Espressif Systems (688018.SH) today introduced the Private AI Agents Platform, a self-hosted AI agent framework that IoT Device Makers can deploy directly in their cloud accounts. With the already-seen value of LLMs and AI agents, Device Makers are increasingly looking for a streamlined, production-ready platform that makes it easy for them to offer AI capabilities to their customers. This Private AI Agents Platform delivers exactly that — a turnkey, scalable and cost-optimized agent runtime designed to make multimodal, intelligent behavior easy to integrate into connected devices, companion apps and web dashboards. The Private AI Agents Platform is built upon AWS services and uses Amazon Bedrock foundation models providing the choice of models that works the best for the customer use-cases. 

“By giving Device Makers the ability to create and run AI agents privately in their own cloud, we’re ensuring that AI becomes as open, secure, and accessible as connectivity itself extending Espressif’s leadership from connectivity to intelligence.”, said Teo Swee Ann, CEO of Espressif Systems. 

Why It Matters

IoT device makers want products that can understand context, reason about events, and act autonomously. While cloud AI services provide the building blocks, building an agent runtime with full ownership — with orchestration, multimodal interaction, tooling connectors, and secure deployment — requires significant engineering effort. The Private AI Agents Platform removes this barrier by offering a fully integrated, ready-to-deploy stack engineered specifically for connected-device use cases. 

Key Differentiators

• Turnkey Agent Runtime: A complete, production-ready framework that eliminates the need for Device Makers to assemble their own agent backend on top of AWS Bedrock or other LLM providers. 

• Private & Self-Hosted: Deployed entirely within the customer’s AWS account, ensuring full data ownership, privacy, and regulatory compliance. 

• Optimized for IoT: Designed by Espressif to work seamlessly with microcontroller-based devices, mobile apps, and IoT workflows providing scalability at optimized cost — something generic agent frameworks are not optimized for. 

• Multimodal Interface: Native support for both text and voice interfaces to enable natural user experiences.
  

Addressed Use-Cases

• Voice-controlled devices with self-sufficient, multi-lingual and natural voice control such as appliances with one-way voice.
  

• Voice-enabled controllers, and toys for natural user interaction two-way voice communication.
  

• Device management assistants integrated into mobile or web apps to facilitate natural language user-experience for consumer.
  

• Customer support automation through contextual troubleshooting, direct communication with devices through MCP connectors and guidance using authoritative knowledge base from device makers.
  

Platform Highlights

A unified dashboard allows Device Makers to configure prompts, set up connectors, monitor usage, and manage deployed agents. Built-in MCP and Tool connectors and Knowledge Base extensions allow agents to interact securely with device APIs, cloud services, and enterprise systems and provide authoritative information to the customers. The platform includes usage analytics, LLM selection options, and developer SDKs to accelerate integration. Its modular and stateless architecture scales effortlessly across multiple devices, tenants, and agent types. The Private AI Agents Platform also works seamlessly with ESP RainMaker cloud platform, but it is not a mandatory requirement.