Bee Maps is a decentralized mapping application built on the Solana blockchain that aims to create dynamic, real-time maps by crowdsourcing street-level imagery. The project operates as a user-facing application on top of the Hivemapper network, one of the largest Decentralized Physical Infrastructure Networks (DePIN) focused on mapping data. ^[1]

Overview

Bee Maps was officially introduced on September 20, 2024, with the mission to build "The World’s Freshest Map." The project positions itself as a decentralized alternative to established, centralized mapping giants like Mapbox, TomTom, and HERE Technologies. Its core premise is that traditional mapping services suffer from data staleness, high operational costs, and limited coverage, as they rely on dedicated vehicle fleets to manually survey roads. Bee Maps aims to solve these issues by leveraging a global, decentralized network of contributors who collect data passively during their everyday drives. This model is intended to produce maps that are more current, accurate, and comprehensive. ^{[2] [3]}

The application is "powered by Hivemapper," utilizing its underlying protocol, contributor network, and blockchain infrastructure on Solana. ^[3] Based in San Francisco, CA, Bee Maps provides advanced, near-real-time street-level intelligence designed for developers and enterprise clients in sectors such as transportation, logistics, ridesharing, and automotive industries. The project emphasizes the role of artificial intelligence in processing the collected data, branding its product as being "Built by AI." ^[2]

In a statement about the geospatial technology landscape, the project highlighted its goal of fundamentally changing how navigation is experienced:

"It’s an exciting time for geospatial technology, particularly at the street level where innovation isn’t just about maps—it’s about reshaping how we experience and navigate the world around us." ^[3]

Technology

The technological foundation of Bee Maps combines a Decentralized Physical Infrastructure Network (DePIN) model for data collection with advanced artificial intelligence for data processing, all secured and incentivized through the Solana blockchain.

DePIN Model

Bee Maps operates on a DePIN model, which outsources the deployment and maintenance of physical infrastructure to a distributed global community. In this case, the infrastructure consists of AI-enabled dash cams installed in contributors' vehicles. This approach allows the network to scale its data collection capabilities far more rapidly and cost-effectively than a centralized entity could. Contributors, who are primarily everyday drivers, passively capture high-resolution, street-level imagery as they go about their normal routines. ^[1]

The hardware, described as "AI-powered dashcams," is designed to automatically detect and map real-time changes on roads. This includes identifying new road signs, temporary construction zones, detours, changes in speed limits, and other critical road features. By crowdsourcing this data from thousands of vehicles simultaneously, the network can achieve a high refresh rate, ensuring the map reflects on-the-ground reality with minimal delay. The underlying infrastructure for processing and storing this vast amount of data is the Hivemapper Network, which utilizes the high throughput and low transaction costs of the Solana blockchain. ^{[3] [1]}

AI Processing

Artificial intelligence is a critical component of the Bee Maps ecosystem, responsible for transforming raw visual data into structured, queryable map information. The project's tagline, "Built by AI," underscores the importance of machine learning models in its data pipeline. After the dash cams capture and upload imagery, AI algorithms automatically process it to identify, classify, and extract relevant map features. ^[2]

These AI models perform several key functions:

• Feature Extraction: Identifying and geolocating objects such as traffic lights, stop signs, speed limit signs, lane markings, and turn restrictions.
• Change Detection: Comparing newly collected imagery with existing map data to detect changes, such as a new building under construction or a recently closed road.
• Data Quality and Privacy: The AI is also responsible for ensuring data quality and protecting privacy. While specific details are outlined in its privacy policy, this typically involves automatically blurring sensitive information like faces and license plates from the collected imagery.
• Map Compilation: Stitching together processed data from multiple contributors to create a cohesive and seamless digital map layer.

