NLP Development Services & LLM Integration for Business Applications
Build semantic search, document intelligence, and conversational AI with Unisam. We deliver NLP development services and LLM development services that turn unstructured text into structured business value across the world.
What We Deliver as an NLP Development Company
Unisam builds natural language processing and large language model solutions for businesses that need to understand, analyze, and generate text at scale. Our NLP development services and LLM development services cover the full lifecycle: text processing pipeline design, model selection, semantic search implementation, and production deployment.
Our NLP development services include:
We serve clients in Zurich, Geneva, Vienna, Warsaw, Krakow, Milan, and Rome with delivery teams that understand data privacy, GDPR compliance, and the EU AI Act requirements.
Semantic Search & Document Intelligence
We build search systems that understand meaning, not just keywords. Using embeddings and vector databases, we enable your users to find relevant documents, answers, and insights from large text collections without exact keyword matching.
LLM Integration & Fine-Tuning
We integrate large language models into your applications through APIs, custom fine-tuning, or private deployments. We handle model selection, prompt engineering, RAG architecture, and cost optimization for production reliability.
Text Classification & Entity Extraction
We develop NLP pipelines that automatically categorize documents, extract named entities, identify sentiment, and flag critical information. This turns unstructured text into structured data for analytics and automation.
Document Chatbots & Knowledge Assistants
We build conversational interfaces that answer questions from your documents, manuals, and knowledge bases. Using RAG with source attribution, every answer is grounded in your approved content.
Text Summarization & Generation
We implement abstractive and extractive summarization for long documents, reports, and conversations. We also build controlled text generation systems for templates, descriptions, and structured outputs.
Multilingual NLP
We develop NLP solutions for German, Italian, Polish, English, and mixed-language content. We handle tokenization, entity recognition, and semantic matching across languages with regional business terminology.
Business Problems Our NLP Development Services Solve
We have thousands of documents but no way to search them effectively.
We build semantic search systems using embeddings and vector databases. Users find relevant content by asking natural questions, not by guessing keywords. We implement reranking, filtering, and faceted search for precision at scale.
We want to integrate LLMs but don't know where to start.
Our LLM integration services evaluate your use case, select the appropriate model (OpenAI, Claude, Llama, Mistral), and design the architecture: API, fine-tuning, or RAG. We handle prompt engineering, fall-back logic, and production monitoring so your LLM solution is reliable from day one.
Our team spends hours reading and categorizing documents.
We automate text classification, entity extraction, and sentiment analysis through custom NLP pipelines. Documents are automatically tagged, routed, and summarized — reducing manual review time while maintaining accuracy.
Customers ask the same questions, but our knowledge base is hard to navigate.
We build document chatbots that answer questions directly from your documentation. Users ask natural questions; the chatbot retrieves relevant passages, synthesizes answers, and provides source citations. No more frustrated customers lost in documentation hierarchies.
We need to analyze customer feedback, support tickets, or social media at scale.
We develop sentiment analysis, topic modeling, and intent detection systems that process thousands of text inputs automatically. You identify trends, flag issues, and prioritize responses based on data, not intuition.
We have thousands of documents but no way to search them effectively.
We build semantic search systems using embeddings and vector databases. Users find relevant content by asking natural questions, not by guessing keywords. We implement reranking, filtering, and faceted search for precision at scale.
We want to integrate LLMs but don't know where to start.
Our LLM integration services evaluate your use case, select the appropriate model (OpenAI, Claude, Llama, Mistral), and design the architecture: API, fine-tuning, or RAG. We handle prompt engineering, fall-back logic, and production monitoring so your LLM solution is reliable from day one.
Our team spends hours reading and categorizing documents.
We automate text classification, entity extraction, and sentiment analysis through custom NLP pipelines. Documents are automatically tagged, routed, and summarized — reducing manual review time while maintaining accuracy.
Customers ask the same questions, but our knowledge base is hard to navigate.
We build document chatbots that answer questions directly from your documentation. Users ask natural questions; the chatbot retrieves relevant passages, synthesizes answers, and provides source citations. No more frustrated customers lost in documentation hierarchies.
We need to analyze customer feedback, support tickets, or social media at scale.
We develop sentiment analysis, topic modeling, and intent detection systems that process thousands of text inputs automatically. You identify trends, flag issues, and prioritize responses based on data, not intuition.
Semantic Search with Embeddings
We implement vector search using embeddings from models like OpenAI, BERT, or domain-specific transformers. Documents are converted to vector representations that capture meaning, enabling similarity search, clustering, and recommendation across large text collections.
LLM Integration Architecture
We design LLM integration patterns that match your reliability, cost, and privacy requirements. Options include API-based access, fine-tuned models on your data, or private deployments using open-source models. We implement caching, rate limiting, and fallback chains for production stability.
Entity Extraction & Intent Detection
We build NLP pipelines that identify people, organizations, dates, and custom entities in your documents. We also detect user intent from queries, support tickets, and chat messages — enabling automated routing and response generation.
