Datawheel

What Datawheel does

• Builds national and regional open data platforms and observatories.
• Develops interactive visualizations and dashboards that make large datasets easy to explore.
• Applies economic complexity methods to reveal diversification opportunities and growth paths.
• Creates AI-powered tools and agents that answer questions using real data.
• Supports teams with training, capacity building, and open-source tooling.

Who Datawheel works with

Datawheel works with:

• National and regional governments.
• Ministries of economy and development agencies.
• International organizations and development banks.
• Research institutions and nonprofits that rely on economic and social data.

Background and expertise

Datawheel grew out of early work visualizing trade and economic networks, which led to the creation of the Observatory of Economic Complexity (OEC). The team combines expertise in:

• Economic complexity and development economics.
• Data integration and engineering.
• Information design and user experience.
• Machine learning, AI, and forecasting.

The company has contributed to well-known platforms such as the OEC, DataUSA, DataMexico, DataSaudi, and other national and regional observatories.

• Predictive models – simulate the impact of economic, trade, or policy changes, helping stakeholders evaluate scenarios and prepare for different futures.
• Optimization tools – use advanced algorithms to identify efficient strategies, such as reallocating investments, reducing dependencies, or improving diversification.
• Supply chain analysis – map and visualize supply chains to show how shocks, agreements, or policy changes affect specific products, sectors, or regions.
• Market potential tools – combine machine learning with trade and economic data to identify promising products, markets, or sectors for investment and export.
• Granular data creation – use machine learning to generate high-resolution datasets where only sparse or aggregated data is available, enabling more detailed analysis.
• LLM-enabled tools – integrate large language models into platforms so users can query and interpret data through natural language.

Example applications

Examples of how these capabilities have been applied include:

• Analyzing the impact of tariff changes to help countries identify new export opportunities.
• Building tools that recommend export strategies based on economic complexity and cost considerations.
• Creating interactive visualizations that show the structure of supply chains and the effect of new trade agreements.
• Developing market analysis tools that highlight high-potential industries and products.

These projects are tailored to each client's data, policy questions, and decision-making context.

Datawheel designs and operates data-driven games that make complex datasets engaging for broad audiences. These games turn trade and economic data into interactive challenges that encourage learning, discussion, and community building.

Why data gamification

• Engagement – games spark curiosity and make exploring data enjoyable.
• Community – shared challenges and leaderboards connect people around data and friendly competition.
• Learning – games lower barriers to topics like trade and economic geography, making them accessible to students and non-specialists.

Examples of games

Examples of games associated with Datawheel's work include:

• Tradle – a daily game where players guess a country from a treemap of its exports.
• Pick5 – a challenge to guess the top exporters of a given product and see how much of global market share they represent.
• Connectrade – a game focused on the connectivity of the global economy and the product links between countries.
• Export Hold'em – a card-style game where players identify a mystery country by gradually revealing its export portfolio.
• Trade Swipe – a fast-paced game where players decide if a product–country pair matches real export data.
• Pantheon Trivia and related titles – additional games that use data as the basis for quizzes and challenges.

Reach and impact

These games have attracted large online audiences, with millions of sessions and hundreds of thousands of active users. They are used by:

• Teachers and instructors who incorporate them into lessons.
• Offices and teams that adopt them as informal daily challenges.
• Online communities that organize tournaments and competitions.

For institutions, data gamification offers a way to build sustained interest and participation around data-driven topics.

Datawheel builds high-end data distribution platforms that combine visualization, analytics, forecasting, and AI into a single experience. These platforms are designed for organizations that manage large public or institutional datasets and want to make them accessible and actionable.

Key capabilities

• Interactive visualizations – charts, maps, dashboards, and other views that help users explore complex datasets.
• Analytics – tools to track indicators, spot trends, and compare regions, sectors, or time periods.
• Forecasting – AI-informed forecasting tools that anticipate future trends and help identify opportunities and risks.
• AI chat with data – natural-language interfaces that let users ask questions directly against curated datasets.
• Games and engagement – optional data-driven games that attract and educate users while increasing platform reach.
• SEO-optimized experiences – platforms are designed to be discoverable through search engines and accessible to broad audiences.

Technology approach

Datawheel's platforms are built on a license-free, open-source stack and can be deployed on a client's cloud or on-premise infrastructure. Typical features include:

• A low-code content management system (CMS) to manage pages and narratives.
• Dynamic APIs that serve data and power custom visualizations and tools.
• Configurable templates that can generate large numbers of pages or reports from underlying datasets.

Example platforms

Examples of data platforms and observatories that use Datawheel's technology and expertise include:

• DataUSA – a leading platform for exploring and visualizing U.S. public data.
• DataMexico – the flagship data distribution tool of Mexico's Secretary of Economy.
• DataSaudi – a unified platform for economic and social data for the Kingdom of Saudi Arabia.
• Observatorio SEBRAE / DataMPE – platforms focused on small and medium businesses in Brazil.
• Spain Complexity and related observatories – platforms focused on export performance and economic complexity.

These implementations illustrate how Datawheel adapts its stack to different countries, regions, and institutional needs.

Offices

• North America office

1299 Cambridge Street Boston, MA 02139 USA

• Latin America office

Arturo Prat 390, Of. 1005 Concepción Chile

Team contacts

Selected contact points listed on the website include:

• Cota Pincheira – Client Experience and Backoffice – Cota@datawheel.us
• David Anabalón – Marketing Lead – David@datawheel.us

For new projects or collaborations, organizations typically reach out via the main email address or the contact form so the message can be directed to the appropriate team.

• Reveal what an economy is well-positioned to produce next based on its current capabilities.
• Identify high-potential industries and products that align with existing strengths.
• Map diversification pathways and related opportunities across sectors and regions.
• Provide evidence to support industrial policy, trade strategy, and development planning.

Data and methods

Economic Complexity reports typically combine:

• International trade data.
• Labor and skills data.
• Innovation and technology indicators where available.

These inputs are analyzed using economic complexity metrics and complementary methods to build a forward-looking view of potential growth.

Outputs and use cases

The reports are tailored to the client and may include:

• Narrative analyses for policymakers and stakeholders.
• Visualizations that show product spaces, opportunity maps, and regional strengths.
• Practical recommendations to support policy design, investment promotion, and project prioritization.

They are used by governments, development agencies, and international organizations seeking to align policy and investment with long-term productive capabilities.

The Observatory of Economic Complexity is a widely used platform for exploring international trade and economic complexity data. It provides visual tools to understand what countries export, how diversified their economies are, and what products they are likely to move into next.

Datawheel's team helped create and develop the OEC and continues to build on its data and methods.

OEC BotMarket

OEC BotMarket is a data marketplace designed to ground AI agents in real data. It provides access to trusted datasets covering trade, economics, demographics, labor, health, and related topics so that AI agents can base their answers on factual information rather than fabricated numbers.

Thematic and national observatories

Datawheel also supports or powers platforms such as:

• CICE – a platform that maps industrial capabilities linked to clean energy leadership.
• Border Value – a site that highlights cross-border co-production in North America.
• DataUSA, DataMexico, DataSaudi, Observatorio SEBRAE / DataMPE, Spain Complexity – national and regional platforms that distribute economic and social data in accessible ways.

These platforms demonstrate how Datawheel adapts a common technology stack to different institutional and policy contexts.

Ask anyway — the agent will say plainly that it is not published rather than guess.