Graft AI

Graft AI connects AI agents to existing business software with stable, governed tools built from real interfaces for legacy and internal systems.

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Overview

Graft AI is a tool layer for connecting AI agents to business software that is already in use. It turns real application interfaces into stable, governed tools so agents can operate across legacy systems without replacing them.

The product is built around a four-step flow: observe a workflow, compile a tool contract, verify the result against the live system, and connect agents through a single MCP tool. The site positions this approach for systems that are difficult to replace, including ERP, mainframes, desktop applications, web portals, virtual desktops, internal tools, and file-based workflows.

Graft emphasizes running in the customer environment, keeping data under customer control, and logging actions for auditability. It also presents the product as compatible with common agent frameworks such as LangChain, LlamaIndex, CrewAI, Microsoft AutoGen, and the OpenAI Agents SDK.

Core capabilities

Workflow observation

Graft watches a real workflow and maps screens, inputs, transitions, and side effects so it can understand how work actually moves through a system.

Tool contract generation

It generates a typed schema, adapter, policy boundaries, and conformance tests from the observed workflow, turning the interaction into a stable tool contract.

Independent verification

An independent witness checks the live application state, and the adapter cannot certify itself, which helps verify the real effect before exposure to agents.

Single tool layer for agents

Agents call one stable MCP tool instead of rediscovering the interface every time, which is meant to reduce drift from changing screens or states.

Policy-aware execution

The product supports approval rules, roles, boundaries, and least-privilege access, so actions can be governed before they reach the source system.

Audited and versioned operations

Each action is logged with context, and the site says generated tools ship with a conformance bundle that proves effects across supported application versions.

Practical use cases

Finance and operations workflows
Use Graft to let agents create invoices, update records, reconcile data, or generate reports inside finance and operations systems that already exist.
IT and support tasks
Use it to update systems, create tickets, or resolve requests in IT and support tools where the interface is stable enough to be mapped and governed.
Supply chain operations
Use it for inventory, purchase orders, shipments, and vendor records when work spans legacy systems and file-based processes.
Customer operations
Use it to resolve issues and update records across systems of record for customer operations teams that need traceable actions.
General internal workflow access
Use it to expose any internal tool, desktop application, web portal, or mainframe workflow to agents without replacing the underlying system.

Pros and Cons

Pros

Connects agents to existing software without requiring a source-system replacement project.
Uses typed contracts, policy boundaries, and verification steps rather than relying on a one-off automation script.
Supports a range of legacy and internal environments, including ERP, mainframes, desktop apps, web portals, and file-based workflows.
Keeps actions auditable and permission aware, which is important for governed business operations.
Can be used from several common agent frameworks and runtimes, according to the site.

Cons

The site does not publish full product specifications, integration lists, or deployment requirements, so readers still need more detail before evaluating fit.
Access appears to be private beta and waitlist-based, so the product may not be broadly available yet.
The pricing page does not show concrete pricing or plan details in the provided source.

FAQ

What does Graft AI do?

It is designed to connect AI agents to existing business software through stable tools generated from real interfaces. The site describes a flow where Graft observes a workflow, compiles a tool contract, verifies the source effect, and then exposes that workflow as a single MCP tool for agents to call.

What kinds of workflows can it connect?

The site shows examples for finance and operations, IT and support, supply chain, and customer operations. It also says Graft can be used for ERP, mainframes, desktop apps, web portals, custom internal systems, and files or exports.

How does Graft handle security and data control?

Graft says it runs in your environment and that data stays yours. It also states that actions are auditable, permission aware, and protected by least-privilege access and a complete audit trail.

Is Graft available to everyone yet?

The homepage presents Graft as designed for private beta and asks visitors to join the waitlist. It also says the team will be in touch when early access opens.

What agent stacks does it work with?

The site says Graft can be used from frameworks and agent runtimes such as LangChain, LlamaIndex, CrewAI, Microsoft AutoGen, and the OpenAI Agents SDK. It positions Graft as a tool layer that agents can call rather than a replacement for the source system.

Quick Facts

Category: AI agent tooling / workflow automation
Primary users: Teams using AI agents to operate existing business software
Deployment: Runs in the customer environment
Availability: Private beta; waitlist sign-up
Source domain: graft.axcelner.com
Supported agent stacks: LangChain, LlamaIndex, CrewAI, Microsoft AutoGen, OpenAI Agents SDK