Agent Runtime Governance · EDR for AI agents

Can you see everything your AI agents do?Govern every action — and keep shipping.

Every command, tool call, and data access happens at machine speed — in a blind spot your EDR and DLP can't see. GuardionAI gives security and AI teams real-time visibility, enforcement, and evidence across every agent: customer-facing, autonomous, and coding.

Featured in

GoogleOWASP GenAIWIREDMMC Ventures
app.guardion.ai/aegis-ai/monitoring
AAM

Live Runtime Monitoring

Jun 15 – Jun 16
Total Events
92,782↑ 902.6%
Excluding guardrails
Total Flagged
4,523↑ 1.0%
Flagged spans
Total Findings
24↓ 15.4%
Unique threats
Critical Threats
3
Found · require attention
Event Timeline
By event type & status
AllLLM RequestTool Invocation
Regular Flagged Redacted Denied
Flagged Breakdown
claude-code1974
openclaw847
fintech-support-bot245
production-chatbot122
Finding Status
24
Open20
In Review2
Closed2
False Positive0
Recent FindingsLatest threats across your applications
ThreatApp/AgentRiskStatusOccurrencesFirst SeenLast Seen
Lethal Trifecta Detected
coding-agent-policy
claude-code
SecurityCritical
Open14
Jun 12
09:14
Jun 16
11:02
Data Exfiltration via MCP
customer-facing.policy
fintech-support-bot
Data LeakCritical
Open7
Jun 14
22:47
Jun 16
08:31
Destructive Command on AWS
coding-agent-policy
openclaw
InfrastructureHigh
In Approval3
Jun 15
16:20
Jun 16
03:55
Malicious Skill Behavior Drift
coding-agent-policy
claude-code
Supply ChainHigh
In Review21
Jun 09
13:05
Jun 16
10:48

The state of agent security

AI agents are transforming your business — and creating risks you can't ignore.

Blocking them isn't an option. Neither is leaving them unprotected. Across the industry, incidents are already happening — and traditional DLP and API security weren't built for them.

88%

of organizations had — or suspect — an AI agent security incident in the last 12 months.

CSO

80%

report risky agent behaviors — unauthorized system access and improper data exposure.

AIUC-1

+$670K

added to the average breach cost when AI is used without governance or access controls.

IBM Cost of a Data Breach

What actually goes wrong

Six ways a runtime action becomes your next incident.

Across customer-facing AI, autonomous agents, and coding agents — mapped to the frameworks your auditors already use.

Customer-facing AI

Your chatbot gets hijacked

A crafted message — or poisoned content it retrieves — makes your support bot ignore policy and give unauthorized or off-brand advice.

OWASP LLM01 · Prompt Injection

Off-policy output you are liable for.

Customer-facing AI

The bot exposes a customer

The assistant returns PII or account details that belong to someone else — straight into a customer-facing response.

OWASP LLM02 · Sensitive Info Disclosure

A reportable LGPD / GDPR data-exposure event.

Autonomous agent

An agent exfiltrates data

An autonomous agent pipes customer records to an external endpoint through an MCP or tool call — at machine speed.

OWASP LLM06 · AARM Data Exfiltration

Exfiltration you find out about after.

Autonomous agent

A vetted tool goes rogue

A tool you approved is compromised after the fact — like the Hugging Face MCP poisoned post-approval — and your agent keeps calling it.

OWASP LLM03 · AARM Malicious Tool Output

Supply-chain drift with your agent's permissions.

Coding agent

A secret walks out

A coding agent reads an API key or credential and pastes it into a tool call or a commit. EDR never saw it — it isn't endpoint malware.

OWASP LLM02 · AARM Side-channel Leakage

A credential-exposure incident, found late.

Coding agent

A destructive command runs

A coding agent runs rm -rf, drops a production table, or pushes to prod — an action no human approved.

OWASP LLM06 · AARM Destructive Action

Data loss or an outage, with no trace of why.

And until you can answer “how do you govern this?”, any one of them can stall your next enterprise deal in security review.

Proof in production

Trusted in production by the largest fintechs in LatAm.