Knowledge Base & Semantic Matching
We connect NLP systems to your knowledge base through vector databases and graph structures. Semantic matching finds related concepts even when terminology differs, improving search recall and recommendation accuracy.
Text Summarization Pipelines
We implement extractive summarization (selecting key sentences) and abstractive summarization (generating concise paraphrases) for documents, conversations, and reports. Summaries maintain factual accuracy while reducing reading time.
Multilingual & Cross-Language Processing
We handle German, Italian, Polish, English, and mixed-language content with language detection, cross-lingual embeddings, and translation-aware processing. Regional business terminology and industry jargon are incorporated into custom models.
Example NLP & LLM Use Cases We Can Build
Legal Document Semantic Search
A Swiss law firm needs to search across thousands of contracts, court decisions, and legal opinions using natural language queries. We would build a semantic search system with embeddings, metadata filtering by jurisdiction and date, and source attribution for every result. Lawyers find relevant precedents faster without relying on exact keyword matches.
Multilingual Customer Support Classification
An Austrian e-commerce company receives support tickets in German, Italian, and English. We would develop an NLP pipeline that detects language, classifies intent (refund, technical issue, product question), extracts order numbers, and automatically routes tickets to the right team, reducing response time and improving routing accuracy.
Manufacturing Document Intelligence
A Polish industrial company has decades of maintenance manuals, safety protocols, and technical specifications in PDF format. We would build a document chatbot that answers technician questions, retrieves relevant procedures, and provides step-by-step guidance from approved documentation with full audit trails for compliance.
Financial Report Summarization
An Italian investment firm needs to quickly analyze earnings reports, market commentary, and regulatory filings. We would implement text summarization to extract key metrics, risk factors, and strategic updates from long documents, enabling analysts to review more reports in less time while maintaining consistent coverage.
Step 1: Text Audit & Use Case Discovery (Weeks 1–2)
01We analyze your text data sources, document formats, and user search patterns. We identify the highest-impact NLP opportunities: semantic search, document classification, chatbot integration, or text analytics.
NLP roadmap and data readiness assessment.
Step 2: Pipeline Design & Model Selection (Weeks 3–4)
02We design the text processing pipeline: tokenization, embedding, retrieval, and generation stages. We select models based on accuracy, speed, cost, and language requirements.
Pipeline architecture and model selection report.
Step 3: Knowledge Base & Vector Setup (Weeks 5–6)
03We process your documents into chunks, generate embeddings, and load them into vector databases (Pinecone, Weaviate, pgvector). We implement metadata filtering, reranking, and source tracking.
Searchable knowledge base with semantic retrieval.
Step 4: LLM Integration & Prompt Engineering (Weeks 7–9)
04We integrate the LLM layer with RAG, prompt templates, and output formatting. We test across edge cases, ambiguous queries, and adversarial inputs. Output: working NLP application with validated responses.
Step 5: Testing, Deployment & Monitoring (Weeks 10–12)
05We run user acceptance testing, measure search relevance and response quality, and deploy to production. We set up feedback loops for continuous improvement. Output: live NLP system with performance analytics.
Industries We Serve with NLP Development Services
We provide NLP development services for legal and compliance, e-commerce, manufacturing, healthcare, financial services, and media & publishing businesses that need smarter text search, document analysis, and workflow automation. From contract review and semantic search to multilingual product search, clinical documentation lookup, regulatory filing analysis, and automated content tagging, our NLP solutions help organizations improve accuracy, save time, and streamline operations across complex, text-heavy industries.
Contract analysis, precedent search, regulatory document review, compliance checking. Semantic search across legal databases with jurisdiction-aware filtering.
Product search, review analysis, support ticket classification, chatbot integration. Multilingual processing for cross-border commerce.
Technical documentation search, maintenance guides, safety protocol retrieval, quality report analysis. Domain-specific terminology and multilingual support.
Clinical documentation search, research literature analysis, patient communication support. GDPR-compliant handling with no diagnostic claims from AI.
Document analysis, report summarization, regulatory filing review, client communication drafting. Secure deployment with audit trails and human review.
Content categorization, automated tagging, summarization, translation support. Editorial workflow integration with human approval gates.
Why Businesses Choose Unisam for NLP & LLM Development
Businesses choose Unisam for NLP and LLM development because we build search-first, production-ready solutions that make documents, knowledge bases, and content easy to find and use. With source attribution, multilingual support, transparent ownership, and continuous optimization, our NLP services help businesses improve accuracy, trust, and efficiency across real world workflows.
Frequently Asked Questions About NLP & LLM Development
Start Your NLP or LLM Project with Unisam
Whether you need semantic search, document intelligence, or LLM integration, Unisam delivers NLP development services that work in production.
Tell us about your text data and use case. We reply within 24 hours with a scope document and approach or Schedule a 30-Minute NLP Discovery Call to discuss your project with our NLP team.
Legal & Compliance