General AIoT Deployment
Not every use case fits a predefined industry template. Hubosmart is designed as a composable platform — teams across sectors use it to build custom AI-powered products, internal tools, and client-facing solutions without starting from scratch.
Who This Is For
- Hardware product teams building AI features into devices without dedicated ML staff
- Systems integrators delivering AI-enabled solutions across multiple client industries
- Enterprise IT teams rolling out visual sensing capabilities to distributed facilities
- Startups building edge AI products who need to iterate quickly with limited engineering resources
Platform Capabilities at a Glance
Custom model creation
Train on your own data for your specific domain. No generic pretrained model assumptions — your training data defines what the model recognizes.
Flexible deployment options
Choose the deployment path that matches your distribution model: hot-swap for prototyping, personal SDK for individual product distribution, or enterprise batch for large-scale fleet deployment.
Agent Workflow for intelligent automation
Connect edge inference outputs to LLM-powered decision logic using the LLM-CJSON-OPENCLAW workflow. Build agents that respond to what the model sees — sending notifications, triggering external APIs, or driving actuators — without custom firmware development.
Credit-based authorization model
SDK keys are issued on a credit basis, allowing teams to manage distribution costs predictably and revoke access when needed.
Common Use Cases
| Use Case | Deployment Path | Workflow |
|---|---|---|
| Prototype and internal validation | Hot-Swap | Manual review |
| Independent developer product | Personal SDK | Agent Workflow for event routing |
| Multi-site enterprise rollout | Enterprise Batch | Agent Workflow + external integrations |
| OEM hardware with custom AI | Enterprise Batch | Embedded, customer-specific |
Integration Philosophy
Hubosmart does not require replacing existing infrastructure. The Agent Workflow layer is designed to connect to external systems — messaging platforms, dashboards, ERP, SCADA — through standard interfaces, so edge AI events flow into the tools your team already uses.