Checks every AI answer against your rules before anyone acts on it.
Turn policy into enforceable rulesHow it scores against RAG and LLMsConnect over MCP or RESTChecks a model still meets your standard after it changes.
Define what a correct output isHow a spec becomes an alertCompare model versions before releaseWe build and run the verified workflow when you lack the team.
What Jaxon builds for youFrom your use case to launchGuardrails, proof and human reviewThe same engine over MCP and REST, for chat and code.
Install and run DSAIL on your own infrastructure.
Getting started (documentation site)System requirements (documentation site)DSAIL language reference (documentation site)REST API (documentation site)Release notes (documentation site)How a ruleset is built, what a check returns, who can run it.
From policy text to a compiled ruleset (documentation site)How a check reports its result (documentation site)UNKNOWN is an answer (documentation site)No model in the loop (documentation site)Authentication and access control (documentation site)Threat model, access control and audit for a deployment, and the policies behind it.
Data handling (documentation site)Service Level AgreementAcceptable Use PolicyPrivacy PolicyTerms and ConditionsAnnouncements, articles and press releases.
Jaxon Awarded Phase I SBIR with U.S. Space Force (external site)Jaxon is Live on the AWS marketplace! (external site)Jaxon awarded phase III SBIR with U.S. Space Force (external site)Press inquiries: press@jaxon.aiChecks every AI answer against your rules before anyone acts on it.
Turn policy into enforceable rulesHow it scores against RAG and LLMsConnect over MCP or RESTChecks a model still meets your standard after it changes.
Define what a correct output isHow a spec becomes an alertCompare model versions before releaseWe build and run the verified workflow when you lack the team.
What Jaxon builds for youFrom your use case to launchGuardrails, proof and human reviewThe same engine over MCP and REST, for chat and code.
Install and run DSAIL on your own infrastructure.
Getting started (documentation site)System requirements (documentation site)DSAIL language reference (documentation site)REST API (documentation site)Release notes (documentation site)How a ruleset is built, what a check returns, who can run it.
From policy text to a compiled ruleset (documentation site)How a check reports its result (documentation site)UNKNOWN is an answer (documentation site)No model in the loop (documentation site)Authentication and access control (documentation site)Threat model, access control and audit for a deployment, and the policies behind it.
Data handling (documentation site)Service Level AgreementAcceptable Use PolicyPrivacy PolicyTerms and ConditionsAnnouncements, articles and press releases.
Jaxon Awarded Phase I SBIR with U.S. Space Force (external site)Jaxon is Live on the AWS marketplace! (external site)Jaxon awarded phase III SBIR with U.S. Space Force (external site)Press inquiries: press@jaxon.aiFirst in a series on how AI benchmarks are scored, and how to tell whether a vendor’s accuracy number means what you think it means. We start with the three metrics behind our own compliance benchmark.
When a document is missing the fact a rule depends on, most AI verification tools guess. Here’s what it looks like when the system returns UNKNOWN instead.
Four ways teams make AI follow a policy, and the two questions that show which one can prove it did.
How DSAIL checks a document against a policy over MCP without ever calling a language model.
Jaxon's DSAIL® (Domain-Specific AI Language) has been assessed "Awardable" through the Chief Digital and Artificial Intelligence Office (CDAO) Tradewinds Solutions Marketplace. The designation gives Department of War customers a direct…
Accuracy-as-a-Multiplier. Finance, operations, and transformation leaders talk a lot about enterprise artificial intelligence (AI) agents, automation, retrieval augmented generation (RAG), large language models (LLMs), and copilots. But the quiet determinant…
Why the Industry's Guardrails Fall Short and How Jaxon Is Redefining What Trust in AI Really Means In the rush to make large language models safe, trustworthy, and enterprise-ready, the…
Large language models (LLMs) are evolving fast, and companies need to know what’s out there, not just for capabilities, but for compliance, privacy, and fine-tuning potential. This post breaks down…
"Are you using semantics?" It's a fair question. The word gets thrown around a lot in AI, usually without much substance. So here’s a clear answer: yes—we use semantics, deeply and deliberately.…
At Jaxon, we believe flexibility is key to building trustworthy AI workflows. Whether you're analyzing financial compliance policies, assisting with Section 8 housing eligibility determinations, or supporting mission-critical decision-making in…
