From Document Store to Agentic AI Platform
At its ConnectLive conference, iManage unveiled what it calls the next evolution of its document and knowledge management platform: a shift from passive storage to an active, governed foundation for AI. Rather than simply adding another AI assistant, the company is repositioning its document management system as an agentic AI platform that brokers knowledge, context and permissions to a growing ecosystem of tools and autonomous agents. CEO Neil Araujo has compared the scale of this transition to the industry’s move to cloud computing, underscoring that this is a re-architecture, not a feature pack. With 83% of the Top Global 100 firms, 79% of the Am Law 100 and 40% of the Fortune 100 already on iManage, this document management evolution effectively nudges a large slice of the professional services market toward AI-ready, AI-governed data access at the platform layer.
Inside the Context Fabric Architecture
The centerpiece of the overhaul is iManage’s new context fabric architecture, an inference layer that sits above governed firm data. Instead of treating documents as isolated files, the fabric continuously understands and reasons over content, relationships and real-time activity across the organization. It is enriched by what people and AI agents are doing right now, turning accumulated work product into a living, contextual knowledge base. This makes enterprise knowledge management more dynamic: matter context, precedents and institutional expertise become machine-readable signals that AI systems can safely tap into. Crucially, governance and security are native to this architecture, not bolted on. Policies, permissions and ethical boundaries are enforced within the fabric itself, giving organizations confidence that any AI agent consuming this context does so with permission-aware, AI-governed data access baked into its operating environment.
New Controls for AI-Governed Data Access
To translate the context fabric into operational safeguards, iManage is rolling out new AI-specific controls across its platform. Firms can define how AI is applied at the level of clients and matters, tailoring where agents are allowed to act and what content they can see. Enhanced monitoring and reporting tools track AI agent activity in detail, supporting both auditability and continuous improvement of autonomous workflows. The expansion of the iManage Model Context Protocol (MCP) Server gives organizations a secure mediation layer to connect external AI tools and agents to governed knowledge without bulk data exports. There is also native support for capabilities such as multi-region search and OCR, making more content discoverable under the same governance umbrella. Together, these changes align document management evolution with the practical realities of AI-governed data access: selective exposure, explainability and robust oversight.
Operationalizing Enterprise Knowledge Management for Agents
iManage’s timing reflects a broader market shift from AI experimentation to AI operationalization. As firms embed AI into daily workflows, the central question is no longer which model to choose, but how to ensure that the knowledge those systems depend on is secure, contextual and ready for scale. The revamped platform reframes enterprise knowledge management as the operational substrate for autonomous agents: a governed environment where playbooks, matter files and institutional learnings can be orchestrated rather than merely archived. Features such as playbook analysis in Ask iManage illustrate how domain-specific expertise can be standardized and then surfaced consistently by AI. With 90 new customer logos added and 78% of its customers now on the cloud platform, iManage is leveraging its installed base to set a new norm: AI agents working against a deeply governed, context-rich layer instead of ad-hoc document repositories.
Strategic Implications for AI-Ready Firms
For CIOs and knowledge leaders, the ConnectLive announcements mark a strategic inflection point. When a dominant vendor chooses to rewire its core platform around agentic AI workflows, it effectively redraws the technology roadmap for knowledge-intensive organizations. The context fabric architecture positions iManage as the central broker between institutional knowledge and a proliferating landscape of AI tools, including partners such as Anthropic’s Claude, which can now access governed content without bulk exports. This consolidates governance at the platform layer, simplifying risk management while enabling more ambitious AI use cases. The bigger implication is cultural as much as technical: firms are being nudged to treat knowledge as an active, continuously enriched asset rather than a static archive. In that sense, iManage’s overhaul is less about a new interface and more about redefining how organizations architect work for an agentic future.