Designing persistent memory in Embra

Embra’s core differentiator is its AI-powered graph database that connects customer relationships, interactions, and business context. I designed the experience that helps users capture information from meetings and interactions, structure it into connected data, and reuse that context to support future workflows.

Client: Embra

Founding product designer

Product Design

8 weeks

The problem

Sales conversations generate valuable context, but important details often live in scattered notes or recordings. Once a meeting ended, insights were difficult to find, share, or build on. Embra needed a way to retain this information and make it useful over time.

The approach

I partnered closely with customers and engineering to define how meeting content should become usable context.

Customer interviews helped clarify how teams prepared for meetings and followed up afterward. From there, I worked with engineering to shape a data model around core business objects and designed a product structure that made this information easy to navigate and maintain. The experience was refined through ongoing dogfooding and customer feedback.

Impact

The interaction model made it possible to manage complex customer data without the overhead typical of CRM tools. Teams could move quickly between scanning, filtering, and editing, which reduced friction and encouraged the system to stay up to date.