From Document Store to Agentic AI Platform
At its ConnectLive 2026 user conference, iManage signalled a decisive shift in document management evolution, repositioning its core platform as a governed foundation for agentic AI. Rather than treating the document management system (DMS) as a passive repository, the company is recasting it as an active broker of knowledge for AI agents and workflows. CEO Neil Araujo framed the overhaul as comparable in scale to the move to cloud, underscoring that this is a platform-level re-architecture, not a feature refresh. With 83% of the Top Global 100 firms, 79% of the Am Law 100, and 40% of the Fortune 100 using iManage, this pivot has ecosystem-level implications for enterprise knowledge management. As organisations move from AI experimentation to AI operationalisation, iManage wants its platform to sit at the centre, making existing work product, matter history, and institutional expertise safely available to AI-powered DMS use cases.
Inside the New Context Fabric Technology
The headline innovation is iManage’s “context fabric” technology, an architectural layer designed to make organisational knowledge intelligible and actionable for AI. The fabric continuously understands and reasons over documents, emails, relationships, and real-time activity, turning static content into a living, governed knowledge graph for agentic work. Crucially, governance and security policies are native to this layer, not bolted on, so permission-aware access is enforced even as AI agents traverse matters, work product, and institutional knowledge. This is meant to answer a core challenge in deploying an agentic AI platform: how to give models rich context without breaking confidential walls. By embedding access controls, auditability, and policy management into the fabric itself, iManage aims to let firms safely “activate” their accumulated knowledge at scale, ensuring AI outputs are grounded in relevant, current, and properly governed content.
Model Context Protocol: Wiring AI Agents into Governed Knowledge
To operationalise the context fabric in real AI workflows, iManage has advanced its Model Context Protocol (MCP) Server, which acts as the secure bridge between AI tools and governed content. The MCP Server enables AI agents to query matter history, documents, and institutional context in a permission-bound, auditable manner, effectively wiring external models into the platform’s access rules. This is central to iManage’s “AI freedom of choice” strategy: firms can adopt models such as Anthropic’s Claude while ensuring that any retrieval from iManage happens under strict governance. Rather than exporting data into separate AI silos, the MCP Server lets the agentic AI platform run against live, governed knowledge in place. For legal and professional services teams, this promises AI-powered DMS capabilities that respect ethical walls, client confidentiality, and regulatory requirements by design.
New Features Built Around Contextual Knowledge
The platform repositioning is accompanied by multiple new and enhanced features that showcase how context-driven, AI-powered workflows might look in practice. Ask iManage now extends deeper into playbook analysis, helping legal teams apply institutional knowledge consistently during contract review while keeping work inside the governed environment. Insight+ Multi-Region Search offers a unified view across jurisdictions and data locations, allowing users to retrieve governed work product, emails, and matter-related context regardless of where they reside, all mediated by the context fabric. These capabilities share a common design principle: content is surfaced with rich, matter-aware context rather than as isolated files. iManage is also refreshing user experience and everyday workflows to align with this model, signalling that agentic AI is not a bolt-on assistant but a core part of how professionals will navigate and act on enterprise knowledge.
Strategic Impact: Platform Governance as the New AI Battleground
Beyond individual features, iManage’s overhaul reflects a broader strategic shift in enterprise knowledge management. As firms adopt AI agents and tools, the key question is no longer which model has the best benchmarks, but whether the underlying knowledge layer is secure, permission-aware, and connected enough to support agentic workflows. With 90 new customer logos added in 2026 and 78% of its customer base now on the cloud platform, iManage is betting that governance-first architecture will be the differentiator. By rewiring its DMS into an agentic AI platform centered on context fabric technology, the company is pushing the industry toward a future where AI systems operate directly over governed institutional knowledge. For CIOs and knowledge leaders, the message is clear: the battle for effective AI will be won or lost at the platform layer that controls how content, context, and policy come together.