API Claw — Smart Hardware & Third-Party Developer Integration

Smartwatches, IoT devices, chat plugins — they all want built-in AI Agents. But running a large model on-device isn't viable: not enough compute, too much power draw, poor results.

API Claw is built for this. With a few API calls to Buda's OpenAPI, third-party developers can give their products a cloud-based OpenClaw 🦞 AI Agent — with conversation capability and a private knowledge base, waking on demand and consuming zero resources at rest.

In practice, you are not integrating a raw model API. You are integrating a managed Agent capability layer that already includes model access, runtime, knowledge base, session management, and operational scaling.

Who it's for

• Smart hardware makers — watches, earbuds, IoT devices that want a built-in AI assistant
• Software developers — mini-programs, apps, browser extensions that want to embed AI chat
• SaaS providers — who want to offer customers an "AI-powered private space"

Two common buyer types

1. Chat apps, SaaS tools, and third-party software

If you already have a product with users, conversations, forms, or workflows, API Claw lets you add an AI Agent without building the whole backend stack yourself.

Examples:

• A chat app that wants to add an AI assistant into every conversation
• A customer service SaaS that wants each customer to have a private AI support agent
• A browser extension or internal enterprise tool that needs a cloud-based AI worker

2. Hardware manufacturers

If you are building a smartwatch, earbuds, a voice terminal, or another connected device, API Claw lets the device connect to a cloud AI brain instead of trying to run the intelligence locally.

That means:

• The device handles input and output
• The Agent runs in the cloud
• Upgrades happen server-side instead of through constant firmware complexity

How it works

Your product (hardware / software)
        ↓  API call
  Buda OpenAPI
        ↓
  Space (tenant)
        ↓
  Agent (AI assistant) + Drive (knowledge base)
        ↓
  Chat Session (conversation)

Each end user gets an independent Chat Session with isolated context. The Agent sleeps when idle and wakes automatically when a message arrives.

What you do not need to build yourself

With API Claw, the developer does not need to separately build or operate:

• Model configuration and provider switching
• Inference machines or GPU infrastructure
• Agent runtime and tool sandboxing
• File ingestion and knowledge base processing
• Session and context management
• Tenant isolation for different users or customers
• Wake/sleep orchestration for idle agents

This is the key value: your team can focus on the product experience, while Buda provides the Agent infrastructure layer behind it.

Why not just call an LLM API directly?

Calling a model API gives you model output. API Claw gives you an operational AI Agent.

If you are a product company, this difference matters more than model quality alone.

API Claw vs OpenClaw

OpenClaw is the Agent capability and runtime layer. API Claw is the productized API surface that lets external hardware and software connect to that capability.

In simple terms:

• OpenClaw = the underlying Agent runtime / capability model
• API Claw = the developer-facing integration layer built on top of it

Integration steps

POST /api/openapi/spaces
Authorization: Bearer <your-api-key>

{
  "name": "User device space"
}

POST /api/openapi/spaces/{spaceId}/agents
Authorization: Bearer <your-api-key>

{
  "name": "My AI Assistant",
  "instructions": "You are a smartwatch assistant. Help users manage their schedule and answer health questions."
}

POST /api/openapi/spaces/{spaceId}/drive/upload
Authorization: Bearer <your-api-key>
Content-Type: multipart/form-data

file=<your-document>

POST /api/openapi/spaces/{spaceId}/agents/{agentId}/chat
Authorization: Bearer <your-api-key>

{
  "sessionId": "device-user-001",
  "message": "What's the weather like today?"
}

Billing model

Typical model:

• You buy Spaces from Buda (volume pricing available)
• You charge your end users a subscription or activation fee
• The margin is yours

Why hardware teams care

For hardware companies, this changes the cost structure:

• No need to ship a device powerful enough to run a full AI stack locally
• No need to keep a user's laptop or phone acting as the primary runtime
• No need to maintain a separate AI backend team just to support one device line

Your hardware can stay lightweight while the AI capability keeps improving in the cloud.

Analogy: ChatGPT vs OpenAI

The difference: Buda OpenAPI isn't just model inference — it provides a complete Agent runtime including knowledge base, session management, and tool-calling capabilities.

Why not OpenClaw?

OpenClaw is a great open-source AI Agent project — perfect for individuals who want to self-host an assistant on their own machine. But for hardware or software developers who need to scale, it's the wrong tool.

For a full comparison, see: Buda vs OpenClaw

In one line: OpenClaw is a tool for personal use. Buda is infrastructure developers sell to their users.

If you need to give 100,000 smartwatches each their own AI assistant, you need Buda — not a separate OpenClaw instance running behind every device.

FAQ

Do end users need a Buda account? No. End users have no visibility into Buda. Your product proxies all interactions through the API.

Does the Agent consume resources when idle? No. The Agent sleeps when there are no active conversations and wakes automatically when a message arrives.

Can I configure different Agent instructions for different users? Yes. Each Space has its own independent Agent configuration. Create separate Spaces and Agents per user as needed.