Ask questions about your models with Speckle Intelligence

Speckle Intelligence is the assistant in the Speckle web app. You ask in plain language. It reads the models you have published and replies with answers, charts, and — in the 3D viewer — changes to what you are looking at. Use Chat in the project sidebar for project-scale questions. It is part of the default project navigation, so it is available from most screens in a project: the project, models, a model page, versions, issues, and similar. Use the sparkle in the main 3D viewer when you are looking at models and want to ask about those loaded models. Reuse organisation playbooks — colour legends, cost and carbon methods, formulas, house style — as skills. Dashboards are documented on Intelligence Dashboards; this page does not cover them.

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How it works

Speckle Intelligence does not upload a Revit, Rhino, Tekla, or other host file to an AI so the AI can rebuild the model in memory. You publish to Speckle as usual. The assistant then runs read-only queries against the Speckle data already stored for those published versions. That small payload is deliberate. Speckle does not send the whole model into the AI as a giant blob of text, because that would spend your AI credit — and Speckle’s — on tokens the assistant does not need. It asks for the facts it needs, keeps those results compact, and writes the reply from them. The goal is to answer from your data without burning budget on a full-model dump. Those queries can cover:

• Object properties on published models
• How parts relate to each other (containment, connectivity, levels, systems, materials)
• Where a model was published from (the source application on the version, and types in the published data)
• How the project has been updated (who published which version, and what changed between versions)
• Files in the workspace library, and registered tables such as CSV or XLSX uploads and warehouse connections (Snowflake, Databricks, Microsoft Fabric), when those exist

The assistant can still be wrong if it skips a query or misreads a result. If the data is not there, it is instructed to say so rather than invent structure from a host file. The assistant reads versions in the data format introduced in 2026.9. Versions published in the earlier format cannot be queried, so the assistant says there is no queryable data rather than giving partial answers. Publish a new version after the project uses the new format, and questions about properties and about what connects to what or what contains what both work. See Speckle’s new data model. This page does not cover how Speckle handles AI providers or data security.

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Where to ask

Speckle Intelligence has two entry points. They are not the same job.

• Chat is in the default project navigation, next to Browse at the top of the project sidebar. Use it from the project, models, a model page, versions, issues, or another project screen for project-scale questions: the project as a whole, not only the model you have open.
• The sparkle at the top right of the main 3D viewer is for questions about the models loaded in that viewer.

The Intelligence item in the project or workspace sidebar opens dashboards, not Chat.

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Ask about the project

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Ask about the model in the viewer

To point Chat at particular objects, right-click them in the viewer and choose Add to chat. See Interface and navigation.

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What you can ask

Ask in the same language you would use with a colleague. If you type a question in a given language, Speckle Intelligence usually keeps replying in that language for the conversation. Use a skill or an AI Rule when the language or dialect must stay fixed even if someone asks in another language. In Chat, ask at project scale: the project as a whole, not only one open model. Chat can build a Report from a conversation. The viewer sparkle does not create a saved Report. It answers beside the model with charts and changes to the view. After you save a report, edit sources, tabs, version comparison, and share links on Create and share Intelligence Reports. You can share a chat with people on the project so they can view it. They cannot continue that conversation. In the 3D viewer, ask about the model in front of you. Starters can include What’s in this model?, Give me a tour, What changed recently?, and Color it by category. If you have an object selected, you may also see What is this? You can go further than a first overview. Try asks like:

• What models are in this project, and who published recently?
• Compare the two most recent versions and summarise what was added, removed, or changed
• What sits on this level, and what contains those objects?
• What connects to this system?
• Give me a report of quantities by category and level (use Chat, not the viewer sparkle)
• How do the models loaded in this viewer relate to each other?
• What is the history of the object I have selected?
• Make this a validation rule: the ratio must be at most 20 (after colouring the model by a calculated value)

Model questions need a version in the new data format. Those asks use properties and the relational layer in the new format. For worked examples end to end, see:

• Assess model changes with Speckle Intelligence — ask what changed between two versions, then filter and colour the model by how significant each change is.
• Take off quantities and cost with Speckle Intelligence — a priced takeoff against your own rate card.
• Benchmark a project against your portfolio — compare the open project against a pinned benchmark library.

Data Validation has its own assistant in the check editor; that flow stays on the Data Validation guides.

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Skills

A skill is a reusable playbook you invoke with /skill-name. Use one for model-aware methods (colour, cost, carbon, formulas) and for the same kinds of custom instructions you would save in a generic AI chat tool — tone of voice, meeting notes, non-AEC analysis. Tuned to how your company works, a skill also spends fewer AI tokens reinventing that wheel on every turn. Create skills in workspace Settings, then Skills — including Draft with AI when you want Speckle Intelligence to write the first draft. Arm them in Chat or in the viewer sparkle. See Reuse organisation playbooks with Intelligence skills for how to create and share a skill, and a catalogue of playbooks teams put in them.

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AI Rules

An AI Rule is a standing instruction workspace admins set for every conversation. It applies without a slash command — currency, language, disclosure, or any must-follow constraint. Members can read the rules; only admins change them. In Chat, Workspace rules shows which enabled rules apply. See Set standing AI Rules for the workspace.

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FAQ