Machine Learning

Natural Language Processing

Most enterprise data lives in text: emails, contracts, clinical notes, support tickets, reviews, and reports. NLP turns that unstructured content into structured data that can feed dashboards, trigger workflows, and inform decisions. We build NLP systems that work on your actual documents, not just clean benchmark datasets.

95%

Document Classification Accuracy

70%

Manual Review Time Eliminated

10M+

Documents Processed Monthly

What We Deliver

Natural Language Processing Services

Practical, production-ready work — not proofs of concept that never make it to real users.

Document Classification

Automated categorization of incoming documents, emails, and records into predefined classes for routing and processing.

Information Extraction

Named entity recognition and relation extraction to pull structured data from contracts, forms, and reports.

Sentiment & Intent Analysis

Classify customer feedback, support tickets, and survey responses by sentiment, intent, and urgency at scale.

Document Summarization

Automated summarization of long-form documents including legal filings, research reports, and meeting transcripts.

How We Engage

Common Engagements

01

Contract Intelligence

Extract key terms, obligations, and dates from legal contracts to feed a contract management database.

02

Clinical Documentation

Structure free-text clinical notes into coded diagnoses, medications, and procedures for EHR integration.

03

Customer Feedback Analysis

Automated sentiment and topic analysis on support tickets, reviews, and survey responses to surface product insights.

04

Compliance Document Review

Regulatory filing analysis that flags risk language and classifies document sections for compliance teams.

Why InnovTen

What You Can Count On

  • Pre-trained models adapted to your domain vocabulary and document types
  • Processing pipelines that handle PDFs, scanned images, and structured text formats
  • Confidence scoring so borderline documents route to human review rather than auto-processing
  • Multilingual support for organizations operating across language markets
  • Incremental labeling workflows to improve model accuracy as volume grows

Technologies We Use

HuggingFace Transformers spaCy NLTK OpenAI AWS Textract Azure Document Intelligence Python

Ready to Get Started?

Tell us about your project and we'll put together a practical path forward.

Talk to Our Team