Natural language security queries at Orca Security using Amazon Bedrock
- Who
- AWS
- What
- shares an architecture and production results Orca Security’s natural language query agent Discovery AI on Amazon Bedrock
- Quote
In this post, we share the architecture and results of Discovery AI, which converts a natural language question into a Sonar query.
What happened
Orca Security partnered with AWS to build Discovery AI on Amazon Bedrock, translating natural language questions into validated Sonar queries across 900+ cloud infrastructure and application models. The architecture combines example retrieval and reranking, relevant schema selection, agentic generation, and validation, with domain experts continuously updating the example bank. Compared with its initial baseline, Orca reports 90 percent lower costs, 93 percent fewer input tokens, and 75 percent lower latency, with response times falling from approximately 60 seconds to 15 seconds.
Why it matters
The architecture offers a transferable approach to querying large schemas by retrieving validated examples, selecting relevant schema fragments, and feeding validation errors back into generation.
The story so far
Orca Security partnered with AWS to build Discovery AI on Amazon Bedrock, converting natural language security questions into validated Sonar queries across more than 900 cloud infrastructure and application models. Orca reports that, compared with its initial baseline, the system reduced costs by 90 percent, input tokens by 93 percent and latency by 75 percent, with response times falling from approximately 60 seconds to 15 seconds. The architecture retrieves and reranks example queries, selects relevant schemas, generates queries through an agentic process and validates the results. Domain experts continuously update the example bank used to guide query generation.
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