Visual Flow Builder
Build AI agents with drag-and-drop interface. Perfect for non-technical builders and visual thinkers.
GraphChainOrchestration Layer for Transactional AI
Redefining commerce for the AoA — the Age of Agents
Skip to content
Developer Framework
Programmatic control with TypeScript decorators and type-safe APIs. Full control for developers.
Type-Safe Port System
Rich port types including primitives, arrays, objects, streams, and enums with runtime validation via Zod.
Robust Execution Engine
Backend execution engine supports concurrent execution with real-time event subscriptions and debugging.
Real-Time Synchronization
Integrated with tRPC and Effector for end-to-end type safety. Real-time updates via WebSockets.
Docker & Cloud Ready
Easily build, deploy, and scale using Docker and docker-compose. Containerized deployment simplified.
Decorator-Based API
Define nodes with intuitive decorators for inputs, outputs, and configurations. Rapid development.
Distributed Execution
Horizontally scalable with DBOS durable workflows and PostgreSQL. Automatic recovery guaranteed.
Comprehensive Documentation
Full API documentation, architecture guides, and examples for building sophisticated workflows.
What is GraphChain?
GraphChain is an orchestration and settlement infrastructure purpose-built for Agentic Payments and AI-driven commerce.
GraphChain spans the core functional layers of the Agentic AI Stack —providing the runtime, orchestration, and enrichment foundation on which agentic systems operate.
It bridges AI logic, protocol interoperability, workflow, orchestration, and tool integration into one cohesive execution layer.
GraphChain operationalizes agent execution, interoperability, orchestration, and enrichment—powering the middle stack of agentic AI.
GraphChain utilizes ChainGraph that serves as a deterministic orchestration framework.
Why ChainGraph?
ChainGraph is a source-available orchestration framework for building AI agents and automation systems with complex, verifiable logic. It's engineered for mission-critical, high-load environments, delivering fault-tolerant, deterministic flows and enterprise-grade reliability.
ChainGraph lets teams visually design, verify, and deploy multi-agent pipelines that combine multiple AI providers within a single, resilient system.
What Makes ChainGraph Different?
ChainGraph eliminates AI unpredictability through deterministic orchestration.
- TEE-powered private agent runtime (SEV-SNP/TDX + H100 CC):
- Runs inside secure Trusted Execution Environments
- Data processed but never stored or exposed
- Reproducible builds & cryptographic attestation
- Granular access controls ensure agents only access what they need
- Perfect for fintech: precision and privacy that contemporary AI systems cannot satisfy
Additional Features
Source-Available & Self-Hosted Control
- Full source code transparency under Business Source License for audit and compliance
- Complete on-premise deployment with no external dependencies or cloud requirements
- Full control over data sovereignty, infrastructure, and security policies
Enterprise Security Infrastructure
- Integrated Vault system (separate repository, bundled with ChainGraph) for centralized secrets management
- ECDH + AES-GCM-256 encryption for all sensitive data with perfect forward secrecy
- Context-isolated secret handling ensures credentials are always encrypted during execution and never leak to logs or any other execution artifacts. The encryption keys are unique per execution ensuring perfect forward secrecy and complete isolation between workflow runs - even if one execution context is compromised, all other executions remain secure with no cross-contamination of sensitive data.
- Zero-trust security model with role-based access control and audit trails
Flexible LLM Integration Architecture
- LLM-agnostic framework supporting any language model provider or API
- On-premise LLM support for complete air-gapped deployments
- Hybrid deployment flexibility: sensitive data processing on-premise while leveraging cloud LLMs for non-sensitive operations
- Multi-provider optimization within single workflows for cost and performance efficiency
Data Privacy by Design
- Flow-level sensitive data handling preventing exposure of PII, emails, or unique identifiers to LLM contexts
- Data isolation architecture where sensitive information is processed at the ChainGraph layer without reaching AI models
- Configurable data flow policies enabling selective data exposure based on sensitivity classification
- Compliance-ready workflows supporting GDPR, HIPAA, and other regulatory requirements
Enterprise-Grade MCP Server Integration & Tool Orchestration
- Comprehensive Model Context Protocol integration transforming any MCP-compliant server into native workflow components
- Seamless external integration with AI tools, resources, and services through unified, type-safe interface
- Zero-configuration setup enabling immediate connectivity to MCP ecosystem without custom development
- Enterprise-ready architecture supporting production-scale MCP server orchestration and management
Automatic Server-to-Node Transformation
- URL-based server wrapping automatically converting MCP servers into native workflow nodes by simply providing server URL
- Elimination of integration overhead removing need for custom integration code or manual API mapping
- Dynamic capability discovery automatically detecting available tools, prompts, and resources from connected servers
- Type-safe node generation creating corresponding interfaces with full schema validation and type safety
- Continuous synchronization with server capabilities, automatically updating node configurations when servers modify tools
- Zero-maintenance workflows ensuring flows remain current without manual intervention or updates
Intuitive Graph Construction & Real-Time Collaboration
- XYFlow-powered visual editor providing sophisticated workflow design capabilities through modern web-based interface
- Drag-and-drop node placement enabling intuitive graph construction without technical complexity
- Visual edge connections allowing users to create data flow relationships through simple drawing interactions
- Universal accessibility making complex workflow design approachable for both technical and non-technical users