Financial & Enterprise
DAE Search
Making enterprise data actually findable
- 20%
- ROI from better discovery
- –65%
- Information retrieval time
- +85%
- Search accuracy
- –40%
- Support tickets
Role
Lead Product Designer
Timeframe
2024
Outcome
Retrieval time down 65% · 20% ROI from better discovery
AI Tools
GPT-4, Semantic Search AI
Dev Stack
React, ElasticSearch, Python
Design Tools
Figma, Auto-Layout
Overview
A redesign of an enterprise search platform that transformed how teams discover and access critical business data — reducing information retrieval time by 65% and delivering 20% ROI through improved productivity.
Research
Employee interviews revealed critical gaps in enterprise data discovery and access patterns.
Data silos were costing productivity.
Discovery barriers
Teams spend 3+ hours daily searching for existing data across disconnected systems.
→ Drove: Unified search interface with intelligent content tagging and federated results.
Permission complexity
Access control confusion leads to either data hoarding or security breaches.
→ Drove: Visual permission indicators and smart access request workflows.
Context loss
Found data lacks business context, making it unusable without tribal knowledge.
→ Drove: Rich metadata display with usage patterns and related content suggestions.
The problem
Enterprise teams lose 40% of their productive time hunting for data that already exists. Critical decisions get delayed, projects stall, and knowledge workers become frustrated with disconnected systems that hide rather than reveal insights.
The approach
- 1
Moved beyond keyword matching to semantic search that understands intent — increasing relevant results by 85% and cutting refinement queries by 70%.
- 2
Made visual data lineage a first-class feature: sources, freshness, and transformation history give users the confidence to act on results immediately.
- 3
Turned permission barriers into guided pathways with visual access indicators and one-click request workflows.
Key insights
Semantic search changed everything
Moving beyond keyword matching to intent understanding increased relevant results by 85% and reduced refinement queries by 70%.
Visual data lineage built trust
Showing data sources, freshness, and transformation history gave users confidence to act on search results immediately.
Smart permissions reduced friction
Proactive access suggestions and one-click request workflows turned permission barriers into guided pathways.
My thought process
Enterprise search isn't just finding files — it's understanding business context. I designed for the moment when someone needs to make a decision with incomplete information. The interface needed to bridge the gap between data discovery and business insight, making every search result a learning opportunity.
User testing
Prototype sessions with enterprise teams showed information retrieval time dropping to 5 minutes (vs 15+ previously), with search accuracy up 85%.
- 5 min
- Avg. retrieval time
- ↑85%
- Search accuracy
- 90%
- Found lineage valuable
What didn't work
Early versions tried to replicate consumer search patterns, but enterprise users needed more structure and context. A flat results list confused users who needed to understand data quality and permissions upfront. We also learned that auto-complete suggestions backfired when they exposed restricted content, creating security concerns.
The outcome
The platform transformed enterprise data discovery from a daily frustration into a competitive advantage, delivering measurable ROI through improved productivity and decision-making speed.
Next case study
ROI Design Calculator →