Trustworthy AI
Jaxon mathematically proves the output from LLMs is accurate. With a formal reasoning system, Jaxon ensures AI is predictable for use cases where the accuracy has to be trusted.
Rigorous Fact Checker with Domain-Specific Guardrails
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An AI-powered ‘Fact Checker’ to address the hallucination problem.
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Custom AI applications powered by Jaxon
Explore ServicesAddressing the Hallucination Problem
The propensity to “hallucinate” is inherent in LLM architectures. Jaxon’s proprietary Domain-Specific AI Logic (DSAIL) facilitates the formal expression of domain knowledge, constraints, and assertions, acting as a bridge between natural language and the structured language computational tools required for mathematical solving. Fact check LLM output with DSAIL to ensure accuracy.
- Assertions - Explicitly stated truths
- Constraints - Rules or limits that define the scope of possible solutions
- Facts - Predefined, true pieces of information the system uses as a base for reasoning and decision-making
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Featured News Stories
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Tools & Features
Jaxon's AI Agents Are Waiting to Assist You
Jaxon is equipped with a versatile toolbox designed to streamline your projects, offering a suite of tools and features accessible to users of all skill levels, ensuring that anyone can build trustworthy AI.
- Explore design tradeoffs
- Guide development
- Generate code
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The Limitations of the RAG Technique in Addressing Hallucinations in Large Language Models In
