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AI

Survey Analysis Platform

Turn mixed survey data into quantitative insight and qualitative highlights.

Role
ML / backend engineer
Year
2021
Timeline
Research + delivery
PythonNLPFastAPIMongoDBAWS
01The situation

A research team had rich survey responses across text, numbers, images and video, but no fast way to move from raw responses to insight and shareable highlights.

02The constraint

The data was genuinely multi-modal, and 'the interesting bits' had to be found semantically, not by keyword.

03The decisions

Used semantic search to surface and reel together highlights.

Instead of Keyword filters over transcripts.

Why: Semantic search found relevant moments even when the words didn't match, which is where qualitative insight actually lives.

04What I built
  • Multi-modal ingestion (text, numeric, image, video)
  • Quantitative + qualitative analysis
  • Semantic-search highlight & showreel generation
  • Dockerised deploy on EC2 with Nginx
05The result
Multi-modaltext, numeric, image and video in one pipeline
Semantichighlights found by meaning, not keywords
Hemant Manglani

Hemant Manglani

Ahmedabad, India

Looking for someone who ships? Let’s talk.

I’m actively looking for a backend or AI engineering role. If your team needs an engineer who can own systems end to end, I’d love to hear about it.

Actively looking · Ahmedabad · on-site, hybrid or remote