BotGauge helps teams red-team, evaluate, monitor, and govern AI agents from development to production.
Agents call tools, touch sensitive data, and act with real autonomy, which means they fail in ways traditional checks were never built to catch. Prompt injection hidden in a document, a tool call nudged outside its intended scope, a multi-step reasoning chain steered into an unapproved outcome: these failures rarely show up from asking an agent a few sample questions.
BotGauge runs adaptive red-team campaigns against your live agent to surface these exact risks: prompt injection, unauthorized tool calls, data leakage through connected systems, and guardrail bypasses. Every finding becomes a permanent evaluation, added to your agent's regression suite so the same failure can't silently reappear in a future prompt tweak or model update.
Monitoring keeps watching after deploy, flagging drift and recurring failure patterns as models and tools change. Governance turns technical findings into clear, evidence-based guardrails and insight that engineering, security, and compliance stakeholders can actually act on, built from real attacks that worked, not generic policy templates.
BotGauge works with the frameworks teams are already shipping with, including LangGraph, CrewAI, AutoGen, and the OpenAI Agents SDK, plus MCP-connected agents. It's vendor-neutral and framework-agnostic by design, built to plug into your existing stack rather than lock you into one ecosystem.
Built for AI and ML engineering teams running agents in production who need ongoing red-teaming, durable evals, monitoring, and governance, not a one-time review.