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Saga Natural Language Understanding (NLU) Framework

Extracting insights from natural language content

Saga Natural Language Understanding (NLU) Framework

Filling the gaps in natural language processing systems

User interface

Business-friendly, code-free user interfaces for creating and maintaining language models for a wide range of enterprise NLP/NLU use cases

Cost

Automated NLU pipeline construction and management which substantially reduces development costs and provides predictable cost of ownership

Deployment

Flexible, scalable deployments on-premises or in the cloud

Innovation

State-of-the-art handling of language ambiguity

Ease of integration

Integrated machine learning with many prepackaged models available out-of-the-box

AI readiness

Extensible with machine learning and knowledge graph technologies

Saga Natural Language Understanding benefits

NLU capabilities are powered by both Patterns Matching (for precision and ease of editing) and Machine Learning (for broad coverage and automatic learning).

Patterns are simple to understand, accurate, quick to show value, and work best when no training data is available. NLP output with business object IDs can be easily integrated into business actions.

The process of testing and deploying Machine Learning and language models is easily done and managed by non-data scientists as it does not require coding.

Non-data scientists can perform 95 percent of the NLP/NLU work, providing “ready-to-go” data for data scientists to focus on creating better models.

Enterprises have full control over solution performance, deployment, and cost predictability.

Multiple NLP development efforts, algorithms, and language resources are managed and coordinated centrally within the Saga framework.

Example natural language understanding use cases

Our leaders

John Matchette

Senior Managing Director – Strategy and Consulting, Supply Chain and Operations, Data and AI Solutions Lead

Paul Nelson​

Innovation Lead – Accenture Applied Intelligence

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