Cylestio provides a Secure Agent Lifecycle platform that extends DevSecOps practices to AI agents, delivering continuous static analysis, dynamic runtime tracing, and session replay from development through production. It maps findings to OWASP LLM Top 10 controls, offers behavioral drift detection, risk scoring, and evidence‑based reporting, with an open‑source core and enterprise features for governance, monitoring, and compliance.
Funding
Funding not disclosed
Founders
Product
Problem
AI agents make autonomous decisions and evolve without code changes, making traditional deterministic DevSecOps tools ineffective. This unpredictability creates security, compliance, and operational risks that teams cannot reliably assess or mitigate.
Solution
Cylestio offers a Secure Agent Lifecycle platform that extends DevSecOps principles to AI agents. The platform provides continuous visibility from code authoring through production, capturing agent behavior, runtime traces, and risk metrics. Built-in OWASP LLM Top 10 compliance maps identified threats such as prompt injection and excessive agency to concrete remediation guidance. Developers receive session replay, time‑machine comparisons, and performance profiling, while security teams get behavioral baselines, anomaly detection, and evidence‑based reports. An open‑source core delivers full static and dynamic analysis for free, and an Enterprise tier adds deployment gates, runtime monitoring, approval workflows, and team‑level governance for production‑scale deployments.
Target Audience
Primary customers are AI agent developers and engineering teams who need to build trustworthy agents, and security or compliance teams in enterprises that must govern agent deployments at scale.
Features
- Full static code analysis and dynamic runtime tracing of AI agents, integrated via a local proxy
- Session replay and “Time Machine” comparison to debug and audit agent decisions over time
- Automatic mapping of findings to OWASP LLM Top 10 controls with remediation suggestions
- Behavioral clustering and drift detection to surface emergent risks as models evolve
- Risk scoring and evidence‑based reporting for developers, security officers, and executives
- Open‑source core (Apache 2.0) with no usage limits, installable via a single pipx command
- Enterprise extensions: deployment gates, runtime monitoring, alerting, approval workflows, RBAC, SSO, and centralized audit logging
- MCP integration for Claude Code, Cursor, and other AI agent frameworks