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MapInfo Monday: MapInfo AI

  • 1.  MapInfo Monday: MapInfo AI

    Employee
    Posted an hour ago

    Happy #MapInfoMonday!

    Over the last few months, our engineers have worked on a few things related to MapInfo Pro and AI: 

    They have built an MCP server for MapInfo Pro that allows you to communicate with MapInfo Pro from your favorite AI Chat Assistant, like Claude.

    And they have also built an AI chat window that runs directly inside MapInfo Pro and connects to your Large Language Model (LLM), for example, GitHub Copilot or OpenAI.

    We have gathered this in an add-in called MapInfo AI, which is now available through the MapInfo Marketplace for MapInfo Pro v2023 or newer.

    Let me show you some of the benefits of MapInfo AI.

    Labeling using MapInfo AI

    Let’s start with a simple example. You can ask MapInfo AI to help you label a layer:

    “Label the planned fiber lines with the length”

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    MapInfo AI will check what it has to work with. It checks the available tables, maps, and layers.
    With this, it determines which layer I’m referring to.
    It now checks for existing columns that can be used and decides to use a dynamic expression for calculating the length of the polylines.
    It rounds the number nicely and adds a distance unit to the label, too.
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    Let me do the same for the existing fiber lines:
    “Do the same for the existing”
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    It has the context and knows what I mean, even though I’m not very specific.
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    For each of the commands it runs, I can click on it and see the details.
    It’s a good idea to check the statements that it uses to ensure that it’s doing it correctly.
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    Data Loading and Mapping using MapInfo AI

    MapInfo AI can also help you load data in various formats into MapInfo Pro and map it:

    “Load and map data from this folder "C:\Maps\2025\ Fiber Planning Gainesville\Data"”

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    MapInfo AI starts scanning the specified folder for files it can open. And then it starts importing these into MapInfo Pro.
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    With all the files loaded, MapInfo AI creates a map of the data with styling and some labels.
    It provides an overview of the data loaded, the object types of each table, and the layer's styling.
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    A nice and easy way to get started.

    Query using MapInfo AI

    Let us try with a query example. I’m looking for parcels with no buildings:

    “Highlight parcels with no buildings on the map”

    Notice that I told it to highlight the result, and I didn't specifically tell it to use SQL to find these parcels.

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    You can follow its thinking in the Chat window.
    It tries a few SQL Select statements that don’t work. Then it decides to split the process into two: Find the parcels that do have buildings and then use this to find those that don’t.
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    Also, notice how it gives you information about the result. Counts and details about how the result has been styled in the map.

    Create a New Map using MapInfo AI

    You can also use MapInfo AI to create a new map with either existing base tables or query results.

    Let’s create a map with a focus on the planned fiber lines, and the addresses and buildings nearby:

    “Create a new map showing only the planned lines and the addresses and buildings within a distance of 250 meters from these. Use a road map as base”

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    As before, you can follow how MapInfo AI plans and executes the work in the chat window, and in the map, layers, and queries that have been created.
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    I did specify to use a road map style base map, so MapInfo AI picks the Bing Road base map.
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    As you can see, it also provides a compressed version of the work it did, including how many buildings and addresses it found.
    It even gave the new map a friendly name, and the layers have friendly names too.
    Let’s inspect the query it used to find the buildings. A common mistake here is to use Within. This would require that the centroid of the building fall inside the buffer for the building to get selected. A better choice would be Intersects. Then, the building would get selected if any part of it falls inside the buffer.
    MapInfo AI did use the Intersects operator, as you can see in the details of the spatial joins.
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    Installation

    You find MapInfo AI in the MapInfo Marketplace from inside MapInfo Pro.
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    Click on MapInfo AI Preview under the Featured Products or find it under All Products.
    On the MapInfo AI Preview product page, click the Install Product button to download and install the add-in.
    Please note that currently, this is a preview version of MapInfo AI.
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    MapInfo Pro now downloads the add-in, unzips and registers it in the Tool window.

    Configuration of MapInfo AI

    MapInfo AI doesn’t include a dedicated AI account. You need an account or sign up for one. MapInfo AI can connect to this account using an API key. You can often get this API key from the configuration page of your AI.

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    You configure the connection via the Settings panel as shown above. Start by selecting your provider from the list, then enter your API key in the field.
    You can also select which model you want to use. This depends on the provider. Often, the newer models are more expensive than the older models, but they are also better. 
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    You can use the Test Connection button to check your connection to the service.
    In the next chapter, you can see how you can configure MapInfo AI to use GitHub Copilot.
    Next to the Settings button, you will find a small list that currently lets you choose between two options: Full or Limited (No MapBasic). We recommend starting with the Limited (No MapBasic) option. It controls whether you limit AI to using the specific tools we created to help it perform tasks in MapInfo Pro, or let it find solutions through the marvelous world of MapBasic. In most cases, it can solve the task without MapBasic and does so faster because there are fewer solutions to consider.
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    You can also try solving the same problem with both options and see which one works best. We would like to hear your findings.
    At the top of the AI Assistant window, you find the Chat History. Here you can create new chats and delete existing chats. The AI Assistant window keeps the last 10 chats.
    MapInfo AI also comes with an MCP server, allowing you to control MapInfo Pro from, for example, Claude Desktop. We will revisit this in a later article.

    Configuration of GitHub Copilot

    You need to connect MapInfo AI to a large language model. I’ll walk you through how you can connect it to your GitHub Copilot account. This requires that you have a GitHub account with Copilot access.

    Click on the AI Assistant control on the Home tab to open the AI Assistant window.

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    The AI Assistant window opens, offering tips on how it can help you.
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    To configure it, we need to click on the Settings button. This will open the Settings panel.
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    Select the GitHub Copilot option from the Provider list. Now, click on the Login (GitHub / GitLab) button to initiate the process of getting an API key from GitHub.
    The Authorize with GitHub dialog appears. Click on the link shown in the dialog. Don’t close the dialog, as you will need the code shown there.
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    Select your GitHub account from the Device Activation view or use the Use a Different Account button to specify a different account.
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    Now you must authorize GitHub CLI for the selected account. Click on the Authorize github button.
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    In the Authorize your device view, you must now enter the code shown in the Authorize with GitHub dialog. Click the Continue button to get your device authorized to use your GitHub account with MapInfo AI.
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    You should see the next view if it all worked.
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    The Authorize with GitHub dialog now closes, and the API Key field in the Settings panel has been filled.
    You are now ready to start using the MapInfo AI Assistant.
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    We would love your Feedback

    If you get the opportunity, please try out the MapInfo AI add-in and let us know what you think.
    What did you use MapInfo AI for? How did it help you - or did it? Feel free to share your examples and your prompts.
    You can either share your feedback here in the comments section below or use Precisely Ideas.



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    Peter Horsbøll Møller
    Principal Presales Consultant | Distinguished Engineer
    Precisely | Trust in Data
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