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Description
Agent Control represents a groundbreaking open-source framework designed to manage the behavior of AI agents on a large scale, setting a new benchmark for governance in this domain. It addresses the issue of disjointed and hardcoded checks by providing teams with a unified governance layer that enforces regulations at each step, all managed from a single control interface that can be updated dynamically without altering the agent's underlying code. Developers can easily designate any function as governable by applying the control() decorator, thereby transforming key decision points within an agent into independently regulated control points, each equipped with its own governance policies. When a decorated function runs, Agent Control assesses the input or output against the prevailing policy and generates a response that could be to deny, steer, warn, log, or allow the action. If a denial occurs, the SDK triggers a ControlViolationError, preventing any unsafe actions from being executed. This separation of policies from the actual code empowers developers to strategically position control hooks, while policy teams determine the enforcement specifics of those hooks, ensuring a collaborative approach to governance. The flexibility and robustness of Agent Control make it an invaluable tool for organizations looking to standardize AI agent governance effectively.
Description
Graft AI is an enterprise platform that helps AI agents work inside legacy software by turning existing interfaces into reliable tools. The platform is designed for companies that rely on systems without modern APIs, including ERPs, mainframes, desktop applications, web portals, virtual desktops, internal tools, and file-based workflows. Graft observes real workflows and maps screens, inputs, transitions, rules, effects, and application states. It then compiles those workflows into stable typed contracts, adapters, policy boundaries, and conformance tests that agents can call through MCP-compatible tools. The platform verifies real source-system effects using independent evidence so the adapter cannot simply certify itself. Graft also enforces approvals, roles, permissions, boundaries, and least-privilege access so write actions stay governed. Every agent action is logged with context, making workflows auditable, traceable, and easier to review. The platform runs in the customer’s environment and states that customer data does not train its models. By combining interface intelligence, governed execution, verification, stable contracts, and auditability, Graft AI gives enterprises a practical bridge between existing software and modern AI agents.
API Access
Has API
API Access
Has API
Integrations
Model Context Protocol (MCP)
Agent Development Kit (ADK)
Amazon Bedrock
AutoGen
Cisco AI Defense
CrewAI
LangChain
LangGraph
Mistral NeMo
OpenAI Agents SDK
Integrations
Model Context Protocol (MCP)
Agent Development Kit (ADK)
Amazon Bedrock
AutoGen
Cisco AI Defense
CrewAI
LangChain
LangGraph
Mistral NeMo
OpenAI Agents SDK
Pricing Details
Free
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Agent Control
Country
United States
Website
agentcontrol.dev/
Vendor Details
Company Name
Graft AI
Website
graft.axcelner.com