Smart Sensing and Edge AI Development

Smart sensing and AI

Unleash the power of the edge. We deliver value by collecting hard-to-obtain data from the physical world through our advanced custom sensing capabilities, then transforming it into actionable insights, decisions, and actions. This includes both real-time edge processing on interconnected devices as well as engaging devices as part of agentic AI ecosystems.

Agentic AI Ecosystems

Agentic AI systems are autonomous software agents that can sense their environment, make decisions, take actions, and learn from their experiences, all without requiring human intervention. These systems are proactive, adapting to new situations in real-time and optimizing their actions to achieve specific goals, such as reducing energy consumption in smart buildings. Agentic AI is transforming industries like healthcare, consumer products & retail, manufacturing, and smart cities, enabling more personalized customer experiences and automating complex processes. At Synapse, we specialize in designing agentic systems that seamlessly integrate with the nuances of hardware to unlock new opportunities leveraging first-party data and interactions with the physical world.

Novel sensors and sensor systems

We develop embedded systems to collect real time data from a wide range of sensors essential for application development in innovative technology such as AR/VR, activity tracking, fluidics, and electromagnetics. Utilizing sensor fusion algorithms, we develop everything from high volume, low cost, and low power wearable devices to highly sophisticated and specialized industrial systems.

HaptX gloves

Edge AI & algorithms

Our team designs embedded hardware and machine learning (ML) algorithms to complement one another by balancing tradeoffs between algorithm performance and other embedded design constraints. Our AI and algorithm expertise spans the entire ML development process, beginning with data collection, signal processing, and dataset management and moving on to selecting and training ML algorithms, synthesizing data to augment existing datasets, and deployment of edge AI models onto target embedded hardware.

weaving digital experiences