AquilaX was founded by security engineers who got tired of noisy, expensive tools that developers learned to ignore. We spent years working inside the problem, and Securitron AI — trained on over 300 million real-world projects — is how we solved it.
The founders of AquilaX spent years working in security engineering across companies of all sizes. Everywhere they looked, the pattern was the same: tools generating thousands of false positives, developers who'd learned to tune out security alerts, and CISOs who genuinely couldn't tell whether their codebase was secure.
The root cause was always the same — security tools were built for auditors, not developers. They generated reports instead of fixes, and listed every vulnerability without helping anyone decide where to actually start.
AquilaX was built to change that. We built self-learning AI that understands your specific codebase — not a generic ruleset — alongside 32 scanners that cover every attack surface from a single platform. The result is a Security Rating that gives you one number instead of ten dashboards, with pricing that doesn't need a procurement conversation.
Not just enterprises with seven-figure security budgets, and not only teams with dedicated AppSec engineers on staff. Every team that ships software should be able to ship it securely — that's the goal, and it's why transparent pricing and a real free tier matter so much to us.
The values that guide how we build AquilaX
Security tools that developers hate don't make software more secure — they get ignored. We obsess over developer experience because, however good the underlying technology, adoption is the only metric that actually drives security outcomes.
Every false positive is a trust withdrawal from developers, and broken trust is incredibly hard to rebuild. We'd rather surface 10 real findings than 1,000 potential ones — therefore precision isn't just a feature, it's the whole point.
Pricing is on the website, AI decisions are explained in plain English, and our Trust Center is public. We don't believe in security through obscurity — and that goes for how our own product works too.
The threat landscape evolves daily, and our AI evolves with it. We're not shipping a static product — we're building a system that improves with every scan, every finding, and every merged fix.
We ship constantly, iterate quickly, and listen hard to customers who are securing real code under real constraints. Theory without practice is just theory — and we've always been builders first.
A startup in Lagos should have access to the same AppSec quality as a Fortune 500 in London. That's exactly why we built a genuinely useful free tier — not a hobbled demo designed to push people into a sales conversation.
Securitron AI builds a unique security model for your organization, not a one-size-fits-all ruleset. It learns your codebase, your stack, and your risk profile — and moreover, it gets sharper the more you use it.
SAST, SCA, DAST, Secrets, PII, Container, IaC, API, Malware, Vibe Code, Compliance — all running in parallel across a single platform. No tool sprawl, no fragmented dashboards, just one Security Rating that ties it all together.
A single 0–100 score per repository with full historical trending — boards understand it, developers can actively improve it, and CISOs can compare it across the entire portfolio.
Our pricing is on the website — start free with unlimited repos for authenticated users. There are no per-developer fees and no surprise invoices as your team scales. What you see is what you pay.
How we think about building AI-powered security responsibly
We'd rather find 95% of real vulnerabilities with near-zero false positives than find 99% with 50% noise. False positives destroy team trust, and once developers stop believing the alerts, you've essentially lost the security program.
Every finding includes a plain-English explanation of why it was flagged and exactly how to fix it. Black-box security tools don't build security knowledge in teams, however — ours does, because explainability is built in from the start.
Customer code is never used to train our shared models — per-organization learning stays entirely private. We're scanning your code to protect it, and that's where it stops.
AquilaX scans AquilaX — every commit goes through our own 32 scanners before it ships. We don't ask customers to trust something we wouldn't use ourselves.
Whether you're evaluating AquilaX, interested in joining the team, or just want to talk AppSec — we'd love to hear from you.