This reliance on AI automation allows the network to process data at scale and maintain the freshness of its maps, a key differentiator from traditional services that often rely on manual annotation and verification. ^{[2] [1]}

Contributor Model

The success of the Bee Maps network is dependent on its global community of contributors. These participants, ranging from individual drivers to large vehicle fleets, are responsible for the primary task of data collection. By installing a network-approved AI dash cam in their vehicle, they contribute to building the map during their regular commutes and drives. ^[1]

To encourage participation and lower the barrier to entry, Bee Maps introduced a subscription-based "Bee Membership" plan. This model reduces the significant upfront hardware cost, which can be nearly $600, to a more accessible monthly fee of $19. The subscription includes the necessary hardware, software, and other benefits for contributors, making it easier for new users to join the network and begin earning rewards. The project offers different hardware versions tailored to specific regions, including the "Bee Membership" for contributors in the United States and the "Beekeeper LTE" for the global market, which likely includes cellular connectivity for seamless data uploads. ^{[2] [1]}

Contributors are incentivized for their efforts through token rewards. The system is designed to reward the submission of high-quality and valuable data, encouraging drivers to map unique or under-mapped areas. This creates a flywheel effect: as more contributors join, map coverage and freshness improve, which in turn attracts more data consumers and increases the value of the network and its rewards. ^[1]

Tokenomics

The Bee Maps ecosystem, through its integration with the Hivemapper Network, utilizes the HONEY token as its native utility and incentive token. The primary function of the HONEY token is to reward contributors for collecting and submitting valid street-level imagery. This incentive mechanism is the core driver of network growth, ensuring a continuous supply of fresh data to power the map. ^[1]

Rewards are distributed to contributors based on the quality, quantity, and novelty of the data they provide. For example, mapping a road that has not been recently surveyed or providing the first imagery of a new development would likely yield higher rewards than repeatedly driving a frequently mapped highway. This system encourages the expansion of the map into new territories and ensures that existing areas are kept up-to-date. The HONEY token serves as the economic engine that aligns the interests of contributors, data consumers, and the network itself, creating a self-sustaining and decentralized mapping economy. ^[1]

Funding

On October 6, 2025, it was announced that Bee Maps had raised $32 million in a funding round, marking one of the largest financings in the DePIN sector for that year. The round was co-led by Pantera Capital, LDA Capital, Borderless Capital, and Ajna Capital. ^[1]

The capital was allocated for several strategic purposes aimed at scaling the network's operations globally:

• Expanding Hardware Distribution: Accelerating the global deployment of data-collection devices to increase map coverage.
• Enhancing AI Models: Further developing the artificial intelligence pipeline to improve the speed and accuracy of map data processing.
• Boosting Contributor Incentives: Increasing the pool of HONEY tokens available to reward contributors and attract new participants.
• Scaling Network Infrastructure: Strengthening the overall technical infrastructure to support a larger volume of data and users.

Ariel Seidman, co-founder of Hivemapper, commented on the strategic importance of the funding, stating:

"With this funding, we are accelerating global device deployments, expanding coverage, and strengthening our AI pipeline. Demand is not the problem — supply is.” ^[1]

Partnerships and Customers

Since its launch, Bee Maps has secured several high-profile partnerships and customers, demonstrating early adoption of its technology by major players in the transportation and location services industries.

• Lyft: Announced as a customer on May 14, 2025, the ridesharing company integrated Bee Maps to access fresh, street-level spatial intelligence, aiming to enhance its mapping and navigation systems. ^{[3] [1]}
• Volkswagen ADMT: The automotive giant's autonomous driving division tapped Bee Maps for driverless vehicle data to support its robotaxi program. ^[1]
• Mapbox: An ongoing partnership with the location data platform for developers was announced on February 27, 2025. ^[3]
• TomTom: On February 19, 2025, a partnership was announced with the global leader in navigation technology. ^[3]
• Trimble (NASDAQ: TRMB): The global logistics and navigation systems company was announced as a customer on February 13, 2025. ^[3]

These collaborations underscore the demand for the real-time, detailed road data that the Bee Maps network is designed to provide. ^{[3] [1]}