Vector
Buffer, intersect, overlay, selection, clipping, proximity.
AI-GUIDED. EXPERT-REVIEWED.
Agentic GeoAI that keeps experts in control.
GriidAi turns a spatial question into an inspectable plan, coordinates supported geospatial operations, waits for your review, executes the approved steps, and returns results you can validate and use.
AI-guided execution. Human-reviewed spatial analysis.
THE CATEGORY
What is Agentic GeoAI?
Agentic GeoAI is an AI-guided approach to geospatial work in which a system can interpret a spatial question, organize the data and operations needed to address it, prepare a sequence of actions, and help carry the task through execution. In GriidAi, that process is designed to stay inspectable: users can review the proposed plan, approve supported analytical steps, and validate the outputs before using them in a decision.
The goal is not to replace spatial expertise with a single generated answer. It is to connect natural-language intent with explicit geospatial data, tools, calculations, maps, and review checkpoints inside one working environment.
How is Agentic GeoAI different from a GIS copilot?
A GIS copilot can help explain a tool, suggest a method, or generate a command. Agentic GeoAI goes further when it can connect that reasoning to an actual sequence of geospatial work - while still exposing the steps and requiring the appropriate review before execution.
Copilot capabilities vary by product. This comparison describes interaction patterns, rather than a universal distinction between products.
| Capability | GIS chatbot / copilot | GriidAi Agentic GeoAI |
|---|---|---|
| Understand a natural-language question | Yes | Yes |
| Use workspace context | Sometimes | Uses active session context and known data assets |
| Prepare a multi-step plan | May suggest steps | Generates an implementation plan for supported tasks |
| Execute GIS operations | May be limited or external | Coordinates supported spatial operations |
| Human review before execution | Not inherent | Core interaction pattern |
| Validate output | May summarize result | User inspects maps, tables, statistics, and outputs |
| Continue the workflow | Often conversational only | Continue from the resulting workspace state |
02 / HOW IT WORKS
From spatial intent to reviewed execution
GriidAi is designed around a sequence that keeps the user involved at the points where analytical judgment matters.
- 01
Ask
Describe the spatial question, outcome, or operation you want to perform.
- 02
Context
Use the data and map state already available in the workspace, or bring in the required inputs.
- 03
Plan
Generate an implementation plan that identifies the inputs, method, validation approach, and expected output.
- 04
Review
Check the proposed work, correct it if needed, and approve the next step.
- 05
Execute
Run the supported geospatial operations after user consent.
- 06
Validate
Inspect the resulting layers, tables, statistics, and maps.
- 07
Continue
Refine the question, add another operation, export the result, or continue the workflow.
03 / INTENT & CONTEXT
Start with the question - not the tool menu
Users can describe the result they need in natural language instead of beginning by manually choosing a long sequence of GIS tools. GriidAi uses the current session context - including known layers and the visible workspace state - to reduce ambiguity and connect the prompt to the relevant data.
The AI layer should help clarify what the user is asking for, identify which available assets are relevant, and prepare the next analytical step without pretending that ambiguous requests are automatically correct.
Explore the connected workspace ↗04 / THE IMPLEMENTATION PLAN
See what will happen before it runs
For supported tasks, GriidAi presents an implementation plan before execution. The user can inspect which input is being used, which method will be applied, how the output will be checked, and what result will be created. The plan is a review surface - not decorative AI narration.
FIVE THINGS TO INSPECT
01
Inputs
Which layer, raster, table, AOI, or dataset the operation will use.
02
Method
Which supported spatial operation or analytical approach is proposed.
03
Parameters
Distances, fields, thresholds, projection assumptions, or other required settings where relevant.
04
Validation
What checks should be made before or after execution.
05
Output
What layer, table, statistic, map, or analytical product is expected.
05 / HUMAN APPROVAL
AI proposes the work. The expert decides whether it should run.
GriidAi is designed around human review rather than invisible autonomous execution. The user can review the proposed inputs and analytical approach, request clarification or correction, and then give consent to proceed. After execution, the expert returns to validate the result and decide how it should be used.
Review the proposed work.
Ask for clarification or correction.
Approve the next step.
Connect AI guidance to real GIS operations
The value of Agentic GeoAI is not a more conversational map alone. The AI layer must connect the user's intent to explicit geospatial operations that produce inspectable spatial outputs. GriidAi can coordinate supported vector, raster, terrain, hydrology, network, proximity, attribute, and mapping operations inside the workspace.
