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Planet Makes Its Geospatial Data Available Through Amazon SageMaker

SAN FRANCISCO--(BUSINESS WIRE)--Planet Labs PBC (NYSE: PL), a leading provider of daily data and insights about Earth, today announced it is making geospatial data available through Amazon SageMaker, a fully managed machine learning (ML) service from Amazon Web Services (AWS). Now, Planet data can be directly embedded into Amazon SageMaker, allowing data scientists and ML engineers to acquire and analyze global, daily satellite data. With this data, customers can train, test, and deploy ML models all within Amazon SageMaker.

Planet operates the largest constellation of earth observation satellites in the world, with the capacity to provide daily medium- and high-resolution imagery of Earth’s landmass every day. Planet is using AWS to better serve its customers who can now benefit from the simplicity and speed of Amazon SageMaker’s new geospatial ML capabilities to build, train, and deploy ML models using Planet’s geospatial data at up to 10x the speed. These enhanced capabilities create new opportunities for Planet customers to accelerate data access within geospatial tools and cloud platforms.

Due to the challenging work required to use geospatial data for ML, access to ML has historically been out of reach for many geospatial data customers. With Amazon SageMaker, customers can pull in their proprietary data sources, such as Planet satellite data, from Amazon Location Service and AWS Data Exchange. It’s a first of its kind partnership and the only on-demand, high cadence satellite imagery ML model training, inference, and visualization platform available in the market.

“Planet understands the challenges associated with ingesting and supplying mass volumes of data,” said Planet President Kevin Weil. “Using Amazon SageMaker, we can now offer ML capabilities with deep integrations of multiple datasets, and we look forward to developing and collaborating on complex models with our customers.”

“Building, training, and deploying ML models using geospatial data is a manual process for most organizations. The primary barrier is the lack of purpose-built capabilities for performing ML on these types of massive datasets,” said Kumar Chellapilla, GM AI Services at AWS. “Amazon SageMaker can help simplify and accelerate geospatial ML from months to minutes by enabling Planet customers to enrich their datasets, train geospatial models, visualize the results, and more. Together with Planet, we are excited to unlock the value of geospatial data for their customers and help them make accurate predictions.”

Purposely built for geospatial data, Amazon SageMaker geospatial ML capabilities offer easy to use tools to orchestrate data chunking and pre-processing operations for satellite imagery, creating web-based visualizations, and creating seamless scaling up for large datasets. The pre-built algorithms can reduce development to just a few days and one-click deployment to the cloud, freeing up customers' time.

Planet customers are invited to bring Planet data into the new Amazon SageMaker geospatial ML capabilities to provide early-stage feedback, beginning in December 2022. In November, Kevin Weil participated in a fireside chat at AWS re:Invent where he teamed up with AWS’s Kris Efland to discuss the opportunities of this work.

About Planet Labs PBC

Planet is a leading provider of global, daily satellite imagery and geospatial solutions. Planet is driven by a mission to image the world every day, and make change visible, accessible and actionable. Founded in 2010 by three NASA scientists, Planet designs, builds, and operates the largest Earth observation fleet of imaging satellites, capturing over 30 TB of data per day. Planet provides mission-critical data, advanced insights, and software solutions to over 800 customers, comprising the world’s leading agriculture, forestry, intelligence, education and finance companies and government agencies, enabling users to simply and effectively derive unique value from satellite imagery. Planet is a public benefit corporation trading on the New York Stock Exchange as PL. To learn more visit www.planet.com and follow us on Twitter.

Planet Labs PBC Forward-Looking Statements

Except for the historical information contained herein, the matters set forth in this press release are forward-looking statements within the meaning of the "safe harbor" provisions of the Private Securities Litigation Reform Act of 1995, including, but not limited to, Planet Labs PBC’s ability to capture market opportunity and realize any of the potential benefits from current or future product enhancements, new products, or strategic partnerships and customer collaborations. Forward-looking statements are based on Planet Labs PBC’s management’s beliefs, as well as assumptions made by, and information currently available to them. Because such statements are based on expectations as to future events and results and are not statements of fact, actual results may differ materially from those projected. Factors which may cause actual results to differ materially from current expectations include, but are not limited to the risk factors and other disclosures about Planet Labs PBC and its business included in Planet Labs PBC's periodic reports, proxy statements, and other disclosure materials filed from time to time with the Securities and Exchange Commission (SEC) which are available online at www.sec.gov, and on Planet Labs PBC's website at www.planet.com. All forward-looking statements reflect Planet Labs PBC’s beliefs and assumptions only as of the date such statements are made. Planet Labs PBC undertakes no obligation to update forward-looking statements to reflect future events or circumstances.

Contacts

Planet Press
Claire Bentley Dale
comms@planet.com

Planet Investor Relations
Chris Genualdi, Cleo Palmer-Poroner
ir@planet.com

Planet

NYSE:PL

Release Versions

Contacts

Planet Press
Claire Bentley Dale
comms@planet.com

Planet Investor Relations
Chris Genualdi, Cleo Palmer-Poroner
ir@planet.com

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