Breakthrough AI Search Delivers Trusted Insights

# iManage Delivers Trusted AI Search with Ask iManage

Introduction

In the fast-paced world of legal, accounting, and professional services, finding the right information quickly is often a race against time. iManage, a leader in document and email management, has introduced **Ask iManage**, an AI-powered search tool designed to solve the problem of information overload. It leverages generative AI to provide precise, context-aware answers drawn directly from a firm’s own secure knowledge base. This tool is specifically engineered for professionals in regulated industries who require both speed and strict compliance. The key benefits include significantly reduced time spent searching for documents, improved accuracy in retrieving relevant information, and a trusted AI experience that respects existing security protocols.

Key Features and Capabilities

Ask iManage is built on a foundation of security and precision, distinguishing it from generic AI search tools. Its primary capability is natural language querying, allowing users to ask complex questions like “What were the key liability clauses in the merger agreement with ABC Corp?” rather than relying on simple keyword searches. The tool provides conversational answers with citations, linking directly to the source documents within the iManage repository. This ensures that every piece of information can be verified, which is critical for audit trails and compliance.

Another standout feature is its deep integration with the iManage Work ecosystem. It doesn’t just index metadata; it understands the content of documents and emails, including PDFs and scanned images, thanks to advanced OCR and content extraction. For firms concerned about data privacy, Ask iManage operates on a “zero-retention” model for customer data, meaning prompts and responses are not used to train public AI models. This focus on data security is a major selling point for legal and financial institutions handling sensitive client information.

How It Works / Technology Behind It

At its core, Ask iManage utilizes a combination of large language models (LLMs) and iManage’s proprietary knowledge graph. When a user submits a query, the system first interprets the intent and context. It then performs a semantic search across the firm’s document and email management system, identifying the most relevant chunks of text. These are fed into the LLM to generate a coherent, synthesized answer.

Crucially, the technology includes a “grounding” mechanism. The AI is constrained to answer only based on the documents within the firm’s iManage environment, preventing hallucinations or reliance on external, unverified data sources. The system also respects user permissions; if a user doesn’t have access to a specific document, the AI will not include information from it in the response. This technology stack ensures that the AI acts as a knowledgeable assistant rather than an unpredictable oracle, maintaining the integrity of the firm’s information governance policies.

Use Cases and Practical Applications

The practical applications for Ask iManage are extensive within professional services. For **litigation support**, lawyers can quickly summarize case facts or find precedents across thousands of historical case files without manually reviewing each one. In **due diligence**, teams can ask the AI to identify specific risk clauses across a large volume of contracts, drastically cutting down review time.

**Corporate governance** is another key area; secretaries can instantly retrieve information on board meeting minutes or specific resolutions. For **accounting firms**, the tool can help auditors find supporting documentation for specific transactions across client files. A real-world example would be a partner preparing for a client meeting who needs a quick refresher on all past engagements; they can ask “Summarize our work for Client X over the last five years” and receive a concise overview with links to relevant reports and emails.

Pricing and Plans

Specific pricing details for Ask iManage are not publicly listed on their website, as costs are typically customized based on the firm’s size, existing iManage deployment (cloud or on-premise), and specific feature requirements. iManage generally operates on a subscription model, often priced per user per month.

For firms already using iManage Work 10, Ask iManage may be available as an add-on module. It is recommended that interested organizations contact iManage sales directly for a tailored quote. While the investment may be significant compared to generic AI tools, the value proposition lies in its native integration, security compliance, and the efficiency gains specific to high-value professional work. Compared to building an in-house AI search solution, Ask iManage offers a lower total cost of ownership and faster deployment.

Pros and Cons / Who Should Use It

**Pros:**
* **High Security:** Built for regulated industries with zero-data retention policies.
* **Native Integration:** Seamlessly works within the existing iManage ecosystem.
* **Cited Answers:** Provides source links for verification, reducing hallucination risks.
* **Semantic Search:** Understands context, not just keywords.

**Cons:**
* **Ecosystem Lock-in:** Most valuable for firms already committed to iManage; less compelling for those on other DMS platforms like NetDocuments or SharePoint.
* **Cost:** Likely a premium product compared to general-purpose AI tools.
* **Learning Curve:** While designed for ease of use, shifting workflows to rely on AI requires some change management.

**Who Should Use It:**
Ask iManage is ideal for mid-to-large law firms, corporate legal departments, accounting firms, and consulting agencies that already use iManage as their document management system. It is particularly valuable for roles that require extensive research, such as associates, paralegals, knowledge managers, and partners. If your firm prioritizes data sovereignty and needs to extract maximum value from existing intellectual property, this tool is a strong contender.