Policy Rules Guardrails

Ensuring AI stays accountable, accurate, and aligned with user-defined rules.

AI is powerful, but how do you know it’s following the rules?

Large Language Models (LLMs) are powerful but often unreliable, fabricating information in ways that undermine trust and keep organizations from being able to use it. Jaxon’s Domain-Specific AI Logic (DSAIL) combines AI’s creativity with rigorous logical reasoning to ensure outputs are accurate, transparent, and policy-aligned.

What Are Policy Rules Guardrails?

Created in DSAIL, Policy Rules Guardrails are structured rules that ensure AI outputs align with domain-specific policies. Unlike Retrieval-Augmented Generation (RAG) systems, which rely on external knowledge sources, Jaxon’s approach structures AI outputs into deterministic, verifiable logic.

Enhances trust in AI decision-making and reduces reliance on brittle retrieval strategies.

Allows automated verification of AI-generated content.

Converts natural language into code, a domain-specific language (DSL).

DSL Display

What's a Domain-Specific Language?

A Domain-Specific Language (DSL) is a type of computer language specialized to a particular application domain. Instead of having a general programming language that can do a million different things, a DSL is designed to do one specific thing really well.

How Does it Work?

Jaxon’s policy rules guardrails work by turning natural language rules into structured, verifiable logic (configuration time) that keeps AI systems accountable (inference time).

Configuration Time 3-Step Process

Configuration Time is the process by which a Policy Rules Guardrail is generated. This defines the specific Policy Rule Guardrail which is then applied each time the AI is used to make a decision (Inference Time).

Define Rules – AI distills a policy document into a bullet-point set of rules in natural language.
Generate Code – These rules are converted into a domain-specific language (DSL), ensuring they are machine-readable and enforceable.
Extract Questions – The DSL program generates an ontology of structured questions that guide AI verification at inference time.

Example Configuration

In this example, we look at how the AI parses information on Unsatisfied Debts to create a set of natural language questions showing how the AI verified it’s decision.

Step 1:
Define Rules

Unsatisifed Debts

Evidence of failing to pay debts as agreed.
Mitigations: Older than 3 years or reason (job loss, medical, death, divorce, business downturn, separation).

Step 2:
Generate Code

declare delinquentDebtsNewerThan3Years as boolean;
// Mitigations; we default to false unless they are explicitly provided
declare delinquentDebtsReasonLossOfEmployment as boolean;
let delinquentDebtsReasonLossOfEmployment = False;
declare delinquentDebtsReasonMedicalEmergency as boolean;
let delinquentDebtsReasonMedicalEmergency = False;
declare delinquentDebtsReasonDeath as boolean;
let delinquentDebtsReasonDeath = False;
declare delinquentDebtsReasonDivorce as boolean;
let delinquentDebtsReasonDivorce = False;

Step 3:
Extract Questions

Are the delinquent debts newer than 3 years?

Was loss of employment the reason for the delinquent debts?

Was a medical emergency the reason for the delinquent debts?

Was death the reason for the delinquent debts?

Was divorce the reason for the delinquent debts?

Inference Time 3-Step Process

At Inference time, you use your LLM as you normally would and then DSAIL applies configured rules to automate policy enforcement at every stage. The Policy Rules Guardrail ensures AI decisions are transparent, reliable, and aligned with your rules.

Extract Answers – AI answers the questions generated at configuration time, ensuring structured data extraction.
Enrich DSL Rules – Answers are assigned to the variables present in the existing DSL program, completing the logic for evaluation.
Evaluate DSL Program – The DSL program is evaluated by the underlying SMT solver, verifying accuracy, and flagging violations transparently.

Example Inference

In this example, a synthetic Credit Bureau Report text chunk is analyzed using verification questions to ensure accuracy and detect rule violations.

Step 1:
Extract Answers

Step 2:
Enrich DSL Rules

Step 3:
Evaluate DSL Program

Industries That Benefit

Finance

Ensure AI-driven decisions comply with financial regulations.

Healthcare

Validate AI recommendations against medical guidelines.

Legal

Prevent AI from generating legally non-compliant content.

Government & Defense

Enforce strict policies in AI decision-making.

Not the Right Guardrail for You?

If you’re looking for an AI verification system that iterates, critiques, and refines its own responses, check out Agentic Guardrails — our adaptive AI framework designed for intelligent reasoning and self-improvement.

Keeping AI Accountable — So You Don’t Have To.

Key Benefits

Real-time enforcement of policies on AI-generated content.

Enhances transparency by making AI decisions traceable and auditable.

Future-proof architecture that evolves with regulations.

Minimizes hallucinations by structuring AI outputs into verifiable logic.

Seamless API integration into existing AI pipelines.

The Policy Guardrail is more than a compliance tool — it’s a scalable, adaptable AI governance framework. By integrating seamlessly with AI workflows, it ensures AI remains trustworthy, compliant, and aligned with evolving policies.

Take control with DSAIL and ensure AI plays by your rules.

RAG is NOT Enough