Magna Legal Case Study

Overview

Streamlining complex legal processes

Magna Legal is a leader in the record retrieval service space, processing hundreds of requests for medical records and other sensitive data each month.

Outdated systems and complex processes lead to long processing times and high risk of errors.

Magna sought to modernize their business processes and the related software RecordTrak to enable them to double their business.

Launch is helping to reimagine their process and building a new set of applications and AI tools to increase efficiency.

As a product designer, I collaborated with the product management and software development teams to create new tools and processes to modernize RecordTrak.

emphasis

Design System, Responsive App Design, Complex User Flows

My Role

Created flow diagrams of current and future-state business processes
Designed new client portal and request intake form
Customized UI library to create custom design system

Technologies

Figma, Miro

What is RecordTrak?

RecordTrak is a complex system that includes a client portal, employee suite of tools and a record custodian portal. This system enables Magna Legal to collect and process legal record requests.

The Design Challenge

Streamline the process of requesting and retrieving records for both clients and employees without sacrificing high quality service.

Building from a in depth Business Process Optimization exercise that uncovered many pain points, we aim to redesign RecordTrak from the ground up.

Our Strategy

Collaboration

Our process has been highly collaborative and iterative with continual feedback from key stakeholders who are experts in Magna Legal ‘s processes.

Prioritizing the Work

The current software contains many different modules and features that will take significant time to recreate, so we have identified the key capabilities to enable in the MVP version.

Enable Future Enhancement

There may be ways to further enhance the capabilities of this product with AI. This is being explored in a parallel workstream which will enable us to integrate AI features later.