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Natural Language Processing Service

Natural Language Processing as A Service – Transforming Text into Intelligence

With extensive experience in building AI solutions, we implement Natural Language Processing using advanced computational linguistics and machine learning algorithms enhanced by contextual word embeddings. This enables computers to understand, interpret, process, and generate human language by structuring text, recognizing patterns, and extracting semantic meaning.

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Natural Language Processing Solutions

We apply AI algorithms that learn complex linguistic patterns, context, and semantic relationships through techniques like intent classification and pragmatic analysis across various language-related tasks. VOLTERA team uses advanced machine learning, deep learning techniques, and transformer-based neural network architectures to integrate neural language models into the NLP pipeline.

01 Build NLP Models

Advanced NLP model development creates sophisticated AI systems that can comprehend, generate, and analyze human language through deep learning neural networks trained on massive multilingual datasets. We use architectures like transformers and BERT to capture nuanced linguistic contexts.

02 Create AI Assistants

Conversational AI systems create intelligent chatbots and virtual agents capable of understanding user intent, context, and sentiment. They leverage dialog management and natural language understanding (NLU) techniques to deliver human-like interactive experiences across multiple communication channels.

03 Analyze Text Insights

Text analysis and sentiment detection extract emotional tone, opinion, and underlying meaning from textual data by applying machine learning classifiers and text mining algorithms that combine sentiment analysis and discourse processing.

04 Enable Global Communication

Machine translation platforms and multilingual NLP frameworks use neural models with transformer architectures, transfer learning, and cross-lingual embeddings to translate and process multiple languages. They preserve semantic meaning and grammatical nuances, enabling seamless global communication and adaptable language processing.

05 Automate Document Processing

Intelligent document processing automatically extracts, categorizes, and structures information from complex documents. It uses optical character recognition (OCR), entity recognition, and machine learning algorithms to transform unstructured text into actionable data.

06 Transcribe Voice Data

Speech recognition solutions convert spoken language into machine-readable text using deep neural networks. They analyze acoustic signals, phonetic patterns, and contextual language models to accurately transcribe and interpret human speech.

07 Enhance Information Retrieval

Semantic search engines use advanced NLP techniques to understand user query context, intent, and meaning, going beyond keyword matching. They provide more relevant and contextually appropriate search results.

08 Generate Dynamic Content

Automated content generation leverages large language models to create human-like text by predicting and generating contextually relevant sentences through advanced techniques in language generation.

09 Customize Language Understanding

Custom language understanding models create specialized NLP systems tailored to specific industry or domain requirements. The models use transfer learning, fine-tuning, and domain-specific training data for precise linguistic comprehension.

Natural Language Processing Service in Industries

We provide advanced language processing technologies across industries to solve complex domain-specific challenges by extracting meaningful information, automating repetitive tasks, and providing intelligent, context-aware solutions.

Finance: Market Sentiment

  • Analyzes financial news, social media, and market reports to gauge investor sentiment
  • Predicts market trends by processing textual data from multiple financial sources
  • Provides real-time insights into potential market movements and investment opportunities
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Healthcare: Medical Insights

  • Converts unstructured medical records into structured, machine-readable formats
  • Extracts patient diagnoses, treatment plans, and medical histories with high accuracy
  • Supports clinical decision-making by identifying patterns and potential medical insights
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Legal: Contract Intelligence

  • Automatically extracts key clauses, terms, and potential risks from legal documents
  • Uses named entity recognition and semantic analysis to identify critical contract components
  • Reduces manual review time and enhances compliance by flagging legal inconsistencies
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Natural Language Processing in Customer Service

  • Develops AI-powered chatbots that understand and respond to customer queries
  • Provides 24/7 support with context-aware and personalized communication
  • Routes complex issues to human agents while handling routine inquiries efficiently
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E-commerce: Product Analysis

