Enterprise AI Infrastructure

The layer between
your app and AI.

Drop in. No rewrites.

Caddy connects your existing state, APIs, and data to any AI — without custom integrations or migrations. One component. Any stack.

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SOC 2 Ready
MCP-Native
Zero Rewrite
RBAC + Audit
Integrates with
React Node.js Python Go PostgreSQL Redis Kafka GraphQL Claude GPT-4o Gemini
Architecture

One layer. Zero rewrites.

Context flows from your existing stack through Caddy to any AI model — observed, secured, and routed in a single component deployed once.

Your Application
Frontend State
Web & mobile apps
ReactReduxZustand
Backend Services
REST / GraphQL APIs
NodePythonGo
Data Stores
Databases & queues
PostgresRedisKafka
Observe
Caddy
👁
State Observer
Passively hooks into app state
🔒
Access Control
Scoped context, signed tokens
⚡
Inference Router
Stateless, horizontally scalable
📋
Audit Logging
Full context trail per request
Deliver
AI / Inference
Claude
Anthropic
Claude 3.5
GPT-4o
OpenAI
GPT-4
Custom LLM
Any MCP-compatible model
AgentsTools
Why Caddy

Different by design.

Most solutions ask you to rebuild, migrate, or write custom glue. Caddy is a single component that fits into what you already run.

01
Drop-in, not build-in
Works with your existing state, APIs, and data stores. No migrations, no refactors — unlike point solutions requiring new pipelines in every service.
Any stackZero rewrite
02
Model-agnostic
Route context to any LLM or AI provider. Switch models or add new ones without changing your app — no vendor lock-in or one-off integrations.
Any modelMCP protocol
03
Secure by default
Scoped context, audit trails, RBAC, and horizontal scaling are built in — not bolted on. Enterprise security your compliance team can approve.
RBACAuditJWT
Capabilities

Everything you need.
Nothing you don't.

State Observer
Live app context — no polling, no duplication
Caddy passively observes state, request lifecycles, and data events. Your code stays unchanged. AI gets structured, real-time context it needs to reason accurately.
app.tsx
// Your existing React application
import { CaddyProvider } from '@Caddy/react'
 
// Wrap once — Caddy observes everything
export default function App() {
  return (
   <CaddyProvider
     scope="org:acme"
     model="claude-3-5-sonnet"
   >
     <YourApp />
   </CaddyProvider>
  )
}
Inference Router
Route to any model, anytime
Batch and stream structured context to any LLM. Switch models or add new ones at the infrastructure level — your application code never changes.
MCP-Native
Built on open standards
Implements the Model Context Protocol natively. Compatible with all MCP tooling and runtimes — no proprietary abstractions, no closed integrations.
🔒
Scoped Context
Context scoped per request and org. No cross-tenant data exposure by design.
📋
Full Audit Trail
Every payload logged with timestamp, model, and user attribution.
⚖️
Role-Based Access
RBAC and JWT enforcement at the context layer before any inference call.
📈
Horizontal Scale
Stateless router — queue, batch, and stream modes out of the box.
Pricing

Enterprise pricing,
tailored to you.

No fixed tiers. Scoped to your stack, usage, and deployment requirements.

Enterprise Plan
Custom contract.

We work with your team to scope deployment, usage limits, SLAs, and security requirements. Every customer receives a dedicated engagement.

Contact Sales
Scoped to your environment and usage
Dedicated support and guaranteed SLAs
Custom contracts and security terms
Deployment guidance and onboarding