Data & AI

AI research agent for law, audit, and consulting firms

This use case presents the implementation of an AI document search agent connected to a firm's EDM system. It allows users to query all internal documents in natural language and quickly access existing information, while complying with existing security and governance rules.

AI use case: document search agent connected to EDM

This use case presents the implementation of an AI document search agent connected to a firm's EDM system.
It allows users to query all internal documents in natural language and quickly access existing information, while complying with existing security and governance rules.

For law, auditing, and consulting firms

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The problem: considerable time wasted in documentary research

On average, a lawyer or consultant spends 30 to 45 minutes searching for a precedent, internal memo, or template in the EDM system before starting each new case.

Multiply by 50 employees.
Multiply by 220 working days.

The result: thousands of hours lost each year navigating SharePoint trees, reformulating searches, and reopening archived files.

And often, the employee ends up redoing the work rather than looking for what already exists.

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The solution: a conversational AI document search agent

A conversational AI agent connected to your EDM (SharePoint, Azure file server) that responds in natural language:

"Find our conclusions on the collective contractual terminations for 2023–2024."
"What are our previous disputes with CAC 40 companies on labor law?"
"Find the model partnership agreement used for the Martin case in 2022."

The agent scans your documents, understands the context, and returns relevant results with direct links to the source files.

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How does an AI document search agent work?

Indexing your existing document database (SharePoint, Azure Files)
Configuring access rules (The agent strictly adheres to existing permissions.)
Customization of the search scope by team or practice.
Deployment in Microsoft Teams

The agent becomes a "virtual colleague" accessible with a single click.

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Concrete benefits measured after deployment

Average search time
Before: 30–45 min
After: 2–5 min

Reuse rate of existing work
Before: ~40%
After: ~80%

User frustration
Before: High
After: Low

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ROI of a document AI agent for a 50-lawyer firm

30 minutes saved per day per lawyer
× 220 days
× 50 lawyers

➡️ ≈ 5,500 hours recovered per year

Valued at $150/hour
➡️≈ $825,000 in time saved per year

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What IT Systems brings to this AI use case

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SharePoint expertise and document governance: Supporting firms such as Gide Loyrette Nouel (670 BAL, 12 TB of data), Littler France, and Lacourte Raquin Tatar for over 9 years.
Mastering Copilot Studio: Configuring agents, managing sources, setting permissions.
Change management: Team training, prompt optimization, continuous adjustment.

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Technical requirements for deploying a document AI agent

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Microsoft 365 Business Premium or E3/E5
SharePoint Online or Azure Files
Standard format documents (Word, PDF, Excel)

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Implementation period

4 to 6 weeks for an initial agent to become operational on a pilot site.

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Demonstration of an AI agent on your own data

Would you like to see a demonstration using your own data?

Contact us to discuss your document environment and discover how an AI agent can be integrated into your existing tools.

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