Find every agent.
Discover authorized and shadow agents across the enterprise — with their MCP connections, tools, owners, access, capabilities and risk.
The Agentic Trust Center
Agenti5
As AI agents become autonomous workers, Agenti5 ensures every identity is verified, every action is governed and every decision is accountable. Because AI without trust is just automation without control.
Discovery3 unregistered agents
Trust gateway · identity · policy · audit
Agent identity
AP-Recon-07Trusted
- Owner
- Finance operations
- Purpose
- Invoice reconciliation
- Authority
- ERP read · payment propose
Token budget72%
The AI workforce is here
- Machine-to-human identity ratio.
- 109:1
Machine-to-human identity ratio.
- AI agents expected by 2028
- 1.3B
AI agents expected by 2028
- Source · Palo Alto Networks, 2026 Identity Security Landscape
- Average additional breach cost associated with Shadow AI.
- $670,000+
Average additional breach cost associated with Shadow AI.
- Source · IBM, 2025 Cost of a Data Breach Report
The agentic stack
Employees don’t act alone anymore — they collaborate with AI. AI acts, decides, retrieves, connects and executes. Yet almost every AI interaction today happens without identity.
- 01Human
Employees and operators — the only layer most security was ever designed around.
- 02AI agent
Autonomous execution, acting on someone’s behalf and very often with their access.
- 03Runtime
Execution and orchestration, where one request quietly becomes many steps.
- 04LLM
Model reasoning that decides what happens next — and can be talked out of its own guardrails.
- 05Tools & APIs
Integrations and connectors: the point where a decision becomes a capability.
- 06Systems
Internal data and enterprise systems, reached through every layer above.
- 07Action
Executed and logged. With Agenti5, attributable to an identity, an authority and a policy.
The new attack surface
01
Jailbreaks
Models talked out of their own guardrails, one clever prompt at a time.
02
Prompt injection
Instructions smuggled inside content an agent was only supposed to read.
03
Browser data leakage
Copilots with tabs open to everything, and no boundary on what leaves.
04
Shadow agents
Agents nobody registered, running with access nobody reviewed.
Meet Agenti5
Five controls that turn autonomous AI from an unmanaged surface into governed infrastructure.
01 / 05 · DISCOVERagents discovered0
Give every agent an identity.
Issue a unique, cryptographic identity tied to each agent’s owner, purpose, permissions, environment and trust context.
Verify before they act.
Cryptographically authenticate and continuously verify every agent — credential, provenance and authority — before granting access or allowing actions.
Control every decision. Prove every action.
Enforce least privilege, human approval, DLP, kill controls and runtime policy — with an immutable record of every action, decision and outcome.
Make every token count.
Optimize structured data and prompts in real time, reducing unnecessary token consumption and AI cost by up to 60–85%.
At the moment of action
- IDENTITY
An identity for every agent
Each agent carries a unique identity with an owner, a purpose, an environment and a lifecycle — not a shared service account that four workflows happen to use.
- AUTHORITY
Authority, verified before the tool call
Credential, provenance and authority checked before the agent reaches a system or a tool. Knowing which model is running is not the same as knowing what it is allowed to do.
- POLICY
Policy at runtime
Least privilege, human approval, DLP and kill controls applied to the call being made — so an exfiltration attempt is refused rather than reported the next morning.
- PROOF
Signed, attributable proof
Which agent acted, under whose authority, against which policy and with what result — recorded as a cryptographic proof rather than reconstructed from logs.
Runtime governance
Prompts
Injection Shield
Detect and control prompt injection, jailbreak and malicious instruction patterns before they become consequential action.
Data
DLP & tokenization
Protect sensitive data as agents interact with models, APIs, tools and enterprise systems.
Discovery
Shadow AI sensor
Discover unsanctioned AI services and agent activity touching the enterprise network.
Detection
Deception canaries
Use controlled signals to detect unauthorized access patterns and suspicious autonomous behavior.
Cost
Token budgets
Control model usage by agent, workflow or team and eliminate unnecessary consumption.
Routing
Provider optimization
Route workloads based on policy, cost, performance and business requirements.
A different layer of the stack
Agenti5 moves identity to the moment of action — so the enterprise can prove which agent acted, under whose authority, against which policy and with what result.
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