Harmony: Automated Questionnaire Data Extraction

Challenge

Harmony needed to process large volumes of questionnaires and extract structured information efficiently. Manual data entry was time‑consuming, error‑prone, and couldn't scale with growing document volumes.

Solution

We developed an NLP‑powered extraction system that automatically processes questionnaires and extracts structured data:

• NER: Custom models to extract respondent info, question IDs, response categories, and metadata.
• Text Classification: Multi‑label classifiers to categorize question types (multiple choice, open‑ended, Likert scale, demographic, etc.).
• Intelligent Parsing: Context‑aware algorithms for varied questionnaire formats and layouts.
• Structured Output: Conversion of unstructured text into clean, queryable datasets.

Results

• ✅ 95% reduction in manual data entry time
• ✅ 98% extraction accuracy for key entities
• ✅ Processing 1,000+ questionnaires/hour (vs. 10 manually)
• ✅ Eliminated human transcription errors
• ✅ Enabled real‑time analysis of questionnaire data