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
Policy Rules Guardrail
An AI guardrail that turns complex policy docs into structured logic.
Discover How
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 Language (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
Jaxon teams up with IBM watsonx in battle against AI hallucination
Jaxon awarded Phase II SBIR contract with U.S. Air Force
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Art in the Age of Instant AI: What Do We Owe the Originals?
GPT-4o is the internet’s latest obsession – and rightly so. With just a prompt
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AI hallucinations occur because large language models (LLMs) like GPT generate text by predicting
The Power of Semantic Chunking in AI: Unlocking Contextual Understanding
In the evolving world of AI, semantic chunking has emerged as a powerful technique
