{"id":17022,"date":"2026-05-19T21:58:56","date_gmt":"2026-05-19T13:58:56","guid":{"rendered":"https:\/\/wp-productionenv-bjg9h2g2bgg5b8aa.southeastasia-01.azurewebsites.net\/news\/terrabyte-raises-the-curtain-on-its-campaign-to-use-ai-to-unleash-the-power-of-geospatial-data\/"},"modified":"2026-05-19T21:58:56","modified_gmt":"2026-05-19T13:58:56","slug":"terrabyte-raises-the-curtain-on-its-campaign-to-use-ai-to-unleash-the-power-of-geospatial-data","status":"publish","type":"post","link":"https:\/\/starpath.global\/news\/terrabyte-raises-the-curtain-on-its-campaign-to-use-ai-to-unleash-the-power-of-geospatial-data\/","title":{"rendered":"TerraByte raises the curtain on its campaign to use AI to unleash the power of geospatial data"},"content":{"rendered":"
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A screenshot of TerraByte\u2019s software platform pinpoints cargo ships, warehouses, solar farms, mining sites and areas of deforestation. One complex query generated more than 2,000 results that can be further filtered. Click on the image for a larger version. (Credit: TerraByte AI)<\/figcaption><\/figure>\n

A stealthy Seattle startup called TerraByte AI is unveiling a software platform that uses artificial intelligence to sift through real-time satellite data for geospatial gems. <\/p>\n

TerraByte\u2019s \u201cEarth Search Engine\u201d analyzes streams of satellite imagery, recognizes features of interest and connects the dots through natural-language queries. The platform\u2019s key advantage is that its data set doesn\u2019t have to go through the laborious, expensive process of manual annotation.<\/p>\n

\u201cWe\u2019re just using self-supervised learning techniques to essentially understand the pixels without having to manually annotate it,\u201d CEO and co-founder Rishi Madhok told GeekWire.<\/p>\n

\u201cThere are many applications that you can do, like identifying power-line segments, finding parking lots near highways without EV charging stalls, watching container ships entering port,\u201d he explained. \u201cIf you want to monitor the Strait of Hormuz, you can use our models to do that. Deforestation areas, open-pit mining in Arizona \u2014 all of these are very different concepts, but our model is able to understand them because it\u2019s a foundational model.\u201d<\/p>\n

TerraByte is laying out its approach this week in Huntsville, Ala., at an ESA-NASA workshop on AI models for Earth observation. A hands-on session is scheduled on Wednesday, and the company\u2019s co-founder and chief technology officer, Fuxun Yu, is due to make an oral presentation on Thursday.<\/p>\n

Madhok and Yu founded TerraByte last year, with operations split between Seattle and San Francisco. Madhok previously led geospatial AI initiatives at Microsoft Planetary Computer, while Yu worked as a principal research manager at Microsoft and led the company\u2019s Geospatial Foundational Model project.<\/p>\n

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TerraByte AI\u2019s co-founders, Rishi Madhok and Fuxun Yu, are both Microsoft veterans. (TerraByte AI Photos)<\/figcaption><\/figure>\n

On the financial front, Madhok said the venture has received pre-seed funding from Ascend, PSL Ventures and angel investors, though he declined to specify the size of the investment. <\/p>\n

Kirby Winfield, founding general partner of Ascend, said in an emailed statement that TerraByte \u201cis building the foundation model layer for satellite intelligence. \u2026 They\u2019re creating the foundational API and AI infrastructure that will power the next generation of location intelligence applications.\u201d<\/p>\n

Vivek Ladsariya, managing director at Pioneer Square Labs and general partner of PSL Ventures, said his fund invested in TerraByte \u201cbecause geospatial data is one of the most consequential and underserved categories in enterprise tech.\u201d<\/p>\n

\u201cThe volume of geospatial data is growing exponentially, yet most organizations still can\u2019t access or act on it effectively,\u201d Ladsariya said via email. \u201cRishi and Fuxun are rare operators \u2014 they\u2019ve lived this problem firsthand and know exactly what it takes to build the infrastructure layer that unlocks it. TerraByte is that layer, and we think it becomes foundational.\u201d<\/p>\n

