LeoTrace is a security decision layer for AI-generated code, designed to identify dangerous assumptions and capture human security reasoning throughout the software development lifecycle. The platform extracts security intelligence from decisions made by both developers and AI agents, enabling safer AI-assisted software delivery. It is currently in early access, targeting teams that need to maintain security oversight in AI-driven development workflows.
Funding
Funding not disclosed
Founders
Product
Problem
As AI agents increasingly generate code, they can introduce security vulnerabilities based on flawed assumptions or incomplete context. Development teams lack a systematic way to capture and apply human security reasoning to AI-generated output, creating risk in the software delivery pipeline.
Solution
LeoTrace provides a security decision layer that sits between AI code generation and deployment, extracting security intelligence from the decisions made by both developers and AI agents. The platform identifies dangerous assumptions in AI-generated code and captures the human security reasoning that informs safe corrections. This creates a reusable knowledge base of security decisions that can guide future AI code generation and review processes. By making security reasoning explicit and traceable, LeoTrace enables organizations to maintain security standards while accelerating AI-assisted development.
Target Audience
Primary customers are software engineering teams and security organizations that use AI code generation tools and need to maintain security oversight without slowing down development velocity.
Features
- Security intelligence extraction from developer and AI agent decision-making processes
- Identification of dangerous assumptions embedded in AI-generated code
- Capture and codification of human security reasoning for reuse across projects
- Decision-layer integration that works alongside existing AI code generation tools
- Traceability of security decisions for audit and compliance purposes