At Felt, we’re creating the best place to make maps on the internet. We've reimagined what's possible with GIS technology by bringing the entire spatial stack into the browser and making it simple to deploy map tooling your whole team loves to use. Founded by Sam Hashemi, Felt puts design at the center of the user experience so every interaction is intuitive, delightful and performant. Whether your team is working with spreadsheets on the desktop or streaming terabytes from cloud sources, Felt makes it simple to build and deploy the maps, apps and dashboards that drive your business forward. Sign up today and join the growing community of innovators who've discovered the power of Felt.
External link for Felt
At Felt, we’re creating the best place to make maps on the internet. We've reimagined what's possible with GIS technology by bringing the entire spatial stack into the browser and making it simple to deploy map tooling your whole team loves to use. Founded by Sam Hashemi, Felt puts design at the center of the user experience so every interaction is intuitive, delightful and performant. Whether your team is working with spreadsheets on the desktop or streaming terabytes from cloud sources, Felt makes it simple to build and deploy the maps, apps and dashboards that drive your business forward. Sign up today and join the growing community of innovators who've discovered the power of Felt.
Oakland, California 94612, US
Felt reposted this
Felt is headed to Databricks Data + AI Summit in San Francisco. Excited to connect with the geospatial crowd and show what an AI-native GIS looks like. Stop by Booth 139 to say hi, check out the latest from Felt, or take on our team's favorite Felt GeoMatcher challenge. #DataAISummit
Felt is headed to Databricks Data + AI Summit in San Francisco. Excited to connect with the geospatial crowd and show what an AI-native GIS looks like. Stop by Booth 139 to say hi, check out the latest from Felt, or take on our team's favorite Felt GeoMatcher challenge. #DataAISummit
Felt reposted this
When we started Felt, we had one mission: make mapping effortless for everyone. Not just for the specialists who'd spent years mastering desktop GIS, but for everyone. The operations manager with a question about service coverage. The analyst who needs to see risk geographically. The executive making a decision that has a "where" buried inside it. Today we're taking our biggest step yet toward that mission. Introducing Felt AI. Ask a question. Get a map. "Build me a map of California wildfire risk to my portfolio properties." The agent pulls your property data from Snowflake, validates and imports CalFire hazard zones from our Global Library, runs the spatial join, styles the result by risk tier, and hands you a live, shareable URL that's already governed by your workspace permissions. Then you keep going. "Now exclude the flood zones." "Add the demographics layer." "Why is this cluster ranked highest?" Every turn builds on the last. One conversational agent. Dozens of capabilities. 100M+ features rendering at interactive speed in the browser. Read-only by default, SSO and RBAC enforced, never trained on your data. This does two things at once. It puts powerful spatial analysis in the hands of anyone in your organization, with answers in seconds instead of a ticket in a queue. It also elevates the GIS team into the role they should have always had: the architects of how an entire organization thinks spatially. They build the infrastructure, connect the authoritative data, and set the cartography standards that everything else runs on. Felt AI answers questions against their work, so instead of fielding one-off map requests, they're building the platform that powers self-serve spatial intelligence across the company. The specialist's expertise doesn't shrink. It scales. Felt AI is available today. If your organization has spatial questions, and a GIS team ready to power the whole org, let's talk. 🌎
Spatial work just changed permanently 🗺️ For forty years, getting a spatial answer meant filing a request, waiting days, and hoping the question didn't change. Every other kind of knowledge work moved into chat. Spatial was the last holdout. ✨Today that changes with Felt AI. ✨ We spent the last year building a solution that lets you do more with spatial data and do it better. One conversational agent. Connected to your warehouse. Backed by the largest catalog of authoritative public geospatial data on the internet. Governed by the same SSO, RBAC, and audit logging your team already relies on. Now you can: → Go from a natural language question to a live, interactive map in minutes → Connect directly to Snowflake, BigQuery, Databricks, and Postgres → Run spatial analysis without writing a line of code or opening a desktop app → Give your entire organization self-serve access to spatial data → Let your GIS team focus on what actually requires their expertise Read more about how Felt AI is changing the way organizations work with spatial data. 🔗 Link to the blog is in the comments.
