Codenotary announced AgentMon Start, a purpose-built release of its AI agent monitoring platform for small and mid-sized businesses that provides visibility into how autonomous AI agents operate in their software development organization, without requiring a dedicated security team or cloud-based deployment.
The agentic monitor system provides the ability to see, investigate and govern what autonomous AI agents are actually doing in software development, and understand where the token spend goes.
The platform enables existing IT, development, and security teams to understand AI agent behavior, investigate anomalies, enforce governance policies, and maintain compliance as AI adoption accelerates. Also, AgentMon Start reports on token spend providing organizations with insight into their AI budget.
“While corporations have the ability to set up AI governance teams, security operations centers and specialized observability infrastructure, non-enterprise organizations often cannot,” said Moshe Bar, CEO and co-founder, Codenotary. “That leaves a visibility gap, yet AI agents used by smaller organizations have access to many of the same sensitive systems, credentials, customer records and source code, and generate substantial cost.”
AgentMon Start closes that gap by providing continuous monitoring, investigation capabilities, governance controls, and cost visibility for AI agents operating throughout the organization.
AgentMon Start is for organizations that want comprehensive AI oversight without deploying complex SaaS infrastructure or building dedicated AI security teams. No cloud account is required. AI activity remains within the organization's network.
AgentMon provides unified monitoring across more than 16 AI agent and large language models (LLMs), including Claude, Codex, Cursor, Gemini CLI, GitHub Copilot, Goose, Groq, KiloCode, Kiro, Ollama, and Roo Code.
AgentMon Start provides visibility across four areas.
- Cost management - Token consumption tracking, model usage, developer activity, session history, and AI spending across teams that enable organizations to identify unusually expensive usage, compare AI tools, establish budgets, and optimize AI operating costs.
- Security and agent behavior - The platform identifies secrets appearing in prompts, monitors files accessed or modified by AI agents, detects potential prompt injection attempts, identifies unauthorized AI tools, and maintains an audit trail of agent activity.
- Incident Investigation - When AI agents behave unexpectedly, organizations can review reasoning replay, execution traces, and search activity logs to understand exactly what occurred, eliminating the need to reconstruct incidents from fragmented application logs.
- Governance and shadow AI detection - Organizations gain visibility into which AI tools employees are actually using while applying consistent governance policies and guardrails across approved and unauthorized AI applications.
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