Raster
Raster calculations, indices, zonal/statistical operations, visualization.
Terrain & hydrology
Slope, aspect, flow direction, flow accumulation, subbasins, stream-network workflows.
Network & proximity
Routing, nearest-location analysis, accessibility, coverage questions.
Map & results
Layers, attributes, thematic output, raster display, map export.
07 / VALIDATE THE OUTPUT
A result is not the same as a validated result
After execution, users should be able to inspect the output in the same working context: view the layer on the map, inspect attributes or statistics, compare intermediate and final outputs, and decide whether the result is ready to use or needs another iteration.
✓
Map
Inspect the analytical layer and its spatial context.
✓
Table
Review the attributes and result statistics.
✓
Context
Compare source layers, intermediate outputs, and final results.
✓
Next action
Refine the question, adjust the method, or continue the analysis.
08 / WORKSPACE CONTINUITY
Agentic execution needs context, not just a prompt
GriidAi keeps the analytical conversation connected to the workspace. Users can work with uploaded and discovered data, view layers and metadata, inspect tables, use an area of interest, and continue prompting from the state of the current session. Trusted data can also be reused across sessions where supported.
Explore Data ↗09 / MULTILINGUAL INTERACTIONSpanish Arabic Hindi
Work in the language that fits the user
GriidAi has demonstrated text-based interaction in multiple languages while keeping the underlying spatial action consistent. In live demonstrations, the platform responded to prompts in Spanish, Arabic, and Hindi for map and data actions.
Zoom to a specified layer.
Open a layer attribute table.
Return minimum and maximum values from an uploaded raster.
See the agentic pattern across different spatial tasks
Building proximity
Select building → propose 50 m buffer → review plan → execute → intersect neighboring buildings.
Explore building proximity ↗Terrain analysis
Use DEM → propose slope/aspect analysis → execute → inspect raster outputs.
Explore spatial workflows ↗Rooftop solar potential
Combine building footprints and elevation/surface data → perform multiple raster/vector steps → classify and summarize potential.
Explore spatial workflows ↗Hydrology
Use elevation data → fill/flow/accumulation/subbasin or stream-oriented steps → inspect drainage outputs.
Explore spatial workflows ↗11 / ORCHESTRATION ARCHITECTURE
Designed for an evolving AI stack
GriidAi is designed with a model-agnostic orchestration architecture so the geospatial workflow layer is not conceptually tied to one model provider. The current product has been demonstrated using OpenAI models, while broader provider flexibility and enterprise-specific model options remain part of the platform direction.
Built to extend geospatial expertise - not erase it
GIS professionals
Spend less time manually assembling routine steps while retaining control of method and validation.
Consultants
Turn repeatable client methods into more consistent, inspectable workflows.
Researchers
Use transparent steps, explicit data, and inspectable outputs for exploratory analysis.
Analysts & engineers
Start from the business/spatial question while staying inside bounded workflows that experts can review.
Enterprise geospatial teams
Standardize how recurring spatial questions are planned, reviewed, and repeated across a team.
COMMON QUESTIONS
Understanding Agentic GeoAI
What is Agentic GIS?
Agentic GIS uses AI agents to help plan and carry out GIS tasks across data, tools, and outputs. In GriidAi, that process includes reviewable plans, supported execution, and human validation.
Can AI perform spatial analysis?
Yes, when connected to explicit spatial data and supported GIS operations. The resulting maps, tables, statistics, and analytical outputs still require validation.
Can I review an AI-generated GIS plan before it runs?
For supported tasks, GriidAi presents an implementation plan so you can inspect the inputs, method, parameters, validation approach, and expected output before approving execution.
Does Agentic GeoAI replace GIS professionals?
No. GriidAi is designed to extend expert capacity while preserving responsibility for methodology, review, validation, and interpretation.
Can Agentic GeoAI work with raster and vector data?
GriidAi supports workflows spanning vector and raster analysis, alongside other supported spatial operations.
Which AI model does GriidAi use?
GriidAi has been demonstrated using OpenAI models. Its orchestration architecture is designed for broader model flexibility over time; this does not mean every provider or model is currently available.
YOUR NEXT SPATIAL QUESTION
Put Agentic GeoAI to work on a real spatial question.
Bring your data or start with a spatial question, review the plan, and see how GriidAi connects AI guidance with geospatial execution.