Distributed AI RealTime Framework
A powerful framework that intelligently combines on-device and cloud processing for real-time AI applications. Designed for use cases like robotics, gaming, AR, IoT, and mobile where latency, privacy, cost control, and offline capabilities are critical.
Easily create AI pipelines such as speech-to-speech or vision pipelines by distributing processing between device and cloud based on your specific needs - whether that's minimizing latency, controlling costs, ensuring privacy, or enabling offline functionality.
Simple API and Extensible
Clean, intuitive API that makes it easy to build complex AI pipelines while remaining highly extensible.
Performant C++ Implementation
High-performance C++ core ensures minimal latency and efficient resource utilization.
Multiplatform
Works seamlessly across mobile, desktop, IoT devices, and cloud infrastructure.
Multimodal
Built-in support for audio, video, and other data modalities for rich interactive experiences.
Cost Control
Optimize costs by intelligently distributing processing between device and cloud.
Privacy First
Keep sensitive data on-device while leveraging cloud for complex processing when needed.
Why Distributed?
Latency Optimization
Process time-critical tasks on device, offload heavy computation to cloud
Cost Control
Reduce cloud API costs by handling routine tasks locally and only using cloud for complex reasoning
Privacy
Keep sensitive data on device while still leveraging cloud capabilities
Offline Capable
Core functionality works even in poor connectivity or completely offline
Use Cases
Gaming NPCs
Engaging, conversational NPCs for games running STT and TTS on device for privacy and lower costs.
Generative Gaming
Games that adapt dynamically based on user voice or actions in the world.
Vision Pipelines
Vision algorithms combining fast detection on device triggering advanced cloud algorithms.
AR World Description
Describe the world for AR use cases with real-time multimodal processing.
Low Bandwidth Networks
Work in ultralow bandwidth & unreliable networks by doing STT locally.
Robotics
Smart robots that process critical tasks locally while offloading complex reasoning to the cloud.
Architecture
The framework provides a unified API to create processing pipelines that seamlessly distribute work between device and cloud:
Built on a high-performance C++ core with bindings for multiple platforms, ensuring consistent behavior and minimal overhead across devices.
Get Early Access
The Distributed RealTime Framework is currently in beta. Contact us to learn more and get early access.
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