NLP Development Services

Take Advantage of our Years of NLP Development Services to Build Your Advanced Solution

Azumo builds custom NLP systems that classify text, extract entities, analyze sentiment, and power conversational AI. We built a named entity recognition system for Meta that extracts supplier capabilities from unstructured text across a 3.5M+ supplier database, and we work across lightweight ML models and LLMs to fit your accuracy, latency, and cost requirements.

Introduction

How Azumo's NLP Development Services Work

Azumo builds custom NLP systems for text classification, named entity recognition, sentiment analysis, document processing, and semantic search. Our NLP work includes a Named Entity Recognition system for Meta that extracts supplier capabilities and products from unstructured text, enabling more precise supplier matches across a large and growing database.

We develop NLP solutions using both modern LLM-based approaches and traditional ML methods. For high-volume, low-latency tasks like email classification or intent detection, we build lightweight models that run efficiently at scale. For complex tasks that need deep language understanding, we use GPT, Claude, and open-source LLMs with domain-specific fine-tuning.

We have built chatbots since 2016, and our NLP services cover the full pipeline: data preprocessing and annotation, model selection and training, integration with your text sources (email, support tickets, document repositories, chat platforms), and production deployment with performance monitoring.

NLP Challenges Azumo Helps Solve

General-purpose language models handle everyday English, but they fumble your industry terminology, internal jargon, and domain-specific nuance. Without NLP built for your context, you get chatbots that frustrate customers and analytics that miss the signal. Azumo builds NLP tuned to your language, data, and systems.

The Problem Azumo's Solution
Domain vocabulary defeats generic models
Models trained on general text miss industry-specific terms, acronyms, and contextual meanings unique to your business.		 We tune models to your language
Azumo fine-tunes NLP models on your terminology, taxonomies, and domain data so the system understands the terms your business actually uses.
Multilingual support adds exponential complexity
Scaling NLP across languages requires separate training data, cultural context, and localized validation for each market.		 Azumo builds multilingual NLP with per-language validation
Using cross-lingual models like XLM-RoBERTa and native Spanish and Portuguese QA, we validate accuracy language by language.
Integration with legacy systems fails
Connecting NLP to existing enterprise workflows takes custom connectors and ongoing maintenance as systems change.		 We connect NLP to your existing systems
Our NLP engineers build and maintain connectors to your email, tickets, documents, and chat platforms so NLP fits your real workflows.
Accuracy varies wildly by use case
A model that excels at sentiment analysis may fail at entity extraction, requiring different architectures per task.		 Azumo matches the architecture to the task
Our NLP developers select and evaluate the right model per task and measure precision, recall, and F1 on your own data before deployment.
Comparison vs Alternatives

Rule-Based vs. Traditional NLP vs. LLM-Based NLP: Which Approach Is Right for Your Business?

Criteria Rule-Based Text Processing Traditional NLP LLM-Based NLP by Azumo
How it works Regex patterns, keyword matching, and hand-coded decision trees. Statistical models such as TF-IDF, word embeddings, and CRF. Our NLP team builds transformer models trained on large corpora and tuned to your domain.
Training data needed None, since rules are written manually. Thousands of labeled examples per task. Our NLP development team uses zero-shot or few-shot for many tasks and needs only hundreds of examples for fine-tuning.
Language understanding Exact string matches only, no semantic context. Statistical patterns and word relationships, limited reasoning. Our engineers deliver understanding of context, nuance, implied meaning, and multi-step reasoning.
Customization Write new rules for every edge case and language variation. Retrain models per domain with labeled datasets. Our NLP team customizes with prompt engineering, RAG for grounding, or fine-tuning for specialized behavior.
Cost to operate Minimal compute; runs on any server. Low to moderate; small models on standard CPU infrastructure. Our developers manage the higher compute with model selection and optimization.
Best for Simple routing, exact keyword alerts, structured extraction. Named entity recognition, sentiment analysis at scale, text classification. Our NLP team builds for complex queries, summarization, generation, and multi-turn conversational AI, selecting the right approach per task.

Key Features of the NLP Solutions We Build

Language Understanding with Context and Sentiment. We build systems that interpret meaning, context, and sentiment in your text, not just keywords.

Entity and Relationship Extraction. Our NLP developers extract named entities and the relationships between them to turn unstructured text into structured data.

Multilingual Processing. Our NLP engineers build cross-language systems with translation and per-language validation for global coverage.

Conversational AI. Our NLP developers build dialogue management and intent recognition for chatbots and virtual assistants that understand what users mean.

