New integration enables knowledge workers to securely access, manage, and work with governed organizational content through ChatGPT Enterprise
iManage, the company dedicated to Making Knowledge Work™, has announced a new integration with ChatGPT Enterprise that enables knowledge workers to securely access and work with governed iManage content directly within ChatGPT. The iManage plugin allows authorized users to search, review, organize, and update content while existing permissions, ethical walls, and audit trails remain in place.
The new integration gives organizations a direct way to bring trusted institutional knowledge into their AI workflows. Customers can enable the iManage plugin within ChatGPT Enterprise without manually configuring a separate connection. Users can then work with information they are already authorized to access, including prior agreements, matter documents, correspondence, and other organizational content.
Connecting Organizational Knowledge with AI
The plugin extends beyond information retrieval. Knowledge workers can search and review documents through ChatGPT Enterprise, organize content within iManage, and file documents into the appropriate matter or workspace. They can also save new or updated work back into iManage as a new version, while retaining the original document and its complete version history.
This creates a connected workflow in which professionals can move from finding information to working with it and returning the resulting work to the organization’s governed knowledge environment. Instead of treating documents as isolated sources, the integration allows users to work with information in the context of the broader organizational record.
At the center of this capability is the iManage Context Fabric™, which connects signals across an organization’s content and activity data. Through this connected context, models available in ChatGPT Enterprise can surface related work and prior matters, helping provide responses grounded in an organization’s institutional knowledge and previous work product.
Supporting Knowledge-Intensive Work
The practical value of the integration can be seen in legal workflows. A lawyer preparing a contract review can use ChatGPT Enterprise to locate the latest agreement, related correspondence, and relevant amendments stored in iManage. The lawyer can review the information within the same workflow and then save updated work back to the appropriate iManage workspace, keeping the resulting work within the governed record.
The development also reflects iManage’s broader open approach to enterprise AI. Rather than limiting customers to a single AI environment, iManage is building connections that allow organizations to bring governed knowledge into the AI tools they choose. Its broader platform strategy includes connectivity with multiple AI applications through the iManage MCP Server.
Governance Remains Central
As organizations adopt AI for knowledge-intensive work, maintaining control over sensitive information remains a key consideration. The ChatGPT Enterprise integration is designed around iManage’s existing governance framework, allowing users to access only the content they are authorized to see while preserving information barriers and auditability.
Neil Araujo, Chief Executive Officer of iManage, said the integration gives customers greater flexibility to use the AI tools that fit their organizations while maintaining governance around important knowledge. Jason Boehmig, GM Legal Industry at OpenAI, highlighted the potential for firms to bring their distinctive expertise, judgment, and ways of working into everyday AI-assisted legal work.
Advancing AI-Enabled Knowledge Work
The iManage and ChatGPT Enterprise integration represents a move toward more connected AI-assisted knowledge work. By bringing governed organizational content into ChatGPT while allowing work to flow back into iManage, the integration connects information discovery, document review, content organization, and work creation within an established knowledge environment.
For organizations managing large volumes of specialized information, the development offers a way to make existing knowledge more accessible through natural-language AI while retaining the permissions, governance structures, and records that support responsible enterprise work.
