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Analyze, classify, and extract structured intelligence from high-volume customer feedback, support transcripts, contracts, and multilingual communication feeds.
Enterprises generate millions of words every week across customer reviews, emails, call transcripts, and surveys, but lack the resources to read and categorize it all manually.
Valuable customer complaints, feature requests, and churn risks remain hidden inside unread text data.
We deploy custom NLP pipelines that automatically read, categorize, score sentiment, and extract structured data points across your incoming text streams.
Voice-of-Customer Sentiment Analysis
Track customer sentiment, emotional tone, and emerging product complaints across social media, reviews, and support chats.
Automated Support Ticket Categorization
Classify incoming tickets by urgency, product category, and issue type, instantly routing them to the correct technical department.
Named Entity Recognition (NER)
Train custom entity extractors to detect specialized domain entities (part numbers, legal clauses, medical terms) in raw text.
Multilingual Text Processing
Translate, classify, and analyze customer feedback across dozens of languages while preserving domain terminology.
150%
Reduction in Manual Workload
60%
Faster Decision-Making
3x
Improved Workflow Efficiency
40%
Task Automation Rate
A 5-week path from corpus ingestion to production API deployment.
Ingest historical text corpora (tickets, transcripts, reviews).
Annotate datasets and fine-tune transformer models for domain classification.
Evaluate accuracy, precision, and F1 scores against edge-case phrasing.
Deploy production API endpoints connected directly to your CRM and BI tools.
Ingest historical text corpora (tickets, transcripts, reviews).
Annotate datasets and fine-tune transformer models for domain classification.
Evaluate accuracy, precision, and F1 scores against edge-case phrasing.
Deploy production API endpoints connected directly to your CRM and BI tools.
Frequently Asked Questions
How does traditional NLP differ from LLMs?
Traditional NLP models (like BERT) are lightweight, cost-effective, and fast (sub-50ms latency), making them ideal for high-volume text classification and tagging where generating new text is unnecessary.
Can the NLP model adapt to our industry's slang and technical acronyms?
Yes. We fine-tune models specifically on your industry vocabulary and internal terminology.
Ready to Bring Enterprise-Grade AI into Your Operations?
Book a 30-minute discovery session with our engineering team to evaluate your workflows and identify your highest-impact AI opportunities.
RixDigi is an AI and workflow automation engineering agency building private, production-ready AI solutions for modern enterprises.
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+971 (050) 3495669
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United States
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