Their agents were live and fully blind — no visibility into what they were doing, no way to trace an incident back to a user. Now every action is observed, enforced, and on record, and security and product finally ship together.

+50M
Agent actions / month protected
0.00%
Detection precision · 0.02% false positives
<0ms
Policy-engine decision · +7ms gateway

Trusted and Backed by

Entrepreneurs First — backedGoogleIndustry veterans in AI, tech & cybersecurity
Apple

Built by the engineers who secured Siri.

Now governing your agents.

The platform

One platform to govern every AI agent across your enterprise.

Every action observed, enforced, and answered for.

Monitor every AI interaction, investigate incidents, enforce policies, and govern every agent from one place.

Live Runtime Monitoring

Jun 15 – Jun 16
Total Events
92,782↑ 902.6%
Excluding guardrails
Total Flagged
4,523↑ 1.0%
Flagged spans
Total Findings
24↓ 15.4%
Unique threats
Critical Threats
3
Found · require attention
Event Timeline
By event type & status
AllLLM RequestTool Invocation
Regular Flagged Redacted Denied
Flagged Breakdown
claude-code1974
openclaw847
fintech-support-bot245
production-chatbot122
Finding Status
24
Open20
In Review2
Closed2
False Positive0
Recent FindingsLatest threats across your applications
ThreatApp/AgentRiskStatusOccurrencesFirst SeenLast Seen
Lethal Trifecta Detected
coding-agent-policy
claude-code
SecurityCritical
Open14
Jun 12
09:14
Jun 16
11:02
Data Exfiltration via MCP
customer-facing.policy
fintech-support-bot
Data LeakCritical
Open7
Jun 14
22:47
Jun 16
08:31
Destructive Command on AWS
coding-agent-policy
openclaw
InfrastructureHigh
In Approval3
Jun 15
16:20
Jun 16
03:55
Malicious Skill Behavior Drift
coding-agent-policy
claude-code
Supply ChainHigh
In Review21
Jun 09
13:05
Jun 16
10:48

The difference

Three layers where agents act. One platform to govern them all.

Most tools secure only the prompt. GuardionAI governs every layer — what your agents say, what they do, and what they build.

What agents say

Customer-facing AI

Chatbots, copilots, and support — every response is public, and you are accountable for it.

The risk
  • Customer PII exposed in a response
  • Prompt injection & jailbreaks
  • Off-policy or non-compliant advice
  • Regulatory exposure — LGPD, GDPR, EU AI Act
What agents do

Autonomous agents

Agents acting on your systems through MCP servers and tools — on their own, at machine speed.

The risk
  • Data exfiltration through a tool call, not the prompt
  • Over-privileged access to production data
  • Compromised or poisoned MCP tools
  • Shadow AI & ungoverned agents
What agents build

Coding agents

Claude Code, Codex, OpenCode, and Cursor writing and running code across your environment.

The risk
  • Secrets & credentials leaked into code or commits
  • Destructive commands — rm -rf, dropped tables, pushes to prod
  • No audit trail from an incident back to a user

GuardionAI

Agent Runtime Governance

One platform across all three layers — the same policy engine, observability, and incident response. Start anywhere, no new tooling.

What we govern

Conversational AIMCP & endpoint DLPCoding agentsSecrets & credentialsShadow AI discoveryPrompt injection & jailbreaksPII detection & redactionTool & MCP supply-chainTamper-evident audit & evidence
SystemsAI AgentsEndpointsMCP ServersDatabasesCustomer PII exposedfrom AI outputRedacted

ModernGuard model series

Our own guardrail models — not a generic API.

ModernGuard is our multilingual model series for prompt security, AI safety, and privacy — built on ModernBERT and trained on proprietary data. Guardrails are event- and session-aware, accumulating context into a live session risk score, so we catch the real action and behavior — not just the prompt. Fully fine-tunable to your use cases, updated from feedback and as it processes production data. Covers 1,080+ languages, fine-tuned on 11.

Hugging FaceGuardion/ModernGuard-1
#1
96.3 F1 on the Prompt Security Leaderboard
20×
faster latency than cloud provider guardrails
1,080+
languages covered

Works with your stack

Works with the AI stack you already have.

