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See.Think.Act.Learn.

Sidekick Robotics develops self-improving robots that can see, think, and act with increasing precision, in real time.

Here's a look under the hood

Technology

Machine Learning at the Core

Long-Horizon Dexterous Reasoning™

Multi-step task planning and execution

LHDR™Task 1Task 2Task 3Task 4Task 5

At the center of Sidekick's platform is Long-Horizon Dexterous Reasoning™, a new learning approach that enables robots to perform complex, multi-step workflows in the real world.

By autonomously learning to do and undo each task, Sidekick reaches human-level reliability for long-horizon physical work with only a small set of expert demonstrations. Sidekick learns directly from visual demonstrations, translating perception into purposeful motion.

Vision-Language-Action Integration

Vision-Language-Action Architecture

End-to-end transformer-based control

VisionLanguageTransformerAction

VLAs are transformer-based advanced language models trained on images and robotic actions that demonstrate impressive generalized performance.

We connect our algorithm with a VLA to upgrade its performance to the 95%+ task effectiveness enterprises expect.

End-to-End Visuomotor Learning

Perception to Action Pipeline

Real-time visual feedback and motor control

PerceptionNeural ProcessingMotor ControlContinuous Feedback Loop

Sidekick's algorithm learns directly from pixels to physical motion using convolutional neural networks, integrating perception, reasoning, and control into a single adaptive model.

During operation, that same model observes, predicts, and evaluates its own performance, creating a closed feedback loop that strengthens over time.

Continuous Learning Loop

Continuous Improvement Cycle

Fleet-wide learning and optimization

DeployCollectLearnImproveFleetLearningPerformance Over Time →

Every deployment makes Sidekick smarter. Demonstrations and real-world feedback feed into a continuous learning pipeline that refines models over time, improving accuracy, dexterity, and reliability with each new task performed.

State-of-the-Art Compute

Edge AI Computing Architecture

High-performance embedded AI hardware

High-PerformanceEmbedded AIMillisecond-LevelResponse TimeEdge ProcessingLocal Inference

Built for embedded AI performance, Sidekick executes vision and control pipelines locally, combining high-resolution perception with millisecond-level manipulation.

This enables enterprise-grade autonomy in compact, everyday environments, without depending on cloud connectivity.

Product Value

Fully Autonomous — So You Can Free Up Labor for Higher-Value Work

Once deployed, Sidekick operates independently, managing repetitive physical workflows end-to-end, allowing human teams to focus on care, creativity, and connection.

Mobility + Dexterity

Sidekick combines mobile autonomy with dexterous manipulation — giving it the range to navigate real spaces and the finesse to handle complex, delicate physical work.

Gets Better Over Time

Each deployment strengthens the Sidekick AI model, creating a compounding improvement cycle across the fleet.

Designed for the Real World

Starting with the on-premises laundry room in healthcare, Sidekick addresses the growing gap between physical labor demand and human availability — and scales across where physical work is most needed.

Our Belief

We believe that AI shouldn't just write, but it should work in the real world.

Learn more about our work