About Axiqual
We help engineering teams ship better AI prompts. Our deterministic Quality Engine gives you measurable, repeatable quality baselines for every prompt in your pipeline.
Our Mission
Prompt engineering is still treated as an art. We believe it should be measurable. Axiqual was built to give teams the same rigor for prompts that they already have for code: static analysis, automated testing, and CI/CD gating.
Our deterministic engine runs in the browser with zero server-side dependencies. Prompts never leave your machine during analysis, making it suitable for privacy-sensitive workflows in healthcare, finance, and legal AI applications.
We are committed to keeping the core prompt checker free and accessible to every developer. Quality prompt engineering should not be gated behind expensive enterprise contracts or proprietary tools. A solo developer building their first chatbot deserves the same quality assurance capabilities as a team at a Fortune 500 company.
Why We Built It
We saw engineering teams shipping prompts to production without any quality gating. The result was predictable: hallucination-prone responses, prompt injection vulnerabilities, PII leaks, and inconsistent user experiences. Traditional testing approaches didn't apply because prompts are neither code nor natural language alone.
Axiqual bridges that gap. We provide a structured evaluation framework that catches structural issues, security vulnerabilities, and quality regressions before they reach your users.
The idea started from a simple observation: every other part of the software development lifecycle has static analysis tools — linters for code, validators for HTML, security scanners for dependencies — but prompts had nothing. We built the first static analysis engine specifically designed for AI prompt templates.
How the Quality Engine Works
The Axiqual Quality Engine is a rule-based static analysis system. Unlike AI-powered review tools that send your prompts to an LLM for evaluation, our engine uses deterministic rules that run entirely in your browser. This means identical input always produces identical output — no model randomness, no API latency, and no data leaving your machine.
The engine evaluates prompts across six dimensions, each with its own set of pass/fail rules:
Prompt Structure (20%)
Checks role definitions, task clarity, formatting boundaries, output format specifications, and instruction completeness.
Memory & State (15%)
Evaluates conversation context management, state directives, and history handling instructions.
Context Grounding (20%)
Measures document references, retrieval parameters, variable placeholders, and citation usage.
Trust & Accuracy (25%)
Flags hallucination risks, conflicting instructions, speculative language, and consistency issues.
PII & Privacy (10%)
Detects email addresses, API key patterns, credential exposure, and data isolation issues.
Security & Safety (10%)
Scans for prompt injection vectors, jailbreak patterns, instruction lock bypass, and output boundary violations.
Analysis completes in under 10 milliseconds for typical prompts. The engine generates a detailed report with per-rule pass/fail results, severity levels, and specific fix suggestions for every issue detected.
Our Approach
Privacy First
All analysis happens in your browser. No prompt data is sent to external servers. Your intellectual property stays yours.
Deterministic by Default
Our rule engine produces the same result for the same input every time. No flaky tests, no model drift, no ambiguity in your CI pipeline.
Security Conscious
We detect prompt injection, jailbreak patterns, PII exposure, and system instruction leaks. Security is built into every analysis.
CI/CD Ready
CLI tools, REST API, GitHub Actions, and SDK support mean prompt quality checks fit naturally into your existing development workflow.
Who Uses Axiqual
Our tools are designed for anyone working with AI prompts, from individual developers to enterprise engineering organizations:
- AI Engineers & Prompt Engineers who need consistent prompt quality baselines and want to catch structural issues, injection vulnerabilities, and privacy risks before shipping to production.
- QA & Testing Teams integrating prompt quality gates into CI/CD pipelines. The deterministic engine runs thousands of checks daily without API costs or external dependencies.
- Security Teams auditing AI applications for prompt injection vulnerabilities, PII exposure risks, and jailbreak patterns in customer-facing prompt templates.
- Students & Researchers learning prompt engineering fundamentals. The six-dimension scoring framework provides concrete, actionable feedback on prompt structure and best practices.
Who's Behind Axiqual
Axiqual is an independently built and maintained project. Instead of marketing claims, we let our process speak — the entire build is documented openly and has been reviewed by external engineering audits and 130+ independent directories.
- Transparent build process: our architecture, engine internals, tech stack, and every engineering decision are published on the How It Was Built page — no black box.
- Externally audited: the codebase has been reviewed through dedicated engineering and front-end audits, and the project is independently listed across 130+ startup and AI directories including Shipstry, Launch List, and Verified Tools.
- Direct line to the maintainer: questions go straight to the person who ships the code via the contact form or [email protected].
- Verifiable by inspection: every tool runs client-side. Open your browser's network tab — prompts never leave your device, which is the strongest proof of how the product actually works.
Get in Touch
Have questions about integrating prompt quality checks into your workflow? We'd love to hear from you.