Business Intelligence Visibility
Track model spend, usage trends, and operational efficiency in one place.
The Control Plane for Your AI Ecosystem.
You build the core product; we handle the rest. Agent ID is your infrastructure for AI security, observability, ROI, and automated AI Act compliance.
Developers: docs.getagentid.com
Unified Control Highlights
01
Built on a Zero-Trust Architecture
Enforce hard runtime guardrails before model actions execute.
EU AI Act Automation
Generate Annex IV evidence and immutable audit logs automatically.
Seamlessly integrates with your AI stack: OpenAI, Anthropic, LangChain, Vercel, Pinecone, AWS
OpenAI
Anthropic
LangChain
Vercel
Pinecone
AWS
OpenAI
Anthropic
LangChain
Vercel
Pinecone
AWS
One Unified Control Plane for Every AI Team
Built on a Zero-Trust Architecture with Business Intelligence visibility and automated EU AI Act compliance.
Fast control layer onboarding with built in policy templates
Launch on a control plane, not a patchwork stack.
Ship product velocity while enforcing runtime security, tracking business intelligence signals, and generating compliance evidence from day one.
Control Plane Capabilities
Everything You Need to Run AI in Production
A unified control layer built on a Zero-Trust Architecture with business intelligence observability, deterministic governance, and automated EU AI Act compliance.
Universal SDK Integration
Connect OpenAI, Anthropic, LangChain, and custom model routes through one shared control layer in minutes.
agentid.guardrails().track().enforce();Real-time Guardrails
Enforce runtime controls built on a Zero-Trust Architecture that block PII leaks, prompt injection attempts, and unauthorized tool calls.
EU AI Act Native
Automate risk categorization, Article 12 evidence logging, and Annex IV documentation without manual workflows.
Annex IV / Article 12
Conformity Report Export
Risk classificationComplete
Article 12 logsSynced
Technical fileGenerated
Automated Compliance Reporting. Stop manual drafting, Agent ID compiles real-time telemetry into official Annex IV and Article 12 reports automatically.
Business Logic Control
Apply deterministic access policies that restrict agents from sensitive data paths and high risk actions.
Permission Matrix
db.read.ordersAllowed
db.write.paymentsBlocked
api.billing.high_costNeeds policy
Critical Action Oversight
Keep humans in the loop for high impact actions such as financial operations, policy edits, and destructive requests.
Oversight Queue
Transfer customer funds
Awaiting operator review: finance_ops
Delete production records
Human in the loop review in progress
Architecture
How the Unified Control Layer Works
Every AI action routes through a deterministic control path with runtime protection, policy enforcement, and immutable evidence logging.
01
User Request
User prompt enters your application
02
Agent ID Gateway
Control layer applies policy and validation built on a Zero-Trust Architecture
03
LLM Provider
Model inference executes in controlled scope
04
Agent ID Logger
Immutable telemetry and evidence capture
05
Safe Response
Approved output returns to your product
Realtime path
Security checks and guardrails execute before model responses are returned.
Async path
Usage analytics and compliance evidence are processed continuously in background.
Built for Engineering Velocity and Enterprise Control.
Integrate a unified AI control layer in minutes. Agent ID centralizes security, governance, and business intelligence observability without slowing your product roadmap.
Low Overhead Layer Enforcement
Runtime policy checks are optimized for production traffic so teams keep performance while enforcing deterministic controls.
Real-Time Security, Continuous Telemetry
Security decisions execute synchronously while analytics and compliance evidence flow asynchronously for resilient operations.
One Integration Across Your AI Stack
Standardize control for LangChain, Vercel AI SDK, OpenAI compatible calls, and custom provider workflows.
Type Safe SDKs
Use TypeScript and Python SDKs to ship deterministic policy control with developer friendly integration.
agent_guard.py
python
from agent_id import AgentGuard
# Initialize with one line
guard = AgentGuard(api_key="ag_...")
# Wrap your LLM call automatically
response = guard.chat.completions.create(
model="gpt-4o",
messages=[{"role": "user", "content": "Analyze this PII..."}],
# Policies applied automatically:
# 1. PII Redaction
# 2. Audit Logging
# 3. Rate Limiting
)Build vs Buy
Why Teams Standardize on Agent ID as Their Control Plane
In house governance stacks look simple at the start, but production AI requires deterministic security, observability, and compliance by default.
CategoryIn-HouseAgent ID
Integration timeCustom control layer, logging, and policy stack built from scratchProduction integration in minutes with one control layer
Security enforcementPrompt based controls with inconsistent behaviorDeterministic guardrails enforced on every request
Compliance operationsManual evidence gathering and fragmented audit trailsAutomated Annex IV outputs and immutable evidence logs
Business intelligence visibilityFragmented usage metrics and delayed optimization feedbackReal time business intelligence analytics with centralized reporting
FAQ
Frequently Asked Questions
How does Agent ID act as a unified control plane for AI systems?
Agent ID sits between your applications and model providers as a control layer. It enforces deterministic policies, captures immutable logs, and centralizes runtime security, governance, and business intelligence visibility.
Does the control layer add latency to production AI workloads?
Overhead is designed to stay minimal. Policy enforcement runs on optimized runtime paths while telemetry and analytics processing is handled asynchronously.
Can this support regulated enterprise environments and EU AI Act requirements?
Yes. Agent ID provides deterministic controls, human in the loop oversight, role based access boundaries, and compliance evidence workflows aligned with high risk operational needs.
Ready to unify your AI control plane?
Talk with our team about integration, rollout strategy, and how to centralize security, compliance, and cost visibility.