New — MCP Governance: register, allow, and deny every tool call an agent makes
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Enable AI across the company
without losing sight of what it does

Stop your data from leaking into AI tools.

ADRI inspects every AI chat and coding agent, redacting sensitive data from prompts and file uploads in real time — before it ever leaves the device.

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adri-security-layer 6 threats
Hey Claude, can you help me analyze this customer data?

Customer: John Smith
Email: john.smith@acmecorp.com
SSN: 523-42-7891
Credit Card: 4532-1234-5678-9012
API Key: sk_live_abc123xyz789
inspecting on device… latency 60.4ms
Coverage across the tools your team already uses
ChatGPTClaudeGeminiCopilotPerplexityCursorClaude CodeCodexGemini CLIOllamaLM StudioLangGraphMCP
ChatGPTClaudeGeminiCopilotPerplexityCursorClaude CodeCodexGemini CLIOllamaLM StudioLangGraphMCP
Who it's for

For teams accountable for AI use

ADRI runs on the endpoint, so every team that answers for AI — security, compliance, engineering — works from the same evidence instead of guesses.

Security & IT Teams
Find every AI tool, coding agent, and MCP server on every device — including the ones IT never approved — and enforce policy at the source, over VPN, proxy, or offline.
Explore discovery
Compliance & Risk Teams
Every inspection, block, and override is logged on the device with a full forensic timeline — audit-ready evidence mapped to the frameworks you already answer to.
Explore compliance
Engineering Teams
Keep Cursor, Claude Code, Codex, and local models in the workflow. Redaction runs in under 100ms on the device, so nobody trades velocity for a policy freeze.
Explore the gateway
The Challenge

Current AI Security Has a Blind Spot

Cloud-based and network-level solutions can't see what happens on the device. That's where AI agents actually run — and where data actually leaks.

0%
of employees use AI at work — most unsanctioned
0%
of AI prompts include sensitive data
0+
AI apps per company, most unreviewed by IT
Cloud Solutions Are Blind
SaaS security tools only see sanctioned apps. Local LLMs, custom agents, and MCP servers stay invisible.
Network-Level Is Bypassable
VPNs, encrypted tunnels, and offline usage defeat network monitoring. Determined users find workarounds.
Agents Act Autonomously
Modern AI agents chain actions, call tools, and access systems — faster than humans can review.
Data Leaves Before You Know
By the time cloud telemetry arrives, sensitive data has already reached external AI providers.
On-Device AI Gateway

Inspect everything. Redact before it leaves.

Every AI call passes through ADRI at the source — before it leaves the device. LLMs, agents, MCP servers, local models. Detection runs locally across prompts and file uploads; cloud escalation is opt-in only.

Sanitized output safe to send
Personal Name Email Address SSN Credit Card API Key Password
<100ms
redaction latency
6/6
entities removed on device
Prompt & upload inspection
Every AI call routes through ADRI on the device — cloud APIs, local models, MCP servers, agent frameworks.
Learn more →
Hard to bypass
Unlike cloud-only tools, an on-device agent keeps protecting over VPN, proxy, or offline — wherever your people work.
Learn more →
Discovery & MCP Governance

Know every AI tool. Govern every tool call.

Shadow AI & MCP Discovery
Find every AI tool, coding agent, and MCP server on every device — ChatGPT, Claude, Copilot, Cursor, local LLMs, and shadow MCP servers IT never approved.
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MCP Governance
Register every MCP server through ADRI, see which tools each agent can call, allow or deny per tool, and block shadow MCP installs — org policy enforced in real time.
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Detection stack

Four layers, all of them on the device

Each prompt falls through the stack in one pass. Nothing leaves the endpoint to make the decision.

LAYER 1
Entity models
PII, secrets, financial and health data
LAYER 2
Context engine
Who is asking, which tool, which agent
LAYER 3
Data fingerprints
Your own systems, recognised by fingerprint
Policy layer
Your rules decide redact, warn or block
Analyst overrides Fingerprint connectors Agent & MCP context
one pass · 60.4ms · no cloud call
Shadow AI map

What is actually running on your fleet

Every endpoint reports the AI tools, agents, and MCP servers found on it — sanctioned or not.

Sanctioned Shadow
0
endpoints reporting
0
distinct AI tools discovered
0
shadow MCP servers
Anatomy of one prompt

From keystroke to provider, in 60 milliseconds

01
Prompt typed
An engineer pastes a customer record into Claude, on home Wi-Fi, outside the corporate network.
02
Intercepted on device
The call routes through the local gateway before a single byte reaches the network stack.
03
Classified & redacted
Local models label each entity against your policy and strip what must not leave.
04
Delivered clean
The provider receives a usable prompt. The audit trail keeps the original decision, not the data.
POST api.anthropic.com/v1/messages
Customer: John Smith · SSN: 523-42-7891
network: home wi-fi · vpn: off
adri.gateway → intercepted (pre-egress)
payload buffered locally · 0 bytes sent
applies regardless of network, VPN, or proxy
classify → PERSON, SSN, CREDIT_CARD, API_KEY
policy [Data_Exfiltration] → redact 6 entities
local inference · 60.4ms · no cloud call
Customer: ████████ · SSN: ███████████
delivered · safe to send
logged: 6 redactions, actor, policy version
MCP governance

Allow or deny, per server and per tool

Agents ask for tools, not permission. ADRI registers every MCP server and decides each call against org policy in real time.

MCP serverToolRequesting agentCalls / 24hPolicy
How it works

Up and running in under an hour

Deploys in minutes. Runs silently. Catches AI use on the device — where cloud and network-only tools can't see.

1.
Deploy
One-click install on macOS, Windows, or Linux. Deploys via MDM (Intune, Jamf, Kandji), SCCM, or direct download.
2.
Inspect
Every AI call routes through ADRI on the device — cloud APIs, local models, MCP servers, agent frameworks.
3.
Control
Block, redact, or allow based on your policies. Real-time alerts, centralized dashboard, per-user rules.
4.
Prove
Full audit trail and forensic timeline. Every policy change logged for compliance, with one-click rollback.
# Install ADRI agent
$ curl -fsSLo install.sh adrisecurity.ai
$ sh install.sh
→ agent installed · policy synced · 0 reboots
# Or via MDM/SCCM
$ adri deploy --fleet
→ 1,248 endpoints queued
// ADRI inspects:
✓ OpenAI, Anthropic, all LLM APIs
✓ Local Ollama, LM Studio, llama.cpp
✓ MCP servers & tool calls
✓ Agent frameworks (LangChain, etc)
✓ Prompts & file uploads
→ avg inspection 60.4ms
// Centralized control:
• Block sensitive data exfil
• Allow approved AI tools only
• Alert on shadow AI discovery
• Deny per MCP server and per tool
• Per-user policies by role or team
→ 550 threats blocked this month
// Evidence, ready for the exam:
• Full forensic timeline per endpoint
• Every override logged with reasoning
• Policy version history + rollback
• Exports mapped to ISO 27001 / SOC 2
→ 22,158 events retained · air-gap capable
Security Operations

Unified AI Security Dashboard

Real-time visibility into threats, policy compliance, and AI usage across your organization.

0
Total Evaluations
+12.4%
0
Threats Blocked
27.6% rate
0
Content Allowed
+8.2%
60.4ms
Avg Response
-2.1ms
Evaluation Intensity
Last 12 months activity frequency
Security Logs LIVE
Inside the console

One place to see the whole fleet

ADRI
Overview
Endpoints
Shadow AI
MCP servers
Policies
Audit trail
agents healthy
Overview · last 7 days
7d30d90d
Prompts inspected per day
Top endpoints by redactions
MBP-4821 · r.cohen142
WIN-1174 · d.levy118
MBP-2093 · a.shani96
LNX-0442 · build-agent71
updated just now
What gets caught

Redactions by entity type, last 30 days

0
Personal Name
0
Email Address
0
API Key
0
SSN
0
Credit Card
0
Password
System map

Your stack, your policy, one enforcement loop

Deployment & identity
INT
JMF
KAN
SCCM
SSO
SIEM
EDR
MCP
SCIM
+more
Fleet enrolled Policy sync
ADRI CONSOLE live
Endpoints
1,248
Tools
63
Blocked
550
Latency
60.4ms
redaction-policy-v12412active
mcp-allowlist-v417review
eng-team-override86active
On-device detection Auto / manual trigger Continuous learning
Your policy
Data classes, allowed tools, per-team rules
Enforcement
Redact, warn or block on the device
Audit & tuning
Every decision logged, overrides feed policy
Fits your stack

Deploy with what you already run

Microsoft Intune
MDM rollout
Jamf
macOS fleet
Kandji
macOS fleet
SCCM
Windows rollout
Air-gapped install
No cloud dependency
WindowsmacOSLinuxiOSAndroidSIEM exportWebhooksSSO / SAMLSCIMSelf-hostedCoexists with EDR
WindowsmacOSLinuxiOSAndroidSIEM exportWebhooksSSO / SAMLSCIMSelf-hostedCoexists with EDR
Multi-framework

Stay compliant across every framework you answer to

Enforce data-handling requirements consistently across regions and regulators, with policies tuned to your own rules — without adding operational complexity.

GDPR / CCPA
Prevents personal data from reaching unauthorized processors; supports data minimization.
EU AI Act
Provides logging and oversight controls that support transparency obligations.
ISO 27001 / SOC 2
Generates audit-ready logs mapped to Annex A / Trust Services Criteria.
Israeli Privacy Law (Amdt. 13)
Helps enforce data-security obligations and supports breach-readiness.
Tuned to your policies
Detection reflects your own data classes and rules, not a generic pattern list. Different policies for engineering, finance, and legal.
Deploys where you operate
Cloud or self-hosted, hybrid with network-level control, and fully functional air-gapped. Native agents for Windows, macOS, Linux, iOS, Android.
Financial Services Healthcare & Life Sciences Legal Technology & SaaS Government & Public Sector Any regulated enterprise

ADRI supports these obligations as part of a broader compliance program; it is not a substitute for legal review or certification.

Ready to turn AI use from a blind spot into a control?

Thirty minutes, your endpoints, your policies. We'll show what ADRI catches before it leaves the device.

Book a demo
ADRI Security
On-device AI data loss prevention for every chat, agent, and MCP server your team uses.
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