Natural language processing consulting & implementation

Tapping into unstructured data—text, voice, audio, images, videos—to enhance enterprise insight discovery, analytics, and decision making

Gain better insights from your unstructured data

Natural Language Processing (NLP) is being integrated into our daily lives with virtual assistants like Siri, Alexa, or Google Home. In the enterprise world, NLP has become essential for businesses to gain a competitive edge. Consider the valuable insights hidden in your enterprise
unstructured data—text, email, social media, videos, customer reviews, reports, etc. NLP applications are a game changer, helping enterprises analyze and extract value from this unstructured data.

At the Search & Content Analytics practice of Accenture Applied Intelligence, we focus on delivering Natural Language Processing consulting and implementation services that help enterprises leverage unstructured data to transform outcomes across industries and business functions.

Extracting insights from unstructured data has been difficult. But with natural language processing and machine learning, this is changing fast.

Example natural language processing applications

Question-answer systems

Enhance enterprise knowledge management and discovery by providing employees with natural language responses generated from data from multiple sources.

Intelligent document analysis

Combine NLP and machine learning (ML) to help gain insights into human-generated, natural language text documents.

Business chatbots and virtual assistants

Answer support queries and direct users to manuals or other resources, helping enterprises reduce support costs and improve customer engagement.

E-commerce product recommendations

Improve search relevancy, provide targeted responses, and deliver personalized results based on the user’s query intent.

Sentiment analysis and market intelligence

Mine social media, reviews, news, and other relevant sources to gain better insights about customers, partners, competitors, and market trends.

Fraud detection and risk management

Identify potential fraud and risk by analyzing financial and contract documents as well as specific communications.

Storage optimization analytics

Provide visibility into enterprise data storage and reduce costs by removing or migrating stale and obsolete content.

Natural resources exploration

Extract information from historical documents, reports, maps, notes, etc., to support business operations and new explorations.

Pharmaceutical research and manufacturing

Extract insights from research and trials reports to accelerate drug discovery and improve manufacturing processes.

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Experienced natural language processing consultants

Whether you’re looking to implement your first NLP application or improve an existing one, our NLP consulting and implementation services can be tailored to your project requirements. We leverage deep NLP and data science expertise to bring:

Strategic consulting, implementation, support 

Assessment, project planning, architectural design, implementation, and support for your NLP application.

A new R&D initiative for a scalable NLU framework

A scalable, maintainable NLP/NLU framework supporting content understanding and query interpretation to deliver better insights and user experience.

User interface development

Custom, enhanced user interface for a unified natural language search and analytics experience.

Machine learning and knowledge graphs

Integration with AI technologies and knowledge graphs to improve accuracy, relevancy, and automation.

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Common natural language processing techniques

We implement NLP techniques to understand both the user’s natural language query and the enterprise’s content to deliver the most relevant insights.

Raw language processing
As raw data varies from different sources, we bring content processing services to ensure your data is enriched for the highest-quality results. 

  • Extract text content
  • Remove common, irrelevant sections
  • Extract coded metadata
  • Token extraction, normalization, and cleansing
  • Phrase extraction

Text mining and text extraction
Often, the natural language content is not conveniently tagged. Text mining, text extraction, or possibly full-up NLP can be used to extract useful insights from this content.

  • Entity extraction – such as companies, people, locations, etc.
  • Content categorization – to conduct sentiment analysis
  • Content clustering – to identify the main topics and discover new topics
  • Fact extraction – to fill databases with structured information for analysis, visualization, and alerting
  • Relationship extraction – to fill out graph databases to explore real-world relationships

Statistical language processing
To provide a general understanding of the document as a whole.

  • Clustering
  • Categorization
  • Similarity
  • Topic analysis
  • Word clouds
  • Summarization

Innovations

We continuously refine our NLP techniques to support more complex enterprise requirements. Applying advanced NLP and other AI methods, we are exploring innovative use cases, such as:

Question matching

Match the question to a curated FAQ list or previously-answered questions database.

Document understanding

Read and interpret highly-curated content, such as documentation and specifications.

Procedure understanding

Read and convert written procedures into knowledge graphs for faster, more robust insight discovery.

Knowledge graph answers

Used to generate answers from curated, structured information.

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