Integrated Databricks AI data

After the synchronization, the assets are available in the specified domain.

Warning Do not move the assets to another domain. Doing so may lead to errors during future synchronizations.

Asset status

By default, the assets are shown in a plain list, but you can enable a multi-path hierarchy to show it in a tree structure.

The Default Asset Status field in the capability determines the status of synchronized assets.

If you select No Status, newly created assets receive the first status listed in your Operating Model statuses, and existing assets keep their assigned status.
If you select Implemented, all assets receive the "Implemented" status.

Note For more information about AI Model Version asset statuses, go to Configure the lifecycle stages of AI Governance assets.

Synchronized metadata per asset type

Important considerations:

We always integrate the latest version of a model.
The integrated attributes depend on training run type.
If you don't see the listed synchronized metadata, the attribute type may not be included in the out-of-the-box asset page layout. In that case, you can manually add the attribute type to the layout to make it visible on the asset page.
The Source Tags attribute is currently not ingested.

Asset type	Synchronized metadata	Public ID
AI Base Model	Description From Source System	DescriptionFromSourceSystem
	Initiating User in Source	InitiatingUserInSource
	Creation Date in Source	CreationDateInSource
	Modification Date in Source	ModificationDateInSource
	Owner in Source	OwnerInSource
Databricks AI Model Version	Description From Source System	DescriptionFromSourceSystem
	Version	Version
	Initiating User in Source	InitiatingUserInSource
	Creation Date in Source	CreationDateInSource
	Modification Date in Source	ModificationDateInSource
	Model Accuracy	ModelAccuracy
	Model Precision	ModelPrecision
	Mean Squared Error	MeanSquaredError
	Mean Absolute Error	MeanAbsoluteError
	Any custom metrics defined via the configuration. If you use custom metrics, ensure that you add them to the assignment and layout on the asset type page. Show available custom metrics accuracy_score, exact_match example_count f1_score f1_score_micro f1_score_macro false_negatives false_positives log_loss max_error mean_absolute_error mean_absolute_percentage_error mean_on_target mean_squared_error precision precision_recall_auc r2_score recall roc_auc root_mean_squared_error sum_on_target token_count true_negatives true_positives
AI Model Deployment	Description from source system	DescriptionFromSourceSystem
	Initiating User in Source	InitiatingUserInSource
	Creation Date in Source	CreationDateInSource
	Modification Date in Source	ModificationDateInSource
	Retirement Date in Source	RetirementDateInSource
	Implemented Content Filtering	ImplementedContentFiltering
	Compute Configuration	ComputeConfiguration
AI Agent	Description	Description
	Initiating User in Source	InitiatingUserInSource
	Description from source system	DescriptionFromSourceSystem
	Instructions	Instructions
	Creation Date in Source	CreationDateInSource
	Modification Date in Source	ModificationDateInSource
	Tool Usage	ToolUsage
	Any custom metrics defined via the configuration. If you use custom metrics, ensure that you add them to the assignment and layout on the asset type page.
	AI Agent has version / is version of AI Agent Version	AgentHasVersion
AI Agent Tool	AI Agent Tool can consult data source / can be consulted via Inference Data	AIAgentToolCanReadInferenceData
	AI Agent Tool delegates to / can receive requests from AI Agent Version	AIAgentToolCallsAIAgentVersion
	AI Agent Tool delegates to / can receive requests from AI Endpoint	AIAgentToolCallsAIAgentEndpoint
AI Agent Version	Version	Version
	Initiating User in Source	InitiatingUserInSource
	AI Agent Version can call / can be called by AI Agent Tool	AgentVersionCallsTool
Databricks Volume	Volume ID	VolumeId
	Volume Type	VolumeType
	Catalog Name	CatalogName
	Schema Name	SchemaName
	File Location	FileLocation
	Owner in Source	OwnerInSource
	Description from source system	DescriptionFromSourceSystem
AI Endpoint	Access Method	AccessMethod
	Access Instructions	AccessInstructions
	Traffic Split	TrafficSplit
AI Monitor	Data Drift Detection Enabled	DataDriftDetection
	Prediction Drift Detection Enabled	PredictionDriftDetection
	Schedule	Schedule
	Alert Configuration	AlertConfiