Implementation-focused summary
From “where is that file?” to instant retrieval
Built for teams managing large media libraries where inconsistent naming and nested folders create knowledge silos and slow down sales, marketing, and operations.
Problem
Teams routinely needed specific product images or training videos, but assets lived in deeply nested folders with inconsistent naming. Retrieval took minutes and often depended on long-tenured staff who knew where everything was.
Solution
A cloud-hosted media intelligence platform that accepts voice queries, parses intent and keywords into structured search criteria, and returns a ranked grid of relevant images and videos with rich previews.
How it works
Voice
Speech recognition tuned for domain vocabulary and natural phrasing.
Indexing
Scheduled crawlers extract metadata and keep the index fresh.
Ranking
Fuzzy matching + similarity scoring tuned for speed and confidence.
Architecture & Stack
- Speech recognition layer for voice input with domain-specific vocabulary.
- Indexing pipeline that scans folders, extracts metadata, and updates on schedule.
- Search and ranking engine combining fuzzy string matching and similarity scoring.
- Responsive web UI with preview grid for images and videos.
Impact
- Asset retrieval time reduced from minutes to seconds.
- Lowered dependency on “tribal knowledge” and reduced internal escalations.
- Improved adoption of the asset library as it became easy to use.
Your role
Engineered the end-to-end platform: voice interface, indexing, ranking, and UI — and positioned it as a reusable pattern for any organization with large internal media libraries.