From Document Repository to Agentic AI Platform
At ConnectLive 2026, iManage introduced the next evolution of its platform, positioning it as a secure, governed backbone for agentic AI rather than a traditional document management system. Central to this shift is a “context fabric” that understands and reasons over content, relationships, and real-time activity across the organisation. Instead of simply storing files, the platform continuously enriches institutional knowledge with what people and AI agents are doing right now. That living knowledge base is designed to power agentic workflows while keeping security and governance controls native to the architecture, not bolted on. As enterprises move from AI experimentation to operationalisation, iManage’s strategy is to provide an AI-native knowledge infrastructure where permission-aware data, context, and expertise are ready to be safely activated at scale across legal, financial, and other knowledge-intensive sectors.
Making Enterprise Knowledge AI-Ready and Contextual
To unlock enterprise knowledge for AI use, iManage is focusing on making information both discoverable and context-rich. Its Model Context Protocol (MCP) Server allows AI agents and large language models to search and surface permission-aware context directly from governed content in iManage. This means AI can draw on work product, matter histories, precedents, litigation and deal insights without bypassing existing security and access controls. Insight+ Multi-Region Search unifies discovery across jurisdictions, giving professionals and AI tools a coherent view of documents, emails, and matter-related context regardless of where data is stored. Native OCR further ensures that scanned documents and image-based PDFs become searchable and legible to AI, preventing years of archived material from remaining invisible to digital assistants such as Ask iManage. Together, these capabilities transform passive archives into an AI-ready, contextual knowledge layer.
Embedding Governance and Security into Agentic AI
A key challenge in deploying agentic AI at enterprise scale is maintaining rigorous governance over what agents can see and do. iManage addresses this by embedding document governance AI capabilities directly into its platform. Security Policy Manager, which already enforces ethical walls and permissions for human users, is evolving toward more granular client- and matter-level controls specific to AI usage. Threat Manager now surfaces AI agent activity within user activity reporting, giving security teams visibility into what agents are accessing, moving, and modifying. On the records side, cloud-native Disposition Manager and improved Records Manager tooling support lifecycle controls, reporting, and exception handling within the same secure AI infrastructure. Rather than treating AI as an external add-on, iManage is building governance, monitoring, and compliance into the core fabric that both humans and agents rely on.
Expanding an Open, Governed AI Ecosystem
iManage’s platform evolution also reflects a broader strategy to support multiple AI tools through a secure, governed hub. By making its MCP Server available for Insight+ and integrating into Anthropic’s partner ecosystem and Claude store, the company offers a controlled way for external models like Claude to work with enterprise knowledge. Through MCP, Claude can access governed iManage content – including matter history, documents, and institutional context – in a permission-bound and auditable manner, without bulk exports or fragile custom integrations. This approach positions iManage as a neutral, trusted knowledge foundation for organisations adopting diverse AI applications and agents. As collaboration patterns evolve, features like Collaboration Links extend that governed environment outward, enabling secure external sharing and co-authoring while keeping work product within the same compliant, AI-ready knowledge infrastructure.