Wherobots

What is Wherobots? It's a question we get asked sometimes, so we wanted to make it super easy to understand. That's why we created this handy explainer video. Check it out here 👇

2024 has been an incredible year for Wherobots! We expanded our team, introduced a host of new features, welcomed numerous new customers, and, most importantly, stayed true to our vision. Remember that our vision is: "Planet Earth generates an immense volume of signals every second, captured by personal devices, autonomous vehicles, satellites, location-based services and more. Our vision is to empower organizations to effortlessly harness these signals, transforming them into actionable insights that drive daily decisions and strategies—impacting businesses, society, and human lives for a smarter, more connected world." Here is to more success in 2025!

Don't miss out on the upcoming #GeospatialRiskSummit! Our very own Daniel Smith will lead a session on cloud-native insurance risk concentration analysis. Learn how to manage portfolio risk in the face of increasingly frequent extreme weather events. 🌎🔥 https://lnkd.in/gvqFntRE

🎊 Please join us in welcoming Dewey Dunnington as our newest Senior Software Engineer! Here’s a little more about him: "Spatial is what got me started programming and anybody that has ever seen my office will tell you that I love maps more than just about anything. For the past three years I had the amazing opportunity to live and breathe Apache Arrow but never had time to work on the spatial projects that brought me to programming in the first place. Wherobots embodies the magic of a modern Arrow-powered composable data system with the obvious focus on spatial; I couldn’t be happier to be joining their amazing team."

🎉 We're excited to welcome Matthew Powers, CFA as our new Staff Developer Relations Engineer! Matthew joins us from Databricks, and he’ll be working closely with the Apache Sedona community. Here’s a little more about him: "I’m a long-time contributor, blogger, and OSS developer in the Spark and Dask communities, and I’m excited to introduce Sedona to the Spark ecosystem! I originally worked in finance, but taught myself how to code and transitioned to data engineering. I’m looking forward to deepening my knowledge of geospatial data, understanding common production workloads, and helping grow the Sedona community of contributors and users."

Missed our session at AWS re:Invent? Here’s the TLDR: 🛰️ Inferring objects and detecting change in satellite imagery was once reserved for companies with the resources to build and manage complex ML inference solutions. 🖥️ Raster Inference is a fully managed computer vision solution built for planetary-scale imagery. - Pick the model you want or bring your own. - Optimized for raster ETL and computer vision. - On-demand, low-cost inference. - Enrich inference results in line with your workflow. Raster Inference is now generally available! Reach out to us for more info or link in comments on how to get started. 👇 https://lnkd.in/gDYZ569b

🚲 If you want to really learn how to work with data, you need to work with messy data. This post from Zhengpei Luo does a great job of showing this with the Citi Bike Dataset which is...messy. Here's why: 🤐 The data is stored in zipped directories (by year) or zipped CSVs by month (but just for 2015 and forward). 😡 The dataset changes schemas 3 times and in the final update the point is tied to the exact pickup location, not the station location. Plus there is a lot of data: 53,083,660 total trips. But here is the data for you to check out! This is just a sample of trips in June 2024 that I processed in Wherobots! #gis #moderngis #geospatial #spatialanalytics #spatialsql #duckdb #wherobots

🌍 Exciting news! WherobotsAI Raster Inference is Generally Available! 🔍 What is it? A planetary-scale computer vision solution that extracts insights from aerial imagery at scale. What's in GA? 🚀 Wherobots-hosted Models: Choose from our optimized, ready-to-use computer vision models to analyze aerial data 💫  Bring Your Own Model: Easily port in your own models and leverage our inference pipeline to get to critical data insights faster 🏎️ Fast Performance: We've made our already fast inference even faster with async data loading ⚡ Effortlessly Scale: Deploy a scalable, serverless inference pipeline that seamlessly scales with increasing workload needs. 💡 Why it matters: Easily extract information at scale from noisy overhead imagery data with a geospatial optimized computer vision platform. Read more about it on our blog: https://bit.ly/3VErLRy On Business Wire: https://lnkd.in/gfbWA4X4 #WherobotsAI #RasterInference #ComputerVision #GeospatialAI #DataScience

🌍 In today’s data-driven world, geospatial data is being collected at an unprecedented scale, yet traditional data lakes and warehouses struggle to manage its complexity. From GPS locations to satellite imagery to IoT sensor data, Havasu is Wherobots' spatial data lakehouse solution. Based on Apache Iceberg, it's designed to help organizations: ✔️ Achieve performance at scale ✔️ Store massive volumes efficiently ✔️ Streamline data management 🔓 Learn how Havasu bridges the gap, enabling organizations to unlock the full potential of their geospatial data with ease and efficiency. https://bit.ly/4gzq5AE

Check out the recap of the GeoParty we hosted with CARTO at #AWSreInvent last week! 👀🌍🎉