From Storing Documents to Powering Agentic AI Work
At its ConnectLive conference, iManage introduced what it calls the next evolution of its document and knowledge management environment: an agentic AI platform designed to make institutional knowledge safely usable by intelligent agents. Rather than layering AI features onto a traditional document repository, iManage is repositioning the system itself as a governed engine that actively surfaces and brokers knowledge for AI. Executives frame this change as comparable in magnitude to the industry’s shift to cloud computing, highlighting a move from AI experimentation toward AI operationalisation in real-world workflows. With governance and security built natively into the platform, the redesign is intended to give organisations confidence that AI agents operate only over permission-aware, policy-compliant content. For firms already standardised on iManage for critical work product, this document management evolution signals a more fundamental rewiring of how knowledge is organised, exposed and controlled for autonomous operations.
Inside the Context Fabric: A Living Layer of Knowledge and Activity
The centrepiece of iManage’s overhaul is its Context Fabric, an architectural layer that treats documents, relationships and real-time activity as a continuously enriched, governed asset. Instead of viewing files as static objects in folders, the Context Fabric knowledge model understands how matters, clients, teams and prior work intersect. It reasons over that graph to give AI agents context-sensitive access to work product without breaching permissions. As people and agents perform tasks, their actions feed back into the fabric, refining its understanding of relevance and expertise. This turns institutional knowledge into a “living, governed foundation” for agentic work, where insights are surfaced in context rather than manually searched. By embedding governance rules directly into this layer, iManage aims to ensure that any knowledge management AI capability—whether summarisation, drafting or workflow automation—operates within tightly controlled boundaries aligned to organisational policies.
Governance-First Foundations for Enterprise AI at Scale
A central message from ConnectLive was that meaningful AI in knowledge-intensive organisations depends less on choosing a model and more on enterprise AI governance. iManage is responding with platform-level controls tailored to agentic AI. New capabilities include AI-specific policies governing how AI is applied across clients and matters, along with enhanced monitoring and reporting of AI agent activity. These features are designed to make every AI interaction traceable, auditable and aligned with confidentiality obligations. The expanded Model Context Protocol (MCP) Server provides a secure bridge between external AI tools and the governed iManage corpus, allowing firms to connect agents without bulk data exports. Combined with multi-region search and native OCR, these updates reinforce a stable, compliant substrate on which knowledge management AI can reliably operate. The objective is not just smarter search, but an AI-ready estate where risk, access and provenance are systematically controlled.
Platform Momentum Raises the Stakes for Knowledge Strategies
iManage’s platform repositioning matters because of its footprint across knowledge-intensive sectors. The company reports usage by a large share of top global law firms and sizeable portions of major corporate and professional services organisations, with its cloud deployment now covering most of its customer base. As these customers move from pilot projects to embedded AI workflows, iManage is pitching itself as the governed knowledge foundation underpinning those strategies. The platform’s integration into broader AI ecosystems, including formal placement within a leading model provider’s partner environment, provides a channel for AI agents to work directly over governed content. For CIOs, knowledge leaders and innovation heads, the shift reframes document management as a strategic AI platform decision. Adopting or extending iManage now involves choosing not just a DMS, but a core layer that will shape how agentic AI operates across the firm’s most sensitive knowledge assets.