From Document Store to Agentic AI Platform
At ConnectLive, iManage signalled a decisive shift in document management evolution: from passive storage to an active agentic AI platform. Instead of treating the DMS as a repository, the company is re-architecting it as a governed broker of institutional knowledge for AI tools and agents. CEO Neil Araujo framed the change as comparable in scale to the industry’s move to cloud, underlining that this is a platform repositioning, not a routine feature drop. With iManage already embedded in a high proportion of large law firms and major enterprises, its strategic pivot effectively nudges the broader enterprise knowledge management stack towards AI-first architectures. The emphasis is clear: organisations are moving from AI experimentation to operationalising governed AI workflows, and iManage wants to be the foundation that connects models, agents, and work product without sacrificing compliance, security, or user trust.
Inside the ‘Context Fabric’ Architecture
The centrepiece of iManage’s overhaul is its Context Fabric technology, an inference layer that sits above governed firm data. Rather than merely indexing documents, the fabric is designed to understand and reason over content, relationships, matter context, and real-time activity. It continuously learns from what people and AI agents are doing, turning static documents into a living, permission-aware knowledge graph. For enterprise knowledge management, this means AI agents can draw on a richer, more contextual view of briefs, contracts, emails, and prior work product without breaching ethical walls or client restrictions. Because governance and security policies are native to the platform, access rules travel with the data wherever it is invoked. In practice, the Context Fabric aims to give firms the benefits of deeply contextual AI assistance while maintaining rigorous controls over who can see what, and under which circumstances.
Governed AI Workflows: Controls, Monitoring and MCP Server
To make AI genuinely usable in sensitive environments, iManage is pairing automation with fine-grained governance. New AI-specific controls let organisations define how AI is applied across clients and matters, reflecting differing confidentiality requirements and risk appetites. Expanded monitoring and reporting of AI agent activity provide a clear audit trail, helping firms demonstrate responsible use and investigate anomalies. A key technical pillar is the iManage Model Context Protocol (MCP) Server, which offers a secure way for AI tools and agents to connect to governed knowledge without bulk data exports. This includes formal placement in Anthropic’s partner ecosystem and Claude store, giving Claude controlled, permission-aware access to the iManage corpus. Together, these capabilities are designed to underpin governed AI workflows at scale, ensuring that as firms automate drafting, research, and review, they do so under well-defined, enforceable policies.
User Experience, Cloud Scale and the Road to Agentic Work
The platform evolution is also visible in day-to-day workflows. iManage is rolling out a refreshed user experience, interface updates, multi-region search, and native OCR, all aimed at making knowledge more discoverable and actionable where professionals already work. These changes sit on top of a cloud footprint that now covers 78% of the customer base, with strong adoption among top law firms and large enterprises, positioning iManage as a de facto backbone for AI in professional services. As organisations move further into the agentic AI era, the company’s strategy is to let human and machine agents collaborate over a shared, governed context layer. The long-term vision is a knowledge work environment where documents, emails, and prior matters are not just filed but continuously activated—surfaced, connected, and orchestrated by AI in ways that remain secure, explainable, and compliant by design.