Tensor Labs
NLP

Natural Language Processing

NLP systems that go beyond simple text analysis: intelligent document processing pipelines, conversational AI, real-time sentiment engines, domain-tuned language models, and voice AI agents powered by Vapi and Retell. Built on GPT-4o, Claude, Llama 3, LangChain, LangGraph, and Hugging Face.

Overview

We build NLP systems that go beyond simple text analysis: intelligent document processing pipelines, production

grade conversational AI, real time sentiment engines, custom language models fine tuned to your domain, and

voice AI agents powered by Vapi and Retell. Using state of the art Transformer architectures, large language

models (GPT-4o, Claude, Llama 3), LangChain, LangGraph, and Hugging Face, our solutions turn unstructured

text into structured, actionable intelligence

What We Build

  • Intelligent Document Processing, Automated extraction, classification, and summarization of contracts,

invoices, reports, and legal documents using transformer based models and OCR

  • Conversational AI and Chatbots, Production grade chatbots and virtual assistants powered by RAG (Retrieval

Augmented Generation), LangChain, LangGraph, and vector databases. Context aware, multi turn conversations

with hallucination guardrails

  • Voice AI Agents, Intelligent phone agents and voice interfaces built with Vapi and Retell AI. Real time speech to

text, natural language understanding, and text to speech for automated customer service, appointment booking,

and lead qualification

  • Sentiment and Opinion Analysis, Real time sentiment classification across reviews, social media, support

tickets, and survey data. Aspect based sentiment analysis for granular insights

  • Named Entity Recognition (NER), Custom entity extraction for domain specific use cases: medical terms,

financial instruments, legal clauses, product attributes

  • Semantic Search and Retrieval, Search engines using embeddings (OpenAI, Cohere, Sentence Transformers)

and vector databases (Pinecone, Weaviate, Qdrant, pgvector). Beyond keyword matching, understanding intent

  • Custom LLM Fine Tuning, Domain specific fine tuning of open source LLMs (Llama 3, Mistral, Phi-3) for

specialized tasks using LoRA, QLoRA, and RLHF techniques

Industries and Applications

Legal and Compliance, Contract analysis, clause extraction, regulatory document processing, and compliance

monitoring.

Healthcare, Clinical note summarization, medical entity extraction, patient communication automation via voice

AI with Vapi, and clinical trial matching.

Customer Experience, AI powered support agents (text and voice), ticket classification, response generation,

and voice of customer analytics using Retell and LangGraph based agent workflows.

Finance, Financial document parsing, earnings call analysis, news sentiment for trading signals, and fraud

detection in text data.

E-Commerce, Product description generation, review analysis, intelligent FAQ systems, and multilingual content

processing.

Tech Stack

  • LLMs, GPT-4o, Claude, Llama 3, Mistral, Phi-3. Fine tuning with LoRA/QLoRA on custom datasets
  • Frameworks, LangChain, LangGraph, LlamaIndex, Hugging Face Transformers, spaCy, NLTK
  • Vector Databases, Pinecone, Weaviate, Qdrant, ChromaDB, pgvector
  • Agentic AI, LangGraph for stateful multi step agents, CrewAI, AutoGen, OpenClaw for multi agent orchestration
  • Voice AI, Vapi for programmable voice agents, Retell AI for conversational telephony, Deepgram and Whisper for

speech to text

  • Deployment, FastAPI, AWS Lambda, SageMaker, vLLM, Ollama for local inference
  • Evaluation, RAGAS, LangSmith, DeepEval, custom hallucination detection and response quality metrics