What Context Fabric Is and Why It Matters
iManage’s context fabric is an architectural layer that turns an organization’s documents, knowledge, and real-time activity into a governed foundation that document management AI and enterprise AI agents can understand, reason over, and act on in context. Introduced as the centerpiece of a broad platform overhaul at ConnectLive 2026, context fabric marks a shift from document management as passive storage to an active intelligence layer for knowledge work. iManage positions this change as comparable in scale to its earlier move to cloud, arguing that the value of AI depends less on model choice and more on how institutional knowledge is structured, connected, and secured. By embedding governance, permissions, and ethical-wall awareness into the fabric itself, the platform aims to give organizations a single, policy-aware surface through which AI tools can work safely across matters, work product, and institutional expertise.
From DMS to AI Context Layer for Enterprise AI Agents
At ConnectLive, iManage framed context fabric as the next evolution of its document and knowledge management system: from a repository that stores documents to a context fabric platform that actively surfaces, governs, and brokers knowledge for AI. The fabric models relationships between content, people, and real-time activity, so enterprise AI agents can see not only a document’s text, but how it connects to a matter, client, or prior work product. According to iManage, “the fabric understands and reasons over content, relationships, and real-time activity across the organization and is continuously enriched by what people and agents are doing right now.” This means AI workflows can rely on permission-aware, up-to-date context instead of brittle, one-off exports. The platform’s Model Context Protocol (MCP) Server extends this further by letting AI systems call into governed knowledge directly, aligning retrieval with security policies rather than bypassing them.
Governance, Security, and the New AI Control Plane
A central design choice in iManage’s platform evolution is to embed governance and security into the context fabric, not bolt them on later. The company is adding AI-specific controls that define how document management AI and other tools can access knowledge across clients and matters, with granular restrictions at client, matter, and even agent levels. Conference sessions highlighted ethical-wall-aware agents, monitoring of agent activity in Threat Manager, and policy-based controls in Security Policy Manager, all pointing to the DMS becoming a governance plane for AI. LawNext reports that iManage now serves 83% of the top Global 100 firms and 79% of the Am Law 100, so where this governance plane sits is strategic: if the document system is the broker for AI access, it can become the de facto control layer that other orchestration platforms and AI tools must respect.
Integrating Claude and Structuring Knowledge for AI-Native Workflows
The context fabric platform is also about how enterprise data must be structured so AI agents can support knowledge-intensive work. iManage is reorganizing its user experience around making knowledge more accessible to people and AI, strengthening governance, and reducing friction. Its MCP Server, available for the Insight+ knowledge product, lets large language models search governed work product and institutional knowledge with permission awareness. Integration with Anthropic’s Claude gives firms a governed path to apply a leading AI assistant to their iManage knowledge without bulk exports or custom builds. The system treats documents and activity as a living knowledge graph that updates as people and agents work. As iManage’s CEO Neil Araujo puts it, “iManage is helping organizations move from systems that simply store knowledge to a secure, governed foundation that actively surfaces it, connects it, and makes it usable for AI – contextually, responsibly, and at scale.”
Implications for the Knowledge Management Evolution
Context fabric is arriving amid a broader shift from AI experimentation to AI operationalization in knowledge management evolution. Legal IT Insider notes that several large vendors are racing to “own the governed surface through which firms operationalise AI,” and iManage’s move is part of that structural change. With 78% of its global customer base already on cloud and 90 new customer logos added in 2026, iManage is betting that the control point for AI will be the fabric that understands both content and permissions. For firms, the strategic question is where to place the governance layer: within the document management AI platform, an AI orchestration tool, or elsewhere in the stack. By recasting its DMS as a context fabric platform, iManage argues that the system closest to documents and knowledge is best placed to become the intelligence and policy layer that enterprise AI agents rely on for secure, context-aware work.