Inside iManage’s Next-Generation Platform: Unlocking Enterprise Knowledge and AI-Driven Legal Workflows

Following a highly successful early-access program involving prominent global law firms, corporate legal departments, and leading financial institutions, iManage officially reached General Availability (GA) for its next-generation platform in October. The release marks a watershed moment for knowledge management and legal technology, shifting the paradigm from static document storage to active, context-aware artificial intelligence.

To explore the depths of this new offering, Legal IT Insider recently sat down with two of the platform’s key architects: Jan Van Hoecke, Vice President of Product Management and AI Services, and Emma Furnivall, Senior Technical Presales Solution Engineer at iManage. In an in-depth product demonstration and interview, Van Hoecke and Furnivall walked through the platform’s core capabilities, addressing how it aims to transform document review, harness institutional knowledge, and navigate the complex governance demands of an increasingly "agentic" software environment.

Main Facts: What is the iManage Next-Generation Platform?

At its core, the newly released iManage platform is designed to transcend traditional document management systems (DMS) by introducing a proprietary "context fabric." This foundational layer does not merely store files; it actively understands, reasons over, and connects content, human relationships, and real-time activity across an entire organization.

Key highlights of the GA release include:

• Context Fabric Architecture: An advanced structural framework that synthesizes data, interactions, and organizational workflows to power more accurate AI reasoning.
• Seamless Migration-Free Transition: Cloud customers can toggle directly between their familiar iManage Work environment and the new platform without undergoing costly, time-consuming data migration projects.
• Autonomous AI Agents: Specialized agents capable of executing complex natural language searches, leveraging core platform tools independently, and processing multi-step tasks.
• Playbook Integration and Tabular Review: Tools that allow organizations to enforce approved corporate standards automatically, structuring outputs into side-by-side comparison tables for rapid review.
• Granular Administration Control: Built-in safeguards that provide IT and compliance teams with strict governance over user access and feature activation.

Chronology: The Journey to General Availability

The path to the October General Availability release was carefully plotted through iterative development, extensive testing, and direct collaboration with industry stakeholders.

Phase 1: Conceptualization and the Realization of Knowledge Value

The genesis of the next-generation platform lay in a fundamental industry observation. While law firms and legal departments displayed immense appetite for generative AI tools, iManage leadership recognized a critical nuance: off-the-shelf AI models alone do not provide a competitive advantage.

• The Insight: A firm’s true differentiator is its proprietary knowledge, institutional memory, and historical data securely captured within its existing systems.
• The Mission: Reimagine the architecture of the enterprise platform to unlock this siloed information safely and efficiently.

Phase 2: The Early Access Program (EAP)

Before opening the platform to the wider market, iManage deployed an extensive early-access initiative. Participating organizations—comprising a cross-section of top-tier law firms, sophisticated corporate legal teams, and major financial institutions—put the platform through rigorous real-world stress tests. This feedback loop allowed the product team to refine user interfaces, enhance agent reliability, and tighten security parameters ahead of the commercial launch.

Phase 3: General Availability and the October Rollout

In October, the platform officially transitioned to GA, immediately becoming accessible to iManage’s vast ecosystem of cloud-based clients. Rather than forcing a disruptive cutover, the rollout was engineered to integrate smoothly with existing deployments, allowing firms to adopt advanced AI capabilities at their own operational pace.

Supporting Data and Technical Architecture

To understand how iManage’s next-generation platform operates under the hood, it is essential to examine its underlying technical framework—particularly how it handles imperfect enterprise data, accuracy, and search methodologies.

The Context Fabric Explained

Traditional enterprise search relies heavily on keyword matching and rigid metadata tagging. However, legal and financial data is notoriously imperfect; metadata is often missing, inconsistent, or outdated. The context fabric solves this by weaving together three critical dimensions:

1. Content: The raw text and documents housed within the ecosystem.
2. Relationships: The connections between authors, reviewers, matters, clients, and external counsel.
3. Real-time Activity: How documents are accessed, edited, shared, and referenced across the organization day-to-day.

By synthesizing these elements, the platform can interpret intent rather than relying solely on exact keyword queries.

Natural Language Search and AI Agents in Action

During the product demonstration, Emma Furnivall showcased a Master Services Agreement (MSA) deviation review—a common and time-consuming bottleneck in legal operations.

Instead of manually filtering folders or constructing complex Boolean search strings, the user interacts with the system using plain natural language.

