An Intellyx Brain Candy Brief
SafeLiShare secures LLM vector transformations to prevent corruption and data theft and to ensure reliable results.
SafeLiShare constructs secure pipelines using encryption, secure processing, and cloud provider secure enclaves.
Their solution focuses on preventing issues that can occur when submitting and processing data to train LLM models, so that customers can be confident of the results of the training.
Corrupt data input, for example, is a common issue that can occur during transformations. Poorly curated and managed data can cause hallucinations. Unsecured RAG processing can also produce incorrect or inaccurate responses to prompts.
SafeLiShare forks customer data pipelines to isolate and protect them so their customers can trust that their transformation results do not suffer from any of these common issues.
SafeLiShare runs on Azure and AWS supports secure enclaves for processors from Intel and AMD. GPU support is in development.
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