Our capabilities
Our Capabilities for NLP Development Services

Turn unstructured text into actionable insights, with NLP solutions that cut processing time by 90% and improve accuracy by 25%, so your teams focus on strategic work.

How We Help You:

Text Understanding

The NLP systems we build analyze and interpret unstructured text to extract meaning, sentiment, and context from documents, emails, social posts, and reviews, so you gain insights and make data-driven decisions.

Language Translation

The translation systems we build convert text between multiple languages with high accuracy and fluency, so you can reach global audiences and expand your international presence.

Sentiment Analysis

The sentiment analysis models we build detect and analyze sentiment, opinion, and emotion in text to gauge customer satisfaction, brand sentiment, and market trends, so you can tailor your strategies accordingly.

Text Classification

The text classification models we build categorize documents and messages into your predefined labels, so you can organize large volumes of text, automate content moderation, and streamline information retrieval.

Named Entity Recognition (NER)

The NER systems we build identify and extract named entities such as names, organizations, locations, and dates, so you can support entity linking and information extraction across your use cases.

Question Answering

The question-answering systems we build understand and answer natural-language questions with accurate, relevant responses, so you can automate support, improve search, and raise engagement.

Engineering Services

Our Engineering Services for NLP Development Services

NLP enables computers to understand, interpret, and generate human language, so by analyzing and processing text our applications help you extract insights, automate tasks, and improve communication across domains.

Sentiment Analysis

The systems we build give you valuable insight into customer opinions and emotions, analyzing text from social media, surveys, and reviews so you understand customer sentiment, identify trends, and make informed decisions.

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Chatbots and Virtual Assistants

The NLP-powered chatbots and virtual assistants we build enhance customer engagement and support, understanding and responding to natural-language queries, providing personalized assistance, answering questions, and automating routine tasks.

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Text Summarization

Our solutions streamline information processing and decision-making, automatically generating concise summaries of lengthy documents, articles, or reports so users quickly grasp key insights and make informed decisions.

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Language Translation

Our NLP solutions break down language barriers and expand your global reach, converting text between multiple languages accurately and efficiently to support communication and collaboration across diverse cultures and regions.

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Case Study

NLP Systems in Production for Our Customers

Language understanding at scale: extraction, classification, and analysis.

Meta

Enterprise AI Development: A Generative Semantic Search Engine

3.5M+
Suppliers Indexed
Read the Case Study
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Photo image of a software development outsourcing project. The image is a man smiling in an office setting after a successful software product demo

AI-Powered Talent Intelligence Company

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Centegix

Read the Case Study

Facebook

Designed, Developed, and Deployed Chatbot for Supplier Management

Read the Case Study
Benefits
What You'll Get When You Hire Us for NLP Development Services

Our NLP work includes a named entity recognition system for Meta that extracts supplier capabilities from unstructured text, automated email classification, and semantic search for enterprise knowledge bases. We build with lightweight ML models for high-volume tasks and LLMs for complex understanding, choosing based on your accuracy, latency, and cost needs.

Streamlined Information Extraction

We extract insights from your unstructured text, from emails to social posts to feedback, identifying the trends, sentiments, and topics that inform data-driven decisions.

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Automated Customer Support

Our NLP developers build chatbots and virtual assistants that understand natural-language questions and resolve inquiries in real time, so customers get seamless, efficient support.

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Sentiment Analysis

We analyze customer sentiment across reviews, social posts, and surveys, so you can spot areas to improve and address concerns early.

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Content Curation and Personalization

Our NLP specialists build recommendation systems that read user content and interactions to personalize what each person sees, so you increase engagement and conversions.

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Compliance and Regulatory Compliance

Our NLP engineers build NLP that reads legal documents, contracts, and compliance material, so you can automate monitoring and risk assessment and reduce compliance risk.

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Language Translation and Localization

Our solutions translate and localize your content across languages efficiently, so you can reach global audiences and expand into new markets.

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Why Choose Us
Why Choose Azumo as Your NLP Development Company
Partner with a proven NLP development company trusted by Fortune 100 companies and innovative startups alike. Since 2016, we've been building intelligent AI solutions that think, plan, and execute autonomously. Deliver measurable results with Azumo.

2016

Building AI Solutions

300+

Successful Deployments

SOC 2

Certified & Compliant

"Behind every huge business win is a technology win. So it is worth pointing out the team we've been using to achieve low-latency and real-time GenAI on our 24/7 platform. It all came together with a fantastic set of developers from Azumo."

