PAR Technology has built a secure multi-tenant analytics system on AWS that uses row-level security. This solution allows business users to perform self-serve analytics without exposing sensitive data across tenants, addressing the complex challenge of data access and correctness.
PAR Technology Corporation has created a natural language text-to-SQL agent for self-serve analytics targeting the restaurant industry. The solution allows users to query data in plain English and receive quick, reliable answers. To achieve this, the system addresses significant challenges related to security, correctness, and user data isolation.
The analytics system utilizes a three-layer architecture that includes cryptographic request signing with AWS SigV4, semantic validation via Amazon Bedrock, and programmatic data isolation through Split-Plane SQL. This layered approach reduces the risk of cross-tenant data exposure, even in case of a security breach affecting the LLM itself.
A critical challenge faced by the analytics agent is ensuring that each query generated is accurate and relevant to the user’s specific permissions. For instance, two users asking the same question about total sales will receive different data based on their operational context—one reflecting localized results and the other a national aggregate. Maintaining these distinctions is essential for data governance and security.
The system is designed to handle thousands of simultaneous users connected to various datasets and permission levels. Each user's query must be precisely scoped to ensure that sensitive information is not inadvertently shared. This design is vital for maintaining trust and compliance within a multi-tenant environment.
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PAR Technology has built a secure multi-tenant analytics system on AWS that uses row-level security. This solution allows business users to perform self-serve analytics without exposing sensitive data across tenants, addressing the complex challenge of data access and correctness.