While single-sensor foundation models already exist to analyze the wide spectrum of sensor data captured by satellite companies, Madhok noted that \u201cTerraByte is the first model layer to natively fuse optical, synthetic aperture radar, thermal and hyperspectral in one foundation model.\u201d That multi-sensor approach could support a rapid response to fast-changing situations such as natural disasters.<\/p>\n

\u201cFor example, we can work with utility companies or even with first responders, and when there\u2019s a wildfire, they can ask for things like, \u2018Show me neighborhoods and power-line segments within one mile of an active wildfire in California or Washington,’\u201d Madhok said. \u201cBecause when catastrophes happen, you need to be able to monitor them instantly in real time, and there aren\u2019t a lot of technologies out there which can actually give them the insights.\u201d<\/p>\n

Risk assessment is another potential application \u2014 for example, addressing the challenges that insurance companies face in evaluating wildfire risk. \u201cIf they\u2019re able to characterize the risk well by understanding if there are high-risk things like vegetation encroachment, you\u2019re able to have better pricing on some of those things,\u201d he said. <\/p>\n

Madhok said the software could also be installed on orbiting satellites to filter data before it\u2019s downlinked. That could minimize the time delay and costs that might otherwise be associated with downlinking massive amounts of data from an Earth observation satellite or an orbital data center.<\/p>\n

\u201cOur goal is to build a model which not only works on the ground station, but also works on the edge, so that it helps all these time-sensitive applications to monitor things,\u201d Madhok said. He said the company is already working on arrangements for an on-orbit demonstration.<\/p>\n

While TerraByte is still refining its commercial strategy, the immediate focus is on enterprise clients. \u201cOur business startup use case is more focused on B2B, so we\u2019re working with large enterprise licenses, but eventually it will be subscription-based,\u201d Madhok said.<\/p>\n

TerraByte isn\u2019t the only company offering geospatial data analysis. Other players in the market include Google Earth Engine and BlackSky Spectra. Still more companies, such as Starcloud and Sophia Space, are working on plans to put computing power on the edge in space. Will TerraByte be able to compete?<\/p>\n

\u201cI see Sophia Space and a lot of similar companies who have compute up in space as partners,\u201d Madhok said. \u201cA lot of the companies out there, whether they\u2019re building satellites or collecting imagery, are really good at doing what they do \u2014 which is building satellites or sending computers up into space. Our DNA is to build the best geospatial models out there, and that\u2019s what our goal is.\u201d<\/p>\n","protected":false},"excerpt":{"rendered":"

A screenshot of TerraByte\u2019s software platform pinpoints cargo ships, warehouses, solar farms, mining sites and areas of deforestation. One complex query generated more than 2,000 results that can be further filtered. Click on the image for a larger version. (Credit: TerraByte AI) A stealthy Seattle startup called TerraByte AI is unveiling a software platform that […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":"","_links_to":"","_links_to_target":""},"categories":[2],"tags":[4349,3735,491,20,442,4329,4350],"class_list":["post-17022","post","type-post","status-publish","format-standard","hentry","category-news","tag-artifical-intelligence","tag-big-data","tag-edge-computing","tag-satellite","tag-satellites","tag-startups","tag-terrabyte-ai"],"acf":[],"_links":{"self":[{"href":"https:\/\/starpath.global\/blog\/wp-json\/wp\/v2\/posts\/17022"}],"collection":[{"href":"https:\/\/starpath.global\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/starpath.global\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/starpath.global\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/starpath.global\/blog\/wp-json\/wp\/v2\/comments?post=17022"}],"version-history":[{"count":0,"href":"https:\/\/starpath.global\/blog\/wp-json\/wp\/v2\/posts\/17022\/revisions"}],"wp:attachment":[{"href":"https:\/\/starpath.global\/blog\/wp-json\/wp\/v2\/media?parent=17022"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/starpath.global\/blog\/wp-json\/wp\/v2\/categories?post=17022"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/starpath.global\/blog\/wp-json\/wp\/v2\/tags?post=17022"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}