CASE STUDY Law Firm | United States
Gibson Dunn Enforces Client-Mandated Confidentiality Requirements and Professional Compliance Rules

Client Need
- Address client confidentiality and firm information security requirements leveraging Intapp Walls.
- Enable adoption of a “pessimistic” (need-to-know) access model, without disrupting lawyer productivity.
- Enforce information barriers and ethical screens to restrict confidential matters, isolate contracts lawyers, and control access of seconded lawyers.
Client Solutions
- Redesign legacy Intapp Walls configurations to simplify policy management and improve software performance.
- Implement a multi-layered access rules framework to provide layers of redundant, client-level protection active when temporary matter-based restrictions expire (e.g., M&A matter conclusion).
- Enable security across iManage, file shares, Microsoft SharePoint, and experience management application.
- Develop and deploy a client, matter, and user security database to surface custom data from Intapp Walls software Application Programming Interface (API).
Why Epiq
- Experience implementing information access controls in complex law firm environments.
- Over 600 successful Intapp Walls projects executed.
- A trusted liaison to the solution provider, helping the firm address challenges and pursue enhancements.
The Epiq Law Firm Advisory team brings tremendous expertise to addressing our complex and demanding Intapp Walls needs. They are incredibly knowledgeable, responsive, and easy to work with. The direct connection they have with Intapp enables them to effectively advocate for our firm and its needs.
— Judy Berman
Director, Conflicts and Information Governance
Results and Benefits
Strengthening confidentiality measures in response to client outside counsel guidelines (OCGs).
Demonstrating commitment to pursuing client confidentiality in response to OCGs and applicable professional rules.
Reducing administrative overhead for risk, IT, and operational staff.
Advancing security foundation and firm-aware framework for governed adoption of internal AI tools.