Connect once. Protect every AI application, agent, and model already running in your environment — no architecture changes, no rewrites, no vendor lock-in.

RAG VECTOR DATABASE
Pinecone
weaviate
milvus
SPM (Security Posture Mgmt)
Wiz
Prisma Cloud
Microsoft Defender
Orca Security
AI BOM
Hugging Face
MLflow
Weights & Biases
CycloneDX
ENDPOINT & WORKSTATIONS
macOS
Windows 11
Linux
NETWORK SECURITY
netskope
zscaler
cisco
IDENTITY PROVIDERS
okta
Microsoft Entra ID
Google Workspace
GuardionAI
GATEWAYS (LLM & MCP)
CloudFlare
LiteLLM
Portkey
LLMs
OpenAI
Claude
Gemini
cohere
Meta
CLOUD PROVIDERS
aws
Google Cloud
Microsoft Azure
MULTI AGENT FRAMEWORKS
OpenAI SDK
LangGraph
Claude SDK
LlamaIndex
LangChain
crewai
NO CODE PLATFORMS
n8n
UiPath
zapier
Agentforce
Copilot
CODING AGENTS
Claude Code
Cowork
Codex
OpenCode
Cursor

Enterprise & trust

Enterprise-grade from the first request.

Zero-trust by architecture

Encrypted gateway; no model provider sees raw data; your data never trains our models. PII is stripped before it ever leaves your org, backed by a security vault.

Compliance-ready

GDPR, HIPAA, and LGPD-ready, with SOC 2 Type II in progress. Comprehensive audit logs, SSO, and granular RBAC — tamper-evident and exportable to your SIEM.

We deploy it with you

A Guardion engineer embeds with your team for 30 days. Replaces the ~12 months and 3+ engineers it takes to build this in-house.

SOC 2 Type II — in progressGDPR · HIPAA · LGPDAARM-alignedANPD AI Regulatory Sandbox — participant

FAQ

The technical details, answered.

For the buyer who needs to know exactly how it works before it ships.

How does GuardionAI deploy into our stack?

Two modes, no application rewrites. Run it inline as a Security Gateway in front of your models, agents, and MCP servers, or call the Guard API directly from your code. Either way it is zero-instrumentation — connect once and it covers every AI application already running in your environment.

What latency or overhead does it add?

The policy engine returns a decision in under 130ms, and the inline gateway adds roughly 7ms of overhead. Enforcement happens before an action executes, so you get real-time blocking without a noticeable hit to your agents.

Which models, frameworks, and tools do you support?

Any model (OpenAI, Claude, Gemini, Bedrock, Cohere, Meta), any framework (LangChain, LlamaIndex, CrewAI, Swarm), any MCP server, and any cloud. Coding agents like Claude Code, Codex, OpenCode, and Cursor are first-class — and it works across five native languages, extended to 1,000+ through post-training.

How do you handle our data?

Zero-trust by architecture. The gateway is encrypted, no model provider sees raw data, and your data never trains our models. PII is stripped before it ever leaves your org, backed by a security vault, and all logs are tamper-evident and exportable to your SIEM.

Does it govern coding agents too?

Yes — this is a core focus. GuardionAI sees what coding agents build and run: it catches secrets and credentials leaking into code or commits, blocks destructive commands (rm -rf, dropped tables, pushes to prod), surfaces which models and credentials developers actually use, and traces any incident back to a session and a user.

How do you get us to production?

We deploy it with you. A Guardion engineer embeds with your team for 30 days to stand it up — replacing the ~12 months and 3+ engineers it would take to build this in-house.

What about compliance and certifications?

GDPR, HIPAA, and LGPD-ready, with SOC 2 Type II in progress. Detections map to the OWASP LLM Top 10, NIST AI RMF, and AARM threat classes, and we are a participant in the ANPD AI Regulatory Sandbox. SSO and granular RBAC come standard.

Now you can see everything your AI agents do —and govern every action without slowing down.

Real-time visibility, enforcement, and evidence across every agent — customer-facing, autonomous, and coding.

We deploy it with you · Cancel anytime