  • Analyzes customer product reviews to understand sentiment and product performance
  • Identifies key product features, strengths, and potential improvement areas
  • Monitors competitor products, pricing, and customer feedback to inform competitive strategies
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Media: Content Classification

  • Automatically categorizes and tags media content for easier recommendation
  • Analyzes content themes, sentiment, and relevance across different media platforms
  • Enhances content discovery and personalization for users
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HR: Talent Matching

  • Screens and matches resume with job requirements using advanced parsing techniques
  • Identifies candidate skills, experience, and potential cultural fit
  • Reduces bias in recruitment by focusing on objective skill-matching
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Education: Personalized Learning

  • Develops learning systems that customize educational content to individual student needs
  • Analyzes student performance, learning patterns, and comprehension levels
  • Creates personalized learning paths and provides targeted educational interventions
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Research: Literature Analysis

  • Automatically processes and summarizes large volumes of academic literature
  • Identifies research trends, connections between studies, and knowledge gaps
  • Accelerates literature review and helps researchers discover new insights
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Telecommunications: Call Optimization

  • Analyzes customer call transcripts to improve service quality and efficiency
  • Provides real-time insights into customer issues and agent performance
  • Develops intelligent routing and recommendation systems for call center interactions
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Struggling with inefficient document processing?

Streamline operations and save costs with intelligent text automation powered by NLP.
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Driving Innovation with AI: Success Stories from Voltera

Check out a few case studies that show why VOLTERA will meet your business needs.

Healthcare
Data Science
Data Insights & Forecasting

Stock relocation solution

The client was faced with the challenge of creating an optimal assortment list for more than 2,000 drugstores located in 30 different regions. They turned to us for a solution. We used a mathematical model and AI algorithms that considered location, housing density and proximity to key locations to determine an optimal assortment list for each store. By integrating with POS terminals, we were able to improve sales and help the client to streamline its product offerings.

 

10% productivity boost 7% increase in sales
Mark S.

Mark S.

Partner Pharmacy network,

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Stock relocation solution
Data Science
Sales automation
Data Insights & Forecasting

Client Identification

The client wanted to provide the highest quality service to its customers. To achieve this, they needed to find the best way to collect information about customer preferences and build an optimal tracking system for customer behavior. To solve this challenge, we built a recommendation and customer behavior tracking system using advanced analytics, Face Recognition, Computer Vision, and AI technologies. This system helped the club staff to build customer loyalty and create a top-notch experience for their customers.

5% customer retention boost 25% profit growth
Christopher Loss

Christopher Loss

CEO Dayrize Co, Restaurant chain,

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Client Identification
Retail
Sales automation
Data Engineering

Performance Measurement

The Retail company struggled with controlling sales and monitoring employees’ performance. We implemented a software solution that tracks sales, customer service, and employee performance in real-time. The system also provides recommendations for improvements, helping the company increase profits and improve customer service.

17% increase in sales 15% revenue boost
Amir R.

Amir R.

CEO, CEO Fashion Retailer

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Performance Measurement
Retail
Supply-chain automation
Web and mobile development

Supply chain dashboard

The client needed to optimize the work of employees by building a data source integration and reporting system to use at different management levels. Ultimately, we developed a system that unifies relevant data from all sources and stores them in a structured form, which saves more than 900 hours of manual work monthly.

900h+ manual work reduced 100+ system integrations
Michelle Nguyen

Michelle Nguyen

Senior Supply Chain Transformation Manager Unilever, World’s Largest Consumer Goods Company

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Supply chain dashboard
Would you like to explore more of our cases?
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Digital Transformation Consulting Firm’s Technologies

Pandas

SciPy

TensorFlow

Numpy

ADTK

DBscan

G. AutoML

Keras

MLFlow

Natural L. AI

NLTK

OpenCV

Pillow

PyOD

PyTorch

FB Prophet

SageMaker

Scikit-learn

SpaCy

XGBoost

YOLO

Don’t let language barriers slow your growth.

