Jaxon's Domain-Specific AI Logic (DSAIL)

Trust Generative AI for Critical Applications

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Knowledge graphs tailored to

your domain-specific language

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Guardrails for new or existing

LLM pipelines

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Formal verification ensures

trusted output

AI guardrails impose user-defined constraints,
ensuring AI outputs remain accurate & relevant.

AI Has a Hallucination Problem

AI can generate information that’s incorrect, even though it might sound plausible. Large language models (LLMs) are just looking at patterns and need guardrails – enter Jaxon’s DSAIL.

 

AI Validation Agent

Jaxon’s patent-pending Domain-Specific AI Logic (DSAIL) platform has an interchangeable set of modules that provide Verification & Validation (V&V) guardrails for generative AI. DSAIL uses ‘formal methods’ to mathematically prove the accuracy of LLM output.

RAG is NOT Enough

RAG increases probability of accurate response with no assurances
for that, you need Jaxon.


For high-risk industries, where accuracy is crucial, RAG is NOT enough.

Jaxon takes RAG to new levels of accuracy and trust with mathematical proof.

Jaxon allows users to select the ‘LLM guardrail’ that fits their organizational needs best on a scale of degree of formality vs degree of trustworthiness. 

Choosing Guardrails

The Image Description Fact Checker

DSAIL’s ‘Fact Checker’ is at the heart of addressing the hallucination problem. Jaxon’s proprietary DSAIL technology turns natural language into binary that gets run through a gauntlet of checks and balances. This ensures the AI’s response meets all constraints and assertions before being returned – formal verification of its output.

Verification & Validation

Verification confirms that a model operates correctly in real-world conditions, while validation ensures the model accurately represents its intended use. The DSAIL platform provides a set of guardrails to make sure AI systems stay on track and produce accurate responses. 

Jaxon’s DSAIL: Tackling AI Hallucinations

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