AI-Powered Text Classification Platform
Operationalizing machine learning classification APIs into an intuitive business tool
A machine learning web system that automates bulk text classification for business documents, categorizing unstructured textual data across multi-level hierarchies (middle, small, product, opinion).
Challenge & Bottlenecks
Internal analysts manually categorized tens of thousands of customer feedback entries and product opinion lines, creating severe operational bottlenecks and human labeling inconsistencies.
Architecture & Strategy
Created a full-stack automation platform connecting machine learning classification models to a frictionless web UI, allowing analysts to upload tabular documents, select target columns, and batch-classify thousands of records instantly.
How The System Operates
Document Ingestion
User uploads structured Excel/CSV documents containing raw unstructured feedback or product comments.
Column & Scope Mapping
System parses document headers and allows user to designate target text columns and desired classification scope.
Batch AI Classification
Backend chunks data payloads and orchestrates high-throughput inference requests against the classification model API.
Enriched Result Export
Predicted taxonomy labels (middle, small, product, opinion) and confidence scores are appended and made ready for export.
Key Technical Highlights
- •Automated complex multi-class text labeling workflows into single-click web operations
- •Supported 4-tier taxonomy: Middle Category, Small Category, Product Level, and Sentiment/Opinion
- •Batch inference queue preventing timeout on large document payloads