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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

Screenshots View All

Screenshots View All

Integrations

Model Context Protocol (MCP)
Agent Development Kit (ADK)
Amazon Bedrock
AutoGen
Cisco AI Defense
CrewAI
LangChain
LangGraph
Mistral NeMo
OpenAI Agents SDK
Strands Agents

Integrations

Model Context Protocol (MCP)
Agent Development Kit (ADK)
Amazon Bedrock
AutoGen
Cisco AI Defense
CrewAI
LangChain
LangGraph
Mistral NeMo
OpenAI Agents SDK
Strands Agents

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

Product Features

Product Features

Alternatives

Alternatives

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