
What it does	AI model of your product's business logic accessible to people and AI agents	Human approval infrastructure for AI agents and automation workflows
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	Developer: Free forever with 250 Actions/month, 3 Sources, 3 Watches, 7-day history. Pro: $10/month ($120/year, save 17%) with 1,000 Actions/month, unlimited Sources, 20 Watches, 30-day history, additional Actions at $8 per 1,000-pack. Team: $49.17/month ($590/year, save 17%) with 5,000 Actions/mont
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	Typed decisions (Boolean, choice, text, number, rating, structured forms) Heartbeat Watches for silent-work detection Action Controls for safe follow-up operations Multi-surface inboxes (web, mobile, Slack, CLI, MCP) Model Context Protocol (MCP) integration Signed receipts and durable decision history Mobile app for iOS (15+) with push alerts Slack approval integration (Beta) CLI with bounded long-poll waiting Integration guides for GitHub Actions, n8n, LangGraph, OpenAI Agents SDK
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	Durable decision records that survive client disconnections and restarts Reduces median approval time significantly in production environments Unified API across multiple approval surfaces without building custom dashboards Source-scoped identity for independent credential rotation across runners Built-in monitoring for stalled background work with heartbeat watches
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	5 no change since last check
Trust Flow (Majestic)	3	7
Citation Flow (Majestic)	28	24
Referring domains (Majestic)	50	42

5 details filled in for both companies.

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