Ask and guide
Use natural language to define intent, request actions, and continue the analysis with workspace context.
GriidAi connects your spatial question, geospatial data, execution plan, supported GIS operations, expert review, maps, and outputs in one AI-guided workspace. Start with intent, stay involved in the method, and move from analysis to a result you can inspect and use.
See Spatial Analysis ↓GriidAi is an AI-guided geospatial workspace that connects data, spatial analysis, execution planning, human review, mapping, and outputs in one environment. Users can define a spatial question, work with geospatial data, review a proposed implementation plan, run supported analytical steps, inspect the results, and continue or export the analysis without treating every question as a completely separate GIS project.
The platform is designed to make spatial work easier to organize and repeat while keeping expert judgment inside the workflow.
Describe the location-based question, task, or analytical outcome you need.
Use data already in the workspace, upload your own, or discover relevant sources when supported.
GriidAi proposes an implementation plan using the selected data and supported geospatial operations.
Check the inputs, method, validation strategy, and expected outputs before execution.
Approve the analytical step and let the platform run the supported spatial operations.
Inspect the map, tables, statistics, intermediate outputs, and final analytical result.
Present the result on the map or export communication and analytical outputs for the next step.
Use the result, trusted data, and session context to continue the next question or related analysis.
GriidAi keeps the analytical conversation, working data, map, layers, attributes, and results in the same session so the next step can use the context already available in the workspace.
Use natural language to define intent, request actions, and continue the analysis with workspace context.
Inspect layers and analytical results on an interactive map with standard navigation and basemap controls.
Organize vector, raster, tabular, AOI, temporary, and result layers as the analysis grows.
Open attribute tables, select records, and inspect structural or spatial metadata where supported.
Work across stored chat sessions and reuse trusted data between sessions when appropriate.
When a supported analytical step requires execution, GriidAi can prepare an implementation plan that makes the proposed work visible before processing begins. Review the selected inputs, method, validation strategy, and expected output, then approve the step when it matches your intent.
This keeps the AI useful without turning spatial analysis into an unexplained black box.
Which layers, features, variables, or data objects will be used?
Which supported geospatial operation or analytical approach is proposed?
What checks should be applied before the result is accepted?
What result or file should the step produce?
Natural-language interaction is the entry point, not the analytical method by itself. GriidAi connects user intent to supported geospatial operations across multiple analysis families, then returns the results to the same workspace for review.
Geometry, proximity, selection, overlay, and feature-based analysis.
Raster calculations, visualization, and image-oriented analytical workflows.
Elevation and drainage-oriented workflows.
Route, nearest, access, and service-coverage questions.
Selection, filtering, and data inspection behind mapped features.
Bring your own geospatial data into the workspace, organize the layers used in the session, and work with data discovered for the question when supported. The platform keeps the data context close to the analysis so users can inspect the layers, attributes, metadata, and results as the workflow progresses.
Spatial outputs are easier to trust when users can see both the mapped result and the data behind it. GriidAi keeps analytical layers in the map workspace, lets users inspect attributes where relevant, and separates communication-ready map exports from analytical data exports.
Capture the current map view for communication or reporting.
Export analytical layers for continued work in other tools.
Review visible layers, attributes, selections, and metadata before export.
GriidAi is designed to help experts move faster without hiding the analytical choices that shape the result. The user defines the intent, reviews the proposed plan, approves supported execution steps, and validates the output before deciding how it should be used.
For geospatial work, this matters because projections, units, joins, time windows, topology, data quality, and analytical assumptions can all change the meaning of a result.
Show the intended inputs, method, checks, and output before supported execution.
People review and approve supported execution steps while retaining responsibility for expert judgment.
Keep source layers and analytical context visible in the workspace.
Use maps, tables, statistics, and validation steps to review outcomes.
If a result is not suitable, revise the request, inputs, or method and run the next step.
The value of the platform becomes clearer when several data and analytical steps are connected around a real question.
Turn elevation data into drainage and stream-network analysis.
Explore example ↗ExampleUse satellite imagery to examine vegetation condition.
Explore example ↗ExampleIdentify service coverage and areas that may be underserved.
Explore example ↗ExampleExplore how different water-level scenarios affect exposed locations.
Explore example ↗GriidAi stores chat sessions and keeps session-specific layers and results organized so users can work through multiple lines of analysis. Trusted data can also be shared between sessions, reducing repeated upload and helping separate data-preparation work from later business questions.
Spatial analysis should not depend on writing every instruction in one language. GriidAi has demonstrated text-based interaction in multiple languages while keeping the requested spatial action consistent across the workspace.
Zoom to a building layer.
Open the building attribute table.
Request minimum and maximum values from an uploaded raster.
Use AI guidance to organize and accelerate analytical work while retaining control of the method.
Turn repeated project methods into more consistent, reviewable workflows and outputs.
Explore geospatial questions, data, and analysis in a visible workspace.
Create a more repeatable path from request to reviewed spatial output.
Use bounded, guided spatial workflows for questions that depend on location.
Start with the data you have, define the analysis you need, review the plan, and use GriidAi to move from spatial question to an inspectable result.