Felt provides a cloud‑native GIS platform that lets users upload, visualize, and analyze spatial data without data wrangling. The platform offers web GIS, dashboards, app development tools, and AI‑assisted spatial engineering, integrating directly with cloud data sources such as Postgres, Snowflake, and BigQuery. Felt monetizes through subscription plans that grant access to its mapping, analytics, and collaboration features, with tiered pricing for enterprise security and extended capabilities.
Funding
$19.5M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Organizations struggle to visualize and analyze geospatial data effectively due to the complexities of data wrangling, fragmented data sources, and the need for specialized GIS software. This often leads to delayed insights and bottlenecks in operational workflows.
Solution
Felt is a cloud-native GIS platform designed to simplify geospatial data visualization and analysis. It allows users to upload and visualize data in various formats without requiring data wrangling. The platform seamlessly integrates with databases like Postgres and Snowflake, ensuring teams work from a single, up-to-date source of truth. Felt also provides tools to build interactive dashboards, empowering teams to gain operational insights with fewer development bottlenecks.
Target Audience
Felt targets cities and governments, the energy and utilities sector, climate and natural resources organizations, the transportation industry, spatial intelligence firms, educational institutions, and anyone who needs mapping capabilities.
Features
- Upload Anything: Supports drag-and-drop functionality for various file formats, automatically geocoding street addresses and parsing geometry columns.
- Database Integration: Connects to Postgres, Snowflake, BigQuery, Databricks, Redshift, S3, ESRI, and STAC for real-time data updates.
- Interactive Dashboards: Enables users to visualize and chart data across time series, filter categories, build histograms, and highlight statistics.
- Python SDK and QGIS Plugin: Allows users to build feature-rich geospatial applications.
- Spatial Transformations: Provides tools to highlight spatial patterns and relationships in data.
- Data Exports: Supports exporting data in GeoJSON, GeoPackage, and GeoTIFF formats.
- Permission Control: Offers fine-grained control over who can access maps and data.
- Automatic Legends: Generates interactive legends for any data added to the map.