Levo.ai has released its Unified AI Security Platform, designed to secure AI applications from development to runtime. The platform unifies five modules under a single control plane, enabling enterprises to deploy AI while meeting compliance and security mandates.
AI has already proven it can deliver massive returns, but those gains remain stuck in pilots. Enterprises report productivity and revenue gains, yet only a fraction deploy AI at scale. Security and compliance stand in the way, keeping boards cautious and ROI unrealized.
How Levo unifies security in one control plane
Part of why AI pilots stall is because security tools weren’t built for the complexity of AI systems. They can’t govern the dense machine-to-machine flows that power AI: agents chaining tasks, MCP servers orchestrating tools, vector stores feeding models, APIs moving data.
With so many moving parts, securing AI piecemeal only multiplies risk. Levo.ai brings applications, agents, MCP servers, APIs, vector stores, and LLMs under a single security umbrella.
- Runtime AI visibility: Automated discovery for every AI component.
- AI monitoring & governance: With governance enforced at runtime, customer data is proactively protected.
- AI threat detection: Sensitive data exposure and over-permissioned agents are surfaced before incidents.
- AI threat protection: Attackers are blocked in real time while customers and partners continue uninterrupted, preserving revenue.
- AI red teaming: Prompt injections, poisoning, and collusion attempts are identified and remediated before they endanger customer data.
“Our eBPF sensors had already begun discovering LLM traffic, and customers asked us to extend that visibility across the entire AI stack. By giving enterprises the confidence to scale AI safely and fast, Levo ensures they lead the AI race,” said CEO, Buchi Reddy.
By automating security and compliance end-to-end, Levo helps enterprises bring AI into production sooner, realize its gains faster, and preserve those gains as profit instead of them disappearing into overhead.
