Introduction

Maps are some of the most critical pieces of infrastructure for human society and the global economy.

Billions of people around the world use mapping apps every day. Millions of organizations, from businesses to government agencies, rely on mapping APIs and services to support their operations. With every year that passes, more and more of the world's 1.5 billion vehicles use advanced technology features that demand richer map data than ever before.

Analysts estimate the mapping industry has a market size of $200B to $300B, including mapping apps and APIs, geospatial analytics, GIS, and map data collection.

But there's a problem.

Most of today's maps are built by deploying dedicated vehicles to collect high-quality, street-level imagery. That's expensive, so mapmaking is consolidated among the few companies with the capital to map roads at global scale. It means maps often don't reflect current realities on the ground.

And yet, most roads are driven every day. In the United States alone, humans drove 3.26 trillion miles in 2022, or 8.9 billion miles per day. So why can’t ordinary people, and ordinary cars, collect map data?

How Bee Maps Works: Built on the Hivemapper Network

Launched in 2022, Hivemapper is an open, decentralized global mapping network. Instead of relying on dedicated mapping fleets, Hivemapper turns everyday driving into fresh, street-level map data—and Bee Maps is built on top of this infrastructure to deliver enterprise-grade mapping products.

Map AI

At the core is Map AI—a purpose-built, AI-native mapping engine that transforms streams of road imagery into structured map data. This data powers autonomous robotaxis, logistics companies, and mapping services worldwide.

Map AI detects changes, interprets road features, identifies restrictions, and continuously updates the network with real-world accuracy at global scale. Every week, it processes millions of kilometers of imagery into fresh, usable map intelligence.

The Problems We’re Solving

Uneven coverage and freshness - Typical methods of collecting map data are very expensive, so even the best-funded companies struggle to refresh maps at global scale.

Fresher maps for autonomous and ADAS driving - Today's maps were made for humans. The maps required by autonomous and semi-autonomous vehicles require far fresher data.

Expensive for businesses - Millions of businesses pay to integrate maps into their products. With so few choices for reliable maps, monopoly pricing makes map data unaffordable.

Today's maps don't understand the "why" - When cars start to travel at 10 mph on a road they normally travel at 40 mph, modern maps don't know if this is due to road construction, a minor fender-bender or a severe crash that will take hours to clear. Even when a user reports an issue through an app, they cannot immediately trust the report without imagery.

This documentation helps you understand and implement Bee Maps products. Use the navigation to explore specific topics, or search for what you need.

Thank you for being a part of the future of maps.

– The Bee Maps Team