AI is rapidly accelerating the production of software. Developers and AI agents can now generate code faster than organisations can fully evaluate through authorship alone.

Yet security failures rarely originate from syntax errors. They arise from dangerous assumptions made during development, decisions about trust boundaries, data handling, authentication, and operational behaviour.

Today’s security tooling focuses on identifying what is wrong in code.

<> Vulnerabilities

<> Misconfigurations

<> Insecure patterns

But the real source of risk is often why those decisions were made in the first place.

As AI-generated code increases, organisations must scale secure decision-making across developers and autonomous agents.

The next step in software security is capturing the reasoning behind those decisions.

LeoTrace exists to make those decisions visible, measurable, and continuously improving.

Enabling organisations to scale AI-generated software while maintaining audit and regulatory confidence.

AI is rapidly accelerating the production of software. Developers and AI agents can now generate code faster than organisations can fully evaluate through authorship alone. Yet security failures rarely originate from syntax errors.

They arise from dangerous assumptions made during development, decisions about trust boundaries, data handling, authentication, and operational behaviour.