Spatial work just changed permanently 🗺️ For forty years, getting a spatial answer meant filing a request, waiting days, and hoping the question didn't change. Every other kind of knowledge work moved into chat. Spatial was the last holdout. ✨Today that changes with Felt AI. ✨ We spent the last year building a solution that lets you do more with spatial data and do it better. One conversational agent. Connected to your warehouse. Backed by the largest catalog of authoritative public geospatial data on the internet. Governed by the same SSO, RBAC, and audit logging your team already relies on. Now you can: → Go from a natural language question to a live, interactive map in minutes → Connect directly to Snowflake, BigQuery, Databricks, and Postgres → Run spatial analysis without writing a line of code or opening a desktop app → Give your entire organization self-serve access to spatial data → Let your GIS team focus on what actually requires their expertise Read more about how Felt AI is changing the way organizations work with spatial data. 🔗 Link to the blog is in the comments.
Felt reposted this
Are you involved in geosptial processing and heading to Databricks #DataAISummit? Me too! Check out these sessions: 1. Rivian + Databricks - https://lnkd.in/eMpUDhFm 2. Felt - https://lnkd.in/e3AggMHV 3. Databricks - https://lnkd.in/eSvEnZSH 4. S&P Global + Databricks - https://lnkd.in/epvY8xgy -- Additional -- 5. Virtue Foundation + Databricks - https://lnkd.in/euCZhhcU 6. Safe Software (FME) - https://lnkd.in/eh_hVfBw 7. Caltrans + Accenture - https://lnkd.in/ecekyY8z 8. Quantum Capital Group - https://lnkd.in/ebE9higH 9. Unifeye - The Databricks Experts- https://lnkd.in/ewSS_G9v Kent Marten | Sam Hashemi | Hubert Boguski | Chinmay Gupte | Filip Ilic | Don Murray | Duper Tong | Bianca Stratulat | Ian Brown
Raster datasets can tell us detailed stories about the world. But how do you make that data understandable? This CropScape Explorer uses Felt AI to break down USDA's Cropland Data Layer by region: from the glacial till soils driving Midwest corn production to California's irrigation-fed specialty crop mix. Explore each agricultural region to understand not just what's growing there, but why. Bring your data. Define your intent with a prompt. Get an interactive app your team can actually use. Click the link in the comments to see the CropScape Explorer.
5 ways to visualize raster data in Felt. → Image - display raw pixel values as-is → Color Range - map continuous values to a gradient → Categories - classify discrete pixel values → Hillshade - model light and shadow for terrain relief → Raster Algebra - compute new values from band math Same dataset. Completely different insight depending on what you're trying to show. See the full walkthrough of what you can do with your raster in the comments.
Felt reposted this
For forty years, spatial analysis has lived inside specialist software. Its own tools, its own file formats, its own team to wait on. Everyone else has had to work around it. We're changing this today and making spatial analysis more accessible to everyone. ⚡ The Felt MCP Server is live. One endpoint, 30 tools, and native support for Claude, ChatGPT, Gemini, Copilot, and more. Here's what that looks like in practice: → Your agent creates a map, connects to your Snowflake, BigQuery, or Databricks warehouse, reads the schema, writes the SQL itself, renders the result as a layer, styles it, and publishes a live URL with your workspace permissions already applied. All from a single prompt. → 30 tools covering the full spatial workflow: creating maps, importing data, writing dialect-aware SQL, running spatial analysis, styling layers, and sharing results. No pre-built workflows to set up. No scaffolding. The agent authors the analysis from scratch every time. → It's model-agnostic and cloud-native. Nothing to install, no local bridge to maintain. Whichever model your org runs on today, and whichever it picks up next, the spatial layer doesn't change. Now every AI agent in your stack has a full GIS behind it. And every person working with one does too! 🗺️ Find out what you can build with Felt MCP. Link in the comments. 👇
Making a map that's both accurate and readable can be a challenge. Label placement. Stroke-to-fill contrast. Halo colors that don't fight the basemap. Small things that add up fast. Felt builds cartographic best practices in as defaults, so the focus stays on the work, not the tool. Our very own Mamata Akella breaks it down. Link in comments.