Build, deploy, and scale autonomous AI agents with expert human oversight
Open-source AI infrastructure you self-host on your own hardware with your own keys
Stage
Established
Not given
Founded
2021
Not given
Based in
US
Not given
Pricing model
Contact for pricing
Open source
Pricing
Fixed monthly subscription with custom pricing based on user licenses and needs. No hidden fees, annual subscriptions with monthly payments. 2-day expert-led discovery workshop costs are 100% credited toward subscription pricing.
Self-host: $0 (open source, MIT-licensed). Service and Enterprise tiers available on contact for integration and custom development work.
Key features
Enterprise Context Engine™ to structure organizational knowledge for AI decisions
Agentic AI agents that scan, test and act on data on schedule or on demand
No data migration required; connects to existing systems
700+ prebuilt data connectors and integrations
Deployment on AWS, Azure, or GCP with flexible hosting options
Enterprise compliance: SOC 2 Type II, HIPAA, GDPR, ISO 42001
Model-agnostic platform working with existing enterprise infrastructure
Compounding Intelligence where each solution builds on the last
Transparent and auditable workflows with full lineage tracking
Expert-led 2-day discovery workshops with PhD-level data scientists
Provider routing with LiteLLM
What makes it different
Hybrid Approach™ pairing agentic AI with human expert oversight for accountability
Production-ready AI in weeks, not months
70% faster from start to go-live year over year
Outcome-based guarantees and PoC engagements for risk-free transformation
Full platform access for unlimited solution creation and deployment
Complete ownership: your keys, hardware, data and audit logs stay under your control
No vendor lock-in: compose individual modules with your existing stack rather than replacing it
Full transparency: MIT-licensed, publicly developed on GitHub with open issues, PRs and commit history
Every request traceable: one ID threads through all services with full audit logging
RapidCanvas
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