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GigaSpaces eRAG
The intelligent GenAI teammate that understands your business data

What is GigaSpaces eRAG?

GigaSpaces eRAG is an enterprise-grade AI solution designed to bridge the gap between generative AI capabilities and business operational data. It functions as an intelligent teammate that learns organizational context and data structures to answer complex, cross-system questions instantly. The platform enables users to interact with their data using natural language, transforming questions into SQL queries without requiring technical expertise.

The solution deploys safely within 2-3 weeks without extensive data pipelines or preparation, maintaining data security by keeping information in place without movement or duplication. eRAG supports decision-making by challenging assumptions, validating choices, and suggesting next steps while providing governed access to operational data across the organization. It integrates with multiple data sources and offers proactive AI governance to ensure compliance and security.

Features

  • Semantic Reasoning: Understands business context and data relationships for accurate insights
  • Natural Language to SQL: Transforms conversational questions into database queries without technical knowledge
  • Multiple Data Source Integration: Connects to various enterprise databases and applications simultaneously
  • Proactive AI Governance: Ensures compliance and security with built-in governance controls
  • No Data Movement: Keeps data in place without ETL processes or duplication for enhanced security
  • Rapid Deployment: SaaS implementation completes in 2-3 weeks without extensive preparation

Use Cases

  • Procurement optimization and supplier analysis
  • Sales operations performance tracking and forecasting
  • Budget management and financial oversight
  • Operations monitoring and efficiency improvement
  • Customer 360-degree view creation and analysis
  • Cross-system business intelligence queries
  • Regulatory compliance and governance reporting
  • Strategic decision support with what-if scenarios

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