Graft AI

Product Introduction

1. Definition: Graft AI is a private-beta enterprise AI infrastructure platform designed to integrate AI agents with legacy, internal, desktop, and browser-only software. It functions as a middleware layer that observes, compiles, and enforces secure access to existing application workflows.
2. Core Value Proposition: It exists to solve the critical integration gap where AI agents cannot directly interact with the vast majority of business-critical software that lacks clean APIs. Graft AI's primary value is turning bounded, screen-based workflows into governed, stable, and auditable tools for AI agents, enabling automation in environments previously inaccessible to automation.

Main Features

1. Interface Intelligence & State Mapping: Graft AI uses computer vision and accessibility tree analysis to perceive and map user interface states, inputs, transitions, and side effects within target applications like ERPs, mainframes, and desktop apps. It builds a capability graph of the workflow, understanding the rules and effects of each action.
2. Stable Tool Contract Compilation: The platform compiles the observed workflow into a versioned, typed schema (akin to an API contract). This includes defining idempotency, error recovery paths, and data types, creating a stable interface (compatible with protocols like MCP - Model Context Protocol) that agents can call reliably, insulating them from underlying UI changes.
3. Governed Execution with Independent Verification: Graft enforces policy boundaries such as role-based approvals and data access controls before execution. Crucially, it requires independent source-system evidence (e.g., a database record, a generated invoice ID) to verify the action's outcome. The adapter cannot self-certify, ensuring audit integrity.

Problems Solved

1. Pain Point: The "API Desert" in enterprise software. Most business operations run on legacy systems, internal tools, and virtual desktop applications that have no API, making them invisible and unusable by modern AI agents and automation platforms.
2. Target Audience: Enterprise IT and Operations leaders, Head of Business Process Automation, CIOs/CTOs at companies reliant on legacy ERP (e.g., SAP, Oracle), mainframe systems, or custom internal web portals. Also, AI/ML engineers and agentic AI developers tasked with deploying assistants that need to execute actions in real business systems.
3. Use Cases: Automating invoice creation in a legacy accounting desktop app, processing purchase order entries in a green-screen terminal, updating customer service tickets in an old web portal, or reconciling inventory data across disparate internal tools—all through AI agent commands.

Unique Advantages

1. Differentiation: Unlike RPA (Robotic Process Automation) which mimics clicks at a fragile surface level, or API integration platforms that require APIs to exist, Graft AI focuses on creating a durable, abstracted tool layer specifically for AI agents. It prioritizes agentic stability, permissioning, and verification from the ground up, unlike screen-scraping tools.
2. Key Innovation: Its "observe-compile-verify" lifecycle. Graft doesn't just record macros; it intelligently maps workflows to generate a robust contract and mandates independent evidence for verification. Furthermore, it is designed to detect "UI drift" (when the underlying application changes) and can retest and repair the workflow mapping without breaking the agent's stable tool interface.

Frequently Asked Questions (FAQ)

1. What is Graft AI and how does it work with legacy software? Graft AI is an enterprise integration platform that allows AI agents to operate legacy software by visually mapping its user interface, compiling the workflow into a stable API-like tool, and governing its execution with permissions and mandatory outcome verification.
2. How does Graft AI ensure security and compliance for automated actions? Graft AI employs a least-privilege security model, evaluating each workflow for specific identity, network, and data boundaries. It enforces approval chains, roles, and rules native to the application, and provides full audit trails with context and independent source-system evidence for every agent action.
3. Can Graft AI handle changes in the underlying application's user interface? Yes, a core feature of Graft AI is its ability to detect UI drift—when buttons, fields, or screens change. It isolates the failed action, flags that a retest is required, and can repair the workflow mapping to maintain the stability of the agent's tool contract.
4. What types of systems and workflows is Graft AI designed for? Graft AI is specifically built for bounded workflows in ERP systems, mainframe terminals, desktop applications (like old accounting software), internal web portals, virtual desktop environments, and custom internal tools that lack modern APIs.
5. What is the "private-beta" model for Graft AI deployment? Graft AI evaluates suitability on a per-workflow basis. Deployment is not a blanket installation; the team assesses the specific target application, environment, control requirements, and available evidence for a single, bounded action before enabling it as a governed agent tool.