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PAR Technology builds secure LLM analytics for restaurants with multi-layer security

PAR Technology Corporation has developed a multi-tenant LLM analytics system designed for the restaurant industry, enabling business users to query data in natural language. The system addresses the critical challenge of row-level security, ensuring that each user only accesses data relevant to their specific business or role. This is achieved through a three-layer architecture that includes cryptographic request signing, semantic validation via Amazon Bedrock, and programmatic data isolation using Split-Plane SQL, thereby mitigating risks even if the LLM is compromised. AI

IMPACT Demonstrates a practical application of LLMs for secure data analytics in a specific industry, highlighting solutions for data governance challenges.

RANK_REASON Article describes a specific product/system built by a company using AI tools, not a core AI release or research.

Read on AWS Machine Learning Blog →

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PAR Technology builds secure LLM analytics for restaurants with multi-layer security

COVERAGE [1]

  1. AWS Machine Learning Blog TIER_1 English(EN) · Anuranjan Mondal ·

    Multi-tenant LLM analytics with row-level security: How we built a secure agent on AWS

    In this post, we show you how PAR built a production-ready multi-tenant LLM analytics system that enforces row-level security through a three-layer architecture: cryptographic request signing with AWS SigV4, semantic validation on Amazon Bedrock, and programmatic data isolation v…