FOR TECH PROVIDERES

Add on-device detection to your hardware.

Embed MAKRR's training and inference pipeline into your robotics, drone, or industrial product. Your customers train their own models. You own the deployment.

WHAT YOU GET

The full vision stack, ready to embed.

TRAINING PIPELINE

Customers train, your team stays out of it

Text and image-ref annotation, one-button training, 17 architecture choices. Hosted on your infrastructure or theirs.

EDGE INFERENCE

Up to 260 fps, sub-10ms latency

TensorRT-optimised models on Jetson Orin. Fits disconnected, mobile and air-gapped deployments. No cloud round-trip.

FLEET MANAGEMENT

Push updates to a fleet from one screen.

Device health, detection throughput and model versioning across every deployed camera, in one dashboard.

DIY-AI

Plug-and-Play Tech

01

STREAM IN

Upload or stream videos and images onto the platform.

02

ANNOTATE + TRAIN

Tag classes and train your model with one button.

03

DEPLOY ANYWHERE

Ship to any hardware — edge, on-prem or cloud.

04

MONITOR LIVE

Get detections and insights in real time, via API.


Frequently Asked Questions

  • No. The platform is designed for non-ML teams, but includes advanced settings for technical users who want custom training parameters, augmentations, or API integrations.

  • MAKRR is hardware-agnostic. It works with IP, industrial and USB cameras, embedded sensors, and footage exported from robots or drones. If your system streams or exports standard video, you can likely use it.

  • Yes to all. Edge deployment supports fully air-gapped environments — MAKRR can run completely offline.

  • Yes, our edge deployment option will support fully air-gapped environments.

  • +

    It depends on object complexity, variation and lighting. With guided labelling, teams often start with a few hundred labelled frames per class, then add edge cases from real operations. Built for continuous improvement, not a one-shot dataset.

Embed the Stack.

Bring vision AI to your hardware without building it from scratch.