RailCall local runtime: free. RailHub Team: $5 per seat per month. Cloud agents: $5 per trained agent per month. Advanced thinking (overflow): metered against a budget you set, with 500 flows per month included. Storage on hub: $0.25 per GB-month with 5 GB free.
Not given
Key features
Studio visual workflow builder with 1,000+ nodes
CLI and terminal-first interface
Ed25519-signed tamper-evident receipts
Human approval airlock for all actions
Autonomous agents that run 24/7
Capacity routing across organization machines
MCP integration with 33 tools
Multi-level human approval workflows
Offline receipt verification
Company-wide stop button
Context Graph of Work - continuously updated model of how work gets done across enterprises
Blueprint for AI roadmap planning with defensible ROI recommendations
Process Intelligence to identify bottlenecks and prioritize automation
Engineering Intelligence for unified view of developer work
Work-aware agents grounded in real operational context
Zero-integration capture across legacy and modern systems
In-environment processing with data staying in customer perimeter
Agentic Operating Procedures for governed agent execution
Audit logs and compliance tracking for every agent decision
Built on 25B+ events from 500+ observed processes
What makes it different
Entire local runtime free with MIT license, no login required
Cryptographically signed receipts verifiable offline
80% reduction in AI costs compared to top models
No execution counters or machine count limits
Observes actual work at scale across enterprise systems rather than relying on assumptions or documentation
Delivers AI agents that work in production at scale, not just pilots
Provides measurable ROI and audit trails for AI spending and decisions
Privacy-first architecture keeps sensitive data within customer environments
RailCall
Skan AI