# Step-by-step tutorials

In this section you can find a set of tutorials with step-by-step instructions on how to solve a series of geospatial use-cases with the help of Agentic GIS. 

<table data-card-size="large" data-view="cards"><thead><tr><th></th><th></th><th></th><th data-hidden></th><th data-hidden data-card-cover data-type="image">Cover image</th><th data-hidden data-card-target data-type="content-ref"></th></tr></thead><tbody><tr><td><strong>Build an AI Agent to collect map-based fleet safety feedback</strong></td><td>Create an AI Agent that helps fleet managers, safety analysts, and other operators <strong>submit precise, location-based feedback back to their systems</strong> using the vehicle data available in the interactive map. </td><td></td><td></td><td><a href="https://3015558743-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FFEElAdsRIl9DzfMhbRlB%2Fuploads%2FNccgPJnnDAmA3MEUW6r9%2FScreenshot%202025-10-08%20at%2000.08.20.png?alt=media&#x26;token=d6e5d65f-742c-4abb-8060-422d6e4d83c8">Screenshot 2025-10-08 at 00.08.20.png</a></td><td><a href="step-by-step-tutorials/build-an-ai-agent-to-collect-map-based-fleet-safety-feedback">build-an-ai-agent-to-collect-map-based-fleet-safety-feedback</a></td></tr><tr><td><strong>Optimizing rapid response hubs placement with AI Agents and Location Allocation</strong></td><td>Create an AI Agent that will help users identify the optimal placement of rapid response hubs in Connecticut using <a href="https://docs.carto.com/carto-user-manual/workflows/components/territory-planning#location-allocation">Location Allocation</a>, part of the <a href="https://docs.carto.com/carto-user-manual/workflows/components/territory-planning">Territory Planning</a> <a href="https://docs.carto.com/carto-user-manual/workflows/extension-packages">Extension Package</a>. </td><td></td><td> </td><td><a href="https://3015558743-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FFEElAdsRIl9DzfMhbRlB%2Fuploads%2F6CBktKY2HE2JP6ndsGpe%2FScreenshot%202025-10-07%20at%2013.16.58.png?alt=media&#x26;token=dd5e1cc5-afd4-465c-b2c1-d610595a3ba8">Screenshot 2025-10-07 at 13.16.58.png</a></td><td><a href="step-by-step-tutorials/optimizing-rapid-response-hubs-placement-with-ai-agents-and-location-allocation">optimizing-rapid-response-hubs-placement-with-ai-agents-and-location-allocation</a></td></tr><tr><td><strong>Analyzing areas of influence with AI Agents through user-driven isoline generation</strong></td><td>Create an AI Agent that generates user-driven isolines based on user input and obtain insights from data within those custom areas. Learn how to combine isoline generation with spatial filtering to analyze points of interest, demographics, or any spatial data within walking, driving, or transit-accessible zones around key locations.</td><td></td><td></td><td><a href="https://3015558743-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FFEElAdsRIl9DzfMhbRlB%2Fuploads%2F8TEbnBY8v2vY8Mk8LJoJ%2FScreenshot%202025-11-06%20at%2019.17.58.png?alt=media&#x26;token=3c5b78bd-06e0-4fd1-a86c-c5854fd213d7">Screenshot 2025-11-06 at 19.17.58.png</a></td><td><a href="step-by-step-tutorials/analyzing-areas-of-influence-with-ai-agents-through-user-driven-isoline-generation">analyzing-areas-of-influence-with-ai-agents-through-user-driven-isoline-generation</a></td></tr></tbody></table>