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The flexible solution to develop and scale your own custom maps.

Use Cases

Proprietary HD Maps

Rapidly develop, easily update, and efficiently scale proprietary HD Maps. Improve simultaneous localization and mapping (SLAM) models to enhance autonomous driving systems and develop efficient navigation and routing.

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    HD Maps

  • prediction and motion planning

    Prediction & Motion Planning

  • map feature detection

    Map Feature Detection

  • navigation planning

    Navigation Planning

How It Works

Easy to Start, Optimize, and Scale

Build better models faster with data you can trust. Maximize operational efficiency and productivity while reducing the cost of ML projects.

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    Your Maps, Your Way

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    Multi-Sensor Support

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    Comprehensive Labeling

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    High Quality at Speed

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    Change Detection & Updates

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    Automated Quality Pipeline

“We really value our partnership with Scale and their ability to deliver custom workflows that suit our needs across a variety of mapping and deep learning models. Scale's high-quality, rapidly labeled data will enable us to ramp our map expansion, allowing us to provide more service to customers like Dominos.”

Eleonor Concepcion

Software Operations Program Manager, Nuro

Enterprise Ready

Custom Annual Plans and SLAs

Get started today with on-demand, or chat with us about an enterprise plan.

  • Guaranteed Task Completion Time

    Enterprise-grade SLAs include task completion times and tasks can be rapidly scaled up and down to meet your requirements.

  • 24/7 Development Support

    Each enterprise customer is paired with a dedicated engagement manager who will ensure smooth on-boarding and continued data delivery.

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  • Cost Effective

    Enterprise engagements provide upfront and volume-based discounts, and is the most cost-effective solution for high-quality labels. Plus with Scale AI, there are no platform fees.

Quality Assurance

Best-In-Class Quality Choice

Industry leading quality datasets safe-guarded against ever-changing, messy data.

Super Human Quality

Mapping tasks submitted to the platform are first broken down into tiles to maximize labeling efficiency. Areas with insufficient data are marked as no data zones before the base vector annotations are added within the annotatable region. Semantic annotations are then layered on before relationships between annotations are established with linking. Once vector, semantic, and linking annotations are complete, tasks are stitched back together to create a comprehensive map.

A more cost effective approach to HD map labeling, this task workflow guarantees industry-leading quality at speed.

Scale's DashboardScale's Dashboard


Trusted by World Class Companies

Scale Mapping is trusted by leading machine learning teams to develop more accurate models.

  • microsoft
  • faire
  • brex
  • etsy
  • general-motors
  • flexport
  • instacart
  • blend
  • openai
  • paypal
  • sap
  • square
  • toyota
  • airforce
  • usarmy
  • irobot
  • lyft
  • linkedin
  • nuro
  • pinterest
  • skydio

Get Started Today