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What is OpenWeave?

OpenWeave functions as a governance framework for AI agents and autonomous systems, operating as a server-enforced state machine that dictates the actions and their timing for these agents. Users can design workflows that include various states, transitions, and authorized triggers; the backend rigorously enforces transitions using a strict 403 error, and crucial states necessitate human approval, thus ensuring that bots cannot proceed without human intervention. Additionally, the monitoring capability offers visibility into agent activities, preventing inappropriate actions from taking place before they can occur. Rather than having transitions hardcoded, agents acquire knowledge about acceptable transitions through the API, guaranteeing that each bot maintains a verifiable identity, with all changes recorded in an immutable audit trail. The system provides integration options via a REST API and a remote MCP server, making it an essential tool for AI-agent developers, AgentOps/MLOps, and platform teams. This robust framework not only fortifies security measures but also simplifies the oversight of AI workflows, ultimately leading to more reliable and efficient autonomous systems. Furthermore, by facilitating seamless collaboration among various stakeholders, OpenWeave enhances the overall development process within the AI landscape.

What is Graft?

Graft AI is a platform for helping AI agents safely use the legacy software that businesses already depend on. It turns real application interfaces into stable tools, allowing agents to execute workflows without requiring source-system replacement or new APIs. Graft is built for systems such as ERPs, mainframes, desktop apps, web portals, virtual desktops, internal applications, custom systems, and file-based workflows. The platform observes real workflows and maps screens, inputs, transitions, rules, side effects, and interface states. It then compiles those workflows into typed schemas, adapters, policy boundaries, recovery behavior, idempotency rules, and conformance tests. Agents can call the resulting stable MCP tools instead of rediscovering and navigating the interface from scratch each time. Graft verifies source-system effects through independent evidence, such as source records or generated IDs, so actions can be proven rather than assumed. Policy controls enforce approvals, roles, boundaries, least-privilege access, and permission-aware execution before agents make changes. Every action is logged with full context, giving teams a complete audit trail across workflows such as order creation, invoice processing, customer updates, ticket creation, reconciliation, reporting, and support operations. The platform runs in the customer’s environment, keeps data under customer control, and states that customer data does not train its models. By combining interface mapping, stable tool contracts, governed execution, source-effect verification, audit trails, and agent framework compatibility, Graft AI helps enterprises extend AI agents into the systems they cannot replace.

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Integrations Supported

Model Context Protocol (MCP)

Integrations Supported

Model Context Protocol (MCP)

API Availability

Has API

API Availability

Has API

Pricing Information

$29/month
Free Version
Free Trial Offered?

Pricing Information

Pricing not provided
Free Version
Free Trial Offered?

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Seven Olives

Date Founded

2013

Company Location

United States

Company Website

openweave.dev

Company Facts

Organization Name

Graft AI

Company Website

graft.axcelner.com

Categories and Features

Categories and Features

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