Latent AI

Founded 2018

Deploy and update machine learning models directly on edge devices and robotics hardware

Pricing model

Demo

You can use Latent AI to build, compress, and run machine learning models on physical hardware devices like drones, cameras, and industrial robotics. The system lets you pair your models with specific edge chips, automate hardware-level performance tuning, and run inferences without an active internet connection. You can also label training datasets with automated assistance, test model performance in disconnected environments, and deploy model updates remotely to entire hardware fleets. This reduces compute expenses and removes the need for round-the-clock cloud connectivity.

What Latent AI does

Compress machine learning models for low-power embedded processorsPackage models into secure runtime containers for edge deploymentPush over-the-air model updates to disconnected drone fleetsAnnotate visual training datasets with automated labeling toolsBenchmark model inference latency across different target chipsFine-tune computer vision architectures using domain-specific sensor dataLEIP Optimize automated hardware and software model compressionLEIP Deploy standardized runtime engine for edge hardwareLatent Agent plain-language chat interface for edge developmentLatent Field Tactical Suite for off-grid fleet updates on dronesLatent Assisted Label to automate training data annotationLEIP Design tool to select matching models and edge chipsPython API interface across the entire development pipelineCompletely offline inference execution without cloud dependence