Saif Ahmed
Saif Ahmed
SVP Technology
Omnicom

Frequently Asked Questions

  • Azumo builds production NLP systems for document classification, entity extraction, sentiment analysis, text summarization, language translation, search relevance, chatbots, and voice interfaces. We work across the full NLP stack: rule-based systems for structured extraction, classical ML models like BERT and RoBERTa for classification, and large language models from OpenAI, Anthropic Claude, LLaMA, and Mistral for generative tasks. Real projects include an AI-powered supplier search tool for Meta that parses unstructured vendor data, a standalone NLP model for gaming, and document processing for financial services. We deploy on AWS, Azure, and Google Cloud. SOC 2 certified with nearshore teams across Latin America working in US time zones.

  • NLP (natural language processing) is the broad field of teaching machines to work with human language. NLU (natural language understanding) is the subset focused on comprehension: parsing intent, extracting entities, resolving ambiguity, and classifying meaning. NLG (natural language generation) is the subset focused on producing human-readable text from structured data or prompts. A customer support system uses all three: NLU to understand the question, NLP pipelines to retrieve relevant information, and NLG to compose a natural-sounding response. Azumo builds systems that combine NLU and NLG, for example RAG-based document Q&A that parses queries, retrieves context, and synthesizes cited answers.

  • Azumo works with transformer-based models including BERT, RoBERTa, DeBERTa, and DistilBERT for classification and extraction. For generative NLP, we use GPT-4o, Claude, LLaMA 3, and Mistral. We build with Hugging Face Transformers, spaCy for entity recognition and dependency parsing, and NLTK for preprocessing. For production, we use ONNX Runtime and TensorRT for inference optimization. Cloud services include AWS Comprehend, Azure Cognitive Services, and Google Cloud Natural Language API for teams that prefer managed NLP. We also fine-tune open-source models on your domain data when off-the-shelf accuracy is insufficient. Valkyrie provides unified model access across providers.

  • Every NLP project starts with data assessment: evaluating your text corpus for volume, quality, language distribution, and label availability. We then select the right approach for your accuracy requirements and budget. For classification, we typically fine-tune BERT-family models, which reach high accuracy with relatively small training sets of 500 to 2000 examples per class. For extraction like named entity recognition, we combine pre-trained models with domain-specific training data. For generative tasks, we use prompt engineering, few-shot learning, or LLM fine-tuning depending on complexity. We build evaluation pipelines that measure precision, recall, and F1 on held-out test sets from your actual data, with bias and edge-case testing before deployment.

  • NLP delivers strong ROI in financial services, healthcare, legal, e-commerce, and media. Financial firms use NLP for earnings call analysis, SEC filing extraction, fraud detection in transaction narratives, and compliance reporting. Healthcare automates clinical note processing, medical coding, and literature review while maintaining HIPAA compliance. Legal teams accelerate contract analysis, clause extraction, and regulatory research. E-commerce uses NLP for product categorization, review sentiment analysis, and search relevance. Media automates content tagging, summarization, and translation. Azumo has built NLP across these verticals, including Meta's supplier search tool and document processing for financial services.

  • A proof-of-concept NLP model on your data can be delivered in 1-3 weeks depending on data readiness. Production systems with enterprise integrations typically take 2-6 months. Key timeline factors are data preparation, which usually takes the most time, plus model selection and fine-tuning, integration complexity, and accuracy requirements. Simple classification with clean labeled data can reach production in 6-8 weeks, while complex extraction or multilingual systems take longer. Azumo accelerates delivery with pre-built text processing pipelines, established evaluation frameworks, and active learning workflows that reduce labeling effort. Our nearshore teams work in US time zones with sprint-based delivery.

  • Azumo builds multilingual NLP using cross-lingual transformer models like XLM-RoBERTa and mBERT that support 100+ languages in a single model. For translation, we integrate Google Cloud Translation, DeepL, and open-source models like NLLB. For domain-specific multilingual accuracy, we fine-tune on your parallel text across target languages. Our approach handles code-switching, dialectal variation, and non-Latin scripts including Chinese, Japanese, Korean, Arabic, and Hindi. We evaluate models per language to find accuracy gaps and apply targeted fine-tuning where needed. Our team in Latin America provides native Spanish and Portuguese QA alongside English.

  • Azumo is SOC 2 certified and implements end-to-end encryption, role-based access controls, PII detection and redaction, and audit logging for all NLP systems. Text often contains sensitive information such as names, account numbers, and medical or legal details, so we build PII detection that identifies and masks sensitive entities before they reach training or inference. For regulated industries, we implement HIPAA-compliant text processing, GDPR data minimization, and audit trails that log every document processed. We deploy within your private cloud or on-premises when data cannot leave your environment, and all models undergo bias evaluation for equitable performance across demographics and language varieties.