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AI That Understands Language

Advanced NLP solutions powered by LLMs and custom models — from sentiment analysis to conversational AI and document understanding

From Text to Insight

Natural language processing unlocks the value in text data. From customer feedback to legal documents, our NLP solutions extract insights, automate workflows, and enable natural human-AI interaction.

NLP Solutions

Large Language Models (LLMs)

Fine-tune and deploy state-of-the-art LLMs like GPT, LLaMA, and custom transformers for your specific use cases and domain.

Content GenerationCode CompletionData Extraction

Sentiment Analysis

Understand customer sentiment from text at scale using aspect-based analysis, emotion detection, and opinion mining.

Social ListeningProduct ReviewsCustomer Feedback

Document Understanding

Extract insights and structure from unstructured documents with named entity recognition, document classification, and summarization.

Contract AnalysisInvoice ProcessingResearch Automation

Conversational AI & Chatbots

Build intelligent chatbots and virtual assistants with intent recognition, dialogue management, and natural responses.

Customer SupportSales AutomationInternal Tools

Machine Translation

Translate text across 100+ languages with context awareness, domain adaptation, and cultural sensitivity.

Content LocalizationReal-time TranslationMultilingual Support

Semantic Search & RAG

Search by meaning, not just keywords, using embeddings and retrieval-augmented generation for accurate answers.

Knowledge BaseDocument SearchQ&A Systems

Real-World NLP Use Cases

Customer Support Automation

AI-powered chatbots that understand and resolve customer queries

80% query automation
24/7 availability
Multi-language support

Document Intelligence

Extract structured data from contracts, invoices, and forms

95% accuracy
10x faster processing
Audit trail

Content Moderation

Automatically detect harmful, offensive, or inappropriate content

Real-time filtering
Multi-language
Customizable rules

NLP Tools & Frameworks

Models

GPT-4
LLaMA
BERT
T5
Mistral

Frameworks

Hugging Face
LangChain
spaCy
NLTK

Vector DBs

Pinecone
Weaviate
Milvus
Chroma

Deployment

vLLM
TensorRT-LLM
FastAPI
Azure OpenAI

NLP Development Process

1

Requirements

Define use cases and success metrics

2

Data Prep

Clean, annotate, and prepare training data

3

Model Selection

Choose base model (LLM vs custom)

4

Fine-tuning

Adapt model to your domain and data

5

Evaluation

Test on real-world scenarios

6

Deployment

Deploy with monitoring and guardrails

Build NLP Solutions That Understand

Let's create language AI that transforms text into action.