AI & Machine Learning

NLP — Making Sense of Unstructured Data at Scale

NLP transforms unstructured text into structured intelligence — unlocking insight from contracts, emails, support tickets, social media, and regulatory filings at scale.

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Capabilities

Natural Language Processing — deep expertise

Sentiment Analysis

Aspect-based sentiment classification across customer reviews, social media, and NPS surveys — granular, actionable insight beyond simple positive/negative scoring.

TransformersBERTAspect-BasedReal-Time

Contract Intelligence

Automated clause extraction, obligation identification, risk flagging, and comparison across legal contracts — reducing legal review time by 70%.

NERClause ClassificationContract Analytics

Information Extraction

Named entity recognition, relation extraction, and event detection from domain-specific text — converting unstructured documents into structured knowledge.

NERRelation ExtractionKnowledge Graphs

LLM Integration (RAG)

Retrieval-augmented generation architectures grounding large language models in your proprietary knowledge base — accurate, private, and hallucination-resistant.

RAGLangChainOpenAIAnthropicVector DBs

Speech Analytics

Automatic speech recognition and conversation analysis for call center quality monitoring, compliance, and customer experience insights.

WhisperAWS TranscribeSpeaker Diarization

Multilingual NLP

NLP pipelines supporting Portuguese, English, Spanish, and 50+ languages — enabling global analytics and customer experience personalization.

mBERTXLM-RoBERTaTranslationMultilingual

NLP Results

Natural Language Processing in Production

80+

NLP systems in production

94%

Avg entity extraction accuracy

70%

Legal review time reduction

50+

Languages supported

Our Approach

From Unstructured Text to Business Intelligence

Text Data Review

Assess your text data sources, volumes, languages, and the NLP use cases with highest business impact.

Model Design

Select NLP approaches — classification, NER, summarization, sentiment — and design the processing pipeline.

Training & Validation

Fine-tune models on domain-specific text, validate with subject matter experts, and test in staging.

Production Deploy

Integrate NLP outputs into your applications with monitoring, feedback loops, and model refresh cadence.