Natural Language Processing API
About this Project
Developed a comprehensive RESTful API service for advanced natural language processing tasks, featuring text analysis, sentiment analysis, entity recognition, and automated content classification.
Four tools, one API
Sentiment analysis, entity recognition, summarization, and language detection behind clean REST endpoints.
Multiple models, best answer
Requests are routed across spaCy, NLTK, and Transformer models depending on the task.
Built for volume
Batching and caching keep throughput high enough for real production workloads.
Documented like a product
Every endpoint ships with clear documentation and examples, so integration takes minutes.
Different language models disagree, and each has its own speed and memory cost. The API needed a routing layer that picks the right model for each request and keeps responses fast even under heavy load.
The service handles thousands of requests per minute in testing and works as a drop-in text analysis backend for any app.