From
Amplify, United Kingdom
industry
LegalTech & RegTech
Deliverables
UI/UX Design, Digital product development
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TEAM MEMBERS
10
PROJECT TIMEFRAME
5+ years
Understanding legal and regulatory communications can be a daunting task for many customers. Often, the language used is complex and filled with jargon, making it difficult for individuals to grasp the essential information. This lack of clarity can lead to misunderstandings and confusion, ultimately affecting the customer's ability to make informed decisions.
To address this issue, Amplifi offers a solution that leverages Artificial Intelligence and Machine Learning. By analyzing the text of legal documents, Amplifi identifies challenging words, sentences, and clauses. It then provides clear suggestions to enhance the readability of the content, ensuring that customers can easily comprehend the information presented to them. This not only improves understanding but also empowers customers to engage more confidently with legal materials.
Phase 1
UX/UI design
We kicked off with deep discovery sessions together with Amplifi’s legal and compliance experts. This shaped a clean, editor-first interface that feels familiar to lawyers yet intuitive for non-legal users. Collaborative brainstorming, rapid wireframes, and multiple usability testing rounds with real compliance teams ensured every feature solved a genuine pain point.
Phase 2
Digital product development
In parallel sprints we built the AI-backed readability engine, document parser, and suggestion system. Close daily syncs with Amplifi’s data-science team, continuous integration of new language models, and rigorous accuracy testing kept us on track while maintaining the highest legal-language standards.
Phase 3
Maintenance and upgrade
After launch we entered a 12-month enhancement partnership. Monthly releases bring new readability metrics, expanded language-model coverage, and client-specific templates. Regular feedback loops with end-users and compliance officers guarantee the platform keeps evolving exactly where it matters most.
