Robin AI · 2022

Revolutionising query experience with natural language

As part of our commitment to enhancing user experiences through innovative technology, we embarked on a project to transform the way users interact with our Query feature. The goal was to leverage Generative AI to enable natural language querying, simplifying the process while maintaining accuracy and efficiency. This case study delves into our journey, challenges, solutions, and the positive impact on our users.

↓Time-to-insight for contract review

NLPReplaced rigid query builders

↑Query success through iterative testing

The key decision

Legal teams needed the power of advanced filters, but rigid query builders created steep learning curves and failed searches during contract review. A chat-only replacement risked hiding the precision reviewers still required.

We replaced the query builder with natural language input and progressive disclosure: power-user filters stay one click away, not buried behind syntax.

The system

Natural language inputPlain-language queries replace rigid boolean builders at the point of search

Intent parserTranslates user language into structured parameters the contract index understands

Results workspaceReview, refine, and export matches with advanced filters surfaced only when needed

How it worked

User describes what they need in plain language

System maps intent to structured query parameters

Advanced filters surface progressively when precision is required

User reviews results, refines, and shares findings

Validation & rollout

Usability testing with legal teams

NLP query beta

Progressive disclosure rollout

Improved query success org-wide

Visuals

Role: Senior Product Designer
Year: 2022
Focus: AI · Legal Tech · NLP