• The Agent Workflow: As Jan Van Hoecke noted during the demonstration, "An AI agent knows how to use the search tools within the core platform really well… so it really does all the hard work for you and just reviews the results coming back and presents you with a list or an answer."
• Playbook Execution: Users can upload or define an internal playbook outlining approved corporate standards. The AI agents then evaluate incoming contracts against these specific parameters, ensuring consistency across every review cycle.
• Tabular Review: To make the results digestible, the system utilizes "Tabular Review," a feature that automatically structures the output of playbooks and complex question lists into a clean, side-by-side comparison table. This drastically accelerates the human lawyer’s ability to spot anomalies, risks, and required redlines.

Official Responses and Perspectives

The transition to an AI-driven, agentic enterprise platform represents a major philosophical shift for document management. In their discussion with Legal IT Insider, Van Hoecke and Furnivall elaborated on the strategy and vision driving these innovations.

Jan Van Hoecke on Unlocking Proprietary Knowledge

Addressing why iManage chose to build a completely new platform rather than simply wrapping third-party AI models around legacy storage, Van Hoecke emphasized the primacy of organizational data:

"We started from a realisation that there’s lots of interest from our customers in AI, but we think that it’s not so much the models or the specific AI tools that make the customers unique, it’s their knowledge and their data which is captured in that platform. So, we needed to reimagine what our platforms would look like to unlock that information."

This perspective highlights a major trend in legal tech: as foundational large language models (LLMs) become increasingly commoditized, the true differentiator for professional services firms is the proprietary data they feed into those models, coupled with the security wrappers that protect it.

Emma Furnivall on Seamless Adoption and Control

Addressing the practical concerns of IT directors and managing partners regarding software upgrades, Emma Furnivall stressed that adoption does not need to be a disruptive enterprise-wide ordeal. Highlighting the frictionless transition from iManage Work to the new platform, she stated:

"All our cloud customers now have access to this next generation platform but there’s a lot of control around who can make this switch as they move through."

This emphasis on administrative control is crucial. Law firms and financial institutions operate under strict client confidentiality and regulatory obligations. Allowing IT departments to phase in user access incrementally ensures that security protocols, user training, and compliance checks keep pace with technological deployment.

Implications for Legal and Financial Institutions

The commercial release of iManage’s next-generation platform carries profound implications for the legal and financial sectors, touching upon workflow efficiency, data governance, and the evolving role of legal professionals.

1. The Death of the Data Migration Project

Historically, adopting a "next-generation" platform meant embarking on a multi-month, high-risk data migration project involving millions of documents, potential downtime, and significant risk of metadata corruption. By engineering the new platform to sit natively alongside existing cloud environments without requiring data movement, iManage has lowered the barrier to entry for advanced AI adoption. Firms can begin utilizing context-driven search and AI agents immediately upon activation.

2. Navigating Imperfect Metadata and Expanding Accuracy

One of the most persistent challenges in knowledge management has been human error: lawyers failing to apply correct metadata tags, saving documents in incorrect folders, or using inconsistent naming conventions. The context fabric’s ability to reason over actual document content, contextual relationships, and organizational activity mitigates the impact of poor hygiene. Even with imperfect inputs, the platform’s AI agents can infer context and surface relevant insights that traditional folder structures would bury.

3. Governance and Security in an "Agentic" World

As software transitions from passive tools to active "agents" capable of executing multi-step tasks autonomously, questions of governance, permissioning, and auditability take center stage.

• Who has access to what?
• Can an AI agent accidentally surface confidential client data across ethical walls?
• How do firms maintain compliance under regulations like GDPR or HIPAA?

While iManage’s built-in administration controls allow firms to dictate precisely who can toggle to the new platform and utilize specific agentic workflows, the broader industry must continue to adapt its risk frameworks. Security cannot be an afterthought; it must be baked directly into the fabric of the AI architecture—an ethos iManage has attempted to operationalize through its permission-aware context layer.

4. Redefining Legal Work

By automating routine, time-consuming tasks like MSA deviation reviews, playbook checks, and side-by-side comparative analyses, platforms like this accelerate the shift in legal practice away from mechanical document review toward higher-level strategic analysis and client counseling. Junior associates and contract managers are freed from the drudgery of line-by-line comparison, allowing them to focus on risk interpretation and commercial advisory services.

Conclusion

The general availability of iManage’s next-generation platform represents more than just a routine software upgrade; it is a foundational rethinking of how legal and financial institutions interact with their most valuable asset: their institutional knowledge.

By combining a deep context fabric, seamless cloud integration, autonomous AI agents, and rigorous administrative controls, iManage has provided a roadmap for how enterprise software can harness the power of artificial intelligence without compromising security, governance, or operational continuity.

As law firms and corporate legal departments continue to absorb these new capabilities, the conversation will inevitably shift from whether to adopt AI-driven workflows to how rapidly they can leverage contextual intelligence to outpace their competitors.

Product demos fall within our commercial TalkingTech offering. For more information, readers and industry professionals are invited to contact the Legal IT Insider commercial team.