Non-invasive real time AI threat detection
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Bad detection doesn’t just distract, it destroys business
Most detection tools watch only north–south traffic. But in AI applications, the majority of interactions are east–west: agents invoking other agents, MCP servers chaining APIs, or vector queries midstream. Miss those, and breaches spread invisibly inside production and remain undetected for long periods of time.
Legacy scanners assume deterministic systems. AI isn’t. Agents swap models, alter chains, or trigger loops at runtime, behavior static rules mistake as “incidents.” The flood of false alarms burns analyst hours, slows investigations, and desensitizes teams to real threats.
Every wasted alert is more than a distraction, it’s a tax on scarce analyst time. Overloaded teams stop triaging, assuming “another false alarm.” The cost is inaction: true risks go uninvestigated, responses stall, and incidents escalate into breaches.
Equally dangerous, missed detections allow genuine exploits to persist silently. From insider misuse to chained agent abuse, undetected threats operate until damage is irreparable. Data loss, regulatory fines, and reputational harm mount, all because the system never rang the alarm.
Detection that reduces manual overhead
Security posture matures continuously without extra headcount
Every detected exploit attempt — from prompt injections to data extraction — is auto-converted into repeatable tests. Posture improves with every incident, closing the loop between runtime detection and pre-production hardening.
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Compliance proven, audit friction lowered in regulated industries
Sensitive data flowing through prompts, embeddings, or vector DBs is identified without ever sending payloads to vendor LLMs. eBPF sensors and satellites enforce detection locally, keeping PHI/PII secure.
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Time to value accelerated, tuning cycles cut from months to minutes
Unlike black-box stacks, Levo’s rules are white-box: visible, editable, and extensible. Enterprises can suppress noise, add servers, or tune detection instantly with NGINX + ModSecurity configs.
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Levo unites every team to defend against the biggest risk: obsolescence from slow AI adoption.
Ship faster without noise. High signal detections ensure quick remediation, and ensure engineering velocity is not slowed by false alarms.
Replace blind spots with clarity. Realtime, explainable detections across agent chains and east–west flows reduce burnout and accelerate response to what actually matters.
Prove compliance continuously, not retroactively. Validated, audit grade signals tie actions to identities and data flows, eliminating audit fatigue and cutting regulatory risk.
Cut through noise, eliminate threats, eradicate budget wastes
Frequently Asked Questions
Got questions? Go through the FAQs or get in touch with our team!
What is Levo’s AI Detection?
Levo delivers non-invasive, context aware, runtime aware detection that surfaces only validated risks across the entire AI control plane, then guides rapid remediation without drowning teams in noise.
What makes it “non-invasive”?
eBPF sensors and satellites observe runtime traffic passively, so there are no SDKs to stitch, no agent rewrites, and no broken calls. Coverage improves without slowing delivery.
How is this different from legacy detection stacks?
Traditional tools focus on north south edges and deterministic patterns. Levo watches east west machine to machine flows inside AI apps, understands non deterministic agent behavior, and validates impact before alerting.
What risks does it detect out of the box?
Prompt injection, data extraction and leakage, insider misuse, unsafe agent chains, unexpected model switches, excessive token consumption, agent loops, and risky MCP or API calls in live runtime.
What does “validated risk” mean?
An alert fires only when Levo correlates behavior, identity, and data movement to show a real exploit path. This reduces false positives and accelerates response.
How does Levo reduce false negatives?
By inspecting east west traffic across agents, MCP servers, LLMs, RAG, vector stores, and APIs. Hidden chains and insider actions are visible, so genuine threats do not slip by.
How is Levo “context aware”?
Detections include who authorized and who executed, token scope, model and tool changes, and the full chain of calls. Analysts see the why and the how, not just a symptom.
Does this add latency or break flows?
No. Detection is passive at runtime. Levo does not sit inline or block by default, so performance and reliability remain intact.
How fast can we get value?
Time to value is measured in minutes, not months. Out of the box AI rules start clean, then teams tune instantly with white box policies.
What are “white box rules”?
All rules are visible, editable, and extensible. You can suppress noise, add servers, and tune detection quickly, including via NGINX plus ModSecurity configs.
Can analysts customize signals on the fly?
Yes. Analysts can suppress, refine, or request new rules on demand. High fidelity signals reduce alert fatigue and focus teams on what matters.
How does Levo handle non deterministic agent behavior?
Levo understands that agents branch and adapt. It correlates plan changes, tool use, and token patterns with identity and data flow to avoid misclassifying normal variance as incidents.
How does this cut mean time to detect and respond?
Validated alerts arrive with chain context and remediation cues. Less triage, faster action, and lower dwell time follow naturally.
What about privacy and compliance?
Sensitive payloads stay local. Levo identifies PHI or PII risks in prompts, embeddings, and vector DBs without sending payloads to vendor LLMs, easing audits in regulated industries.
How does detection improve our overall security posture?
Every detected exploit attempt is auto converted into a repeatable test. Your pre production and CI pipelines harden continuously using real runtime truth.
Is this a black box?
No. Levo ships AI specific rules and lets you extend coverage programmatically via MCP, turning detections into usable data for developers, SOCs, and AI copilots.
How does this help Engineering?
High signal alerts and clear context prevent churn. Teams fix fast and keep shipping without being slowed by false alarms.
How does this help Security?
Blind spots are replaced with explainable, real time detection across agent chains and east west flows, reducing burnout and speeding investigations.
How does this help Compliance?
Validated, audit grade signals tie actions to identities and data flows. Evidence is always available, so audits become routine.
What outcomes should we expect?
Fewer breaches, leaner operations, lower cloud and tuning costs, and faster, safer AI deployments with measurable reductions in noise and response time.
What is the UVP in one line?
Non-invasive, high signal, context aware, runtime aware, configurable real time detection that finds and fixes what matters across your entire AI control plane.
How do we get started?
Cut through noise, eliminate threats, eradicate budget wastes. Deploy Levo detection and accelerate response from day one.
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