Every agentic system fails at different boundaries.
Validate chatbots, voice agents, RAG applications, MCP servers and tools, internal agents, and autonomous workflows through the interfaces and permissions that shape their real impact.
AI system types
AI Chatbots & Copilots
Customer- and employee-facing chat surfaces are the most common entry point into an organization's AI systems — and the most directly exposed to adversarial input.
Learn more SolutionVoice Agents
Real-time voice and telephony agents inherit every text-based AI risk, plus failure modes unique to speech: transcription-layer injection, caller impersonation, and irreversible actions taken mid-call.
Learn more SolutionMCP Servers & Tools
Model Context Protocol servers look like ordinary backends from the outside, but the agent — not a human — decides which tool to call and with what arguments. That changes what needs testing.
Learn more SolutionInternal Enterprise Agents
Agents with access to internal systems — ticketing, infrastructure, databases, deployment tooling — carry the highest blast radius of any AI surface, and are usually the least tested because they're "just for employees."
Learn more SolutionRAG Applications
Retrieval-augmented applications connect model behavior to private documents and enterprise data. Their security depends on whether retrieval boundaries hold under adversarial conversation.
Learn more SolutionAutonomous Workflows
Long-running agent workflows combine model decisions, external content, tools, and state across multiple steps. A small trust-boundary failure can compound into a high-impact action.
Learn moreSee Oxyne on your own systems.
Book a 30-minute walkthrough — we'll scope a real assessment for your AI and web surfaces.