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Autonomous Driving

Ground Truth Datasets for Autonomous Vehicles

All the software, expertise, and annotators you need for vehicle perception models

Get to production faster with Mighty AI

Purpose-Built Platform

Secure cloud-based annotation tools for autonomous vehicle perception data

Proprietary Quality System

The industry’s first quantitative quality measurements of annotated ground truth datasets

Industry-Proven Workflows

A library of automotive workflow templates for a variety of scene understanding needs

Worldwide Annotator Community

Globally trained annotators who specialize in autonomous vehicle perception data

A Complete Suite of Annotation Tools

Detection and localization

Polygons for road boundaries, road markings, and Botts’ dots

Cuboids for vehicles and side panels

Categorizations for destination path, next road, weather, traffic, pedestrians, speed, topology, and danger

Classifications on object saliency and visibility

Directional commands for driving scenes

Associations for body and head orientation metadata

Key point annotations for pedestrian joints

Segmentation masks

and more





How It Works

With Mighty AI’s platform for autonomous vehicles, customers can achieve faster time to market, with confidence in the integrity of their data.


Define Success and Criteria

You set project goals, annotation specs, gold standards, and velocity needs. The rest is on Mighty AI.


Design the Project

Mighty AI builds the tasks and configures the workflows to meet your needs. You send data securely via API, hard drive, direct connect, email batches—whatever works for you.


Launch on the Platform

Mighty AI distributes tasks to annotators who specialize in autonomous driving data to produce accurate results.


Analyze in Real Time

Using the Mighty AI customer portal, you monitor task velocity and analytics in real time.


Optimize and Scale

Once the annotations have passed our quality checks (always calibrated against your specs), they’re delivered back in your preferred format. Success is evaluated and everyone smiles.

Watch our annotation process