What Is Dwizi

Dwizi is infrastructure for AI tools.

It turns logic into secure, executable endpoints that AI systems can reliably use in the real world.

The Problem

AI systems need tools to be useful.

A language model alone cannot:

• Check real-world data
• Query databases
• Send messages
• Process files
• Call external APIs

Without tools, AI remains theoretical. With tools, AI becomes practical.

But building and operating AI tools today is hard.

Teams face:

• Infrastructure complexity
• Security and isolation concerns
• Deployment and scaling overhead
• Ongoing maintenance costs

Most organizations are not equipped to build tool infrastructure safely and repeatedly. As a result, AI adoption stalls before it reaches production.

What Dwizi Does

Dwizi provides secure, isolated execution for AI tools.

You define what a tool does. Dwizi runs it safely and exposes it as a stable URL that AI systems can call.

The result:

Every tool becomes an endpoint.

That endpoint can be used by:

• AI agents
• LLM-based applications
• Internal systems
• Or any AI platform that supports tool calling (such as MCP)

How It Works

At a high level:

1. Define logic

   • Write a JavaScript or TypeScript function
   • Or generate one from a prompt (for non-technical users)

2. Declare inputs

   • Explicit inputs and outputs
   • No hidden state

3. Deploy

   • Dwizi packages the logic into an isolated runtime

4. Use

   • The tool is available via a URL
   • AI systems call it when needed

Example Tool

export default async function getWeather(input: { location: string }) {
  return {
    temperature: 72,
    conditions: "sunny",
    location: input.location
  };
}

This becomes a callable tool that any compatible AI system can use to fetch weather data.

Security by Default

Every Dwizi tool runs in its own isolated execution environment with:

• Strict resource limits
• Network controls
• No shared state
• No persistent filesystem by default
• Automatic teardown after inactivity

Each execution is clean, predictable, and independent.

Isolation is not optional — it is the foundation of the platform.

Infrastructure Without the Burden

Dwizi eliminates infrastructure concerns rather than abstracting them away.

You do not manage:

• Servers
• Containers
• Scaling rules
• Networking
• Security boundaries

Dwizi handles:

• Execution lifecycle
• Isolation
• Streaming responses
• Resource management
• Availability

If a tool runs, it runs correctly. If it cannot run safely, it does not run at all.

Why This Matters

AI tools built on Dwizi are:

• Reliable — deterministic execution
• Secure — strong isolation by default
• Composable — every tool is a URL
• Maintainable — deploy by changing code
• Scalable — concurrent execution without manual work

Organizations can build real AI capabilities without becoming infrastructure companies.

For Enterprises

Dwizi enables enterprise AI adoption through:

• Controlled execution environments
• Organization-level access management
• Auditable tool usage
• Strong isolation boundaries
• Compatibility with existing AI tooling standards (including MCP)

AI tools become manageable, inspectable, and governable — not ad hoc scripts.

Platform Integrations (Present & Future)

Dwizi is designed to integrate with modern AI ecosystems.

Today

• Model Context Protocol (MCP)
• JSON-RPC–style tool execution
• HTTP-based invocation

Expanding Support

• OpenAI function calling
• Anthropic Claude tool interfaces
• Agent frameworks
• Custom AI platforms via APIs

Dwizi is not tied to a single AI vendor or model.

The Result

Dwizi turns AI tooling from an experimental exercise into production infrastructure.

Teams focus on solving problems. AI systems gain reliable access to real-world actions.

This is not about hype. It is about execution.