Scale globally with multilingual NLP solutions!

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Natural Language Processing Service Process

These steps form a continuous pipeline that transforms raw text into actionable insights through progressive levels of understanding and processing, each step building upon the previous one’s output.
How do we help companies?

Text Acquisition & Preprocessing

Raw text data is collected, cleaned, standardized, and broken down into processable units through tokenization and normalization techniques.

01

Linguistic Analysis

The text undergoes structural analysis to identify grammatical elements, sentence structure, and parts of speech using linguistic rules and patterns.

02

Semantic Processing

The system extracts meaning by identifying entities, relationships, and contextual information within the processed text.

03

Feature Engineering

Text is transformed into numerical representations and vectors that machines can process effectively.

04

Model Development

Machine learning models are selected, trained, and optimized using the engineered features to perform specific NLP tasks.

05

Output Generation

The system produces the desired output — translated text, generated content, or extracted insights.

06

Users' Feedback

Deploying prototype to select user groups and gather comprehensive insights.

06

Performance Evaluation

Results are measured against quality metrics and benchmarks to assess accuracy and identify areas for improvement.

07

Users' Feedback

Deploying prototype to select user groups and gather comprehensive insights.

06

Integration & Deployment

The validated NLP solution is integrated into existing systems and deployed for real-world applications.

08

Users' Feedback

Deploying prototype to select user groups and gather comprehensive insights.

06

Challenges Resolved with Natural Language Processing Service

VOLTERA implements large language models (LLMs) with transformer architectures, which excel at understanding context and processing natural language at scale. These models, combined with transfer learning and fine-tuning capabilities, tackle multiple language-related challenges.

Manual Text Processing Inefficiencies

Automated text processing pipelines with pre-trained models

Inconsistent Customer Interaction

Standardized AI-powered chatbots and response systems

Information Overload

Smart content summarization and prioritization algorithms

Language Barriers

Real-time neural machine translation systems

Manual Text Processing Inefficiencies

Automated text processing pipelines with pre-trained models

Inconsistent Customer Interaction

Standardized AI-powered chatbots and response systems

Information Overload

Smart content summarization and prioritization algorithms

Language Barriers

Real-time neural machine translation systems

Possibilities of Natural Language Processing as A Service

These benefits enable systems to move beyond simple pattern matching to comprehend context, semantics, and linguistic subtleties, transforming text into insights through computational techniques.

Transforming Unstructured Text

NLP algorithms convert complex, unorganized textual data into meaningful, structured information that can be directly used for strategic decision-making across various domains.

Automating Customer Communication

Advanced NLP systems create intelligent communication platforms that understand, process, and respond to customer queries in real-time.

Enhanced Information Extraction

Sophisticated NLP techniques automatically identify, categorize, and extract critical information from large volumes of text, pulling out key entities, relationships, and contextual details.

Chatbot and Virtual Assistant Development

NLP enables the creation of context-aware conversational agents that understand user intent, provide personalized responses, and simulate human-like interactions across multiple platforms.

Cross-Lingual Content Analysis

Advanced language models can analyze and compare content across different languages, breaking down linguistic barriers and providing comprehensive insights from global sources.

Understanding of Complex Documents

NLP algorithms deeply comprehend the meaning, context, and nuanced implications within complex documents, going beyond surface-level text interpretation.

Summarization and Content Classification

Intelligent systems can automatically generate concise summaries of lengthy documents and categorize content based on sophisticated linguistic and contextual analysis.

Voice Interface Development

NLP technologies transform spoken language into actionable commands, enabling more natural and intuitive human-computer interactions through advanced speech recognition.

Predictive Text and Autocomplete Systems

Machine learning models predict and suggest text completions by understanding context, writing style, and user behavior patterns.

Advanced Linguistic Pattern Recognition

Sophisticated NLP techniques identify complex linguistic structures, grammatical patterns, and semantic relationships across different textual data types.

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FAQ

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