We build language AI systems that understand context, intent, and nuance not just keywords. From chatbots to enterprise NLP pipelines, we build for production reliability.
GPT-4 • Claude • Hugging Face • LangChain • spaCy • Rasa • Pinecone
NLP allows organisations to automate tasks that previously required human reading and judgement classifying documents, extracting information, detecting sentiment, routing queries, and generating coherent responses. Conversational AI and chatbots sit at the most visible end of NLP done well they reduce support costs and improve response times; done poorly they frustrate users and damage the brand.
We cover the full NLP spectrum text classification, named entity recognition, intent detection, sentiment analysis, semantic search, document intelligence, RAG systems, and full chatbot development. Every system is designed for your specific use case and data, not from a generic template.
Conversational chatbots that handle customer queries, automate support, generate leads, and assist internal teams using NLP to understand intent, maintain context, handle ambiguity, and escalate to humans when needed.
Customer support chatbots with intent classification and context management
Lead qualification and sales assistant chatbots
HR and internal helpdesk automation
Multi-turn dialogue with graceful escalation handling
Multilingual English, Hindi, Gujarati, and other Indian languages
NLP pipelines that extract structured meaning from unstructured text reducing manual reading and classification across emails, support tickets, forms, reviews, and reports.
Text classification for document routing and support triage
Named entity recognition names, dates, locations, domain-specific terms
Sentiment analysis for customer feedback and social media monitoring
Intent detection and topic modelling for knowledge management
We integrate GPT-4, Claude, Gemini, and open-source LLMs into your applications with prompt engineering, context management, output validation, and RAG systems that ground responses in your own data.
RAG systems for knowledge-grounded LLM responses
Document summarisation and intelligent report generation
Semantic search powered by vector embeddings
Secure, scalable LLM infrastructure and API cost management
Automated extraction of structured data from invoices, contracts, forms, medical records, and regulatory documents feeding results directly into downstream systems without manual data entry.
Invoice and purchase order extraction and validation
Contract clause identification and obligation extraction
Medical record parsing and clinical data extraction
OCR integration for scanned document processing
Search that understands meaning, not just keywords surfacing relevant results even when exact words don’t match. Particularly valuable for knowledge bases, document libraries, and product catalogues.
Embedding-based semantic search over document repositories
Product and catalogue search with intent understanding
Hybrid semantic and keyword search for precision
Integration with Pinecone, FAISS, Weaviate, and Elasticsearch
Process customer feedback, reviews, and support tickets at scale identifying sentiment, pain points, and emerging trends that would take a human analyst weeks to surface manually.
Customer review and feedback sentiment classification
Support ticket scoring for priority routing
Brand sentiment tracking across social media
Aspect-based analysis for granular product feedback
We define conversation flows, NLP requirements, and integration points before any development begins.
Chat logs, FAQs, domain documents annotated and prepared with data privacy compliance throughout.
Intent classifiers, entity extractors, and response generators built and validated iteratively on your domain data.
Multi-turn flows, fallback handling, escalation paths designed to match your brand voice and business rules.
Deployed into your website, app, CRM, or internal tools via APIs on AWS, GCP, Azure, or on-premise.
Performance monitoring, retraining on new data, quarterly reviews keeping accuracy strong over time.
Here is what genuinely distinguishes our React team.
A focused customer support chatbot typically takes six to ten weeks. Advanced LLM-powered assistants with custom training and integrations take two to four months. We give you a realistic timeline after a discovery session.
Historical conversation logs, FAQs, or domain documents relevant to your use case. A minimum of 500 to 1,000 labelled examples per intent yields reliable results. We assist with data collection, annotation, and preparation throughout.
Yes. Multilingual support across English, Hindi, and Gujarati is built in by design not added as an optional extra. We build and validate in each target language, not just the dominant one.
Yes. Our chatbots and NLP systems are API-first and integrate with Salesforce, Zoho, Freshdesk, Zendesk, HubSpot, and any system with a REST or webhook interface.
End-to-end encryption, role-based access control, and compliance with India’s DPDP Act and GDPR where applicable. All conversation data is handled under your data governance policies. NDAs are signed before any project begins.
Simple FAQ chatbots start from Rs. 40,000. Custom NLP pipelines and LLM-powered enterprise assistants range from Rs. 1,50,000 to Rs. 10,00,000+ depending on complexity and integrations. We provide a fixed-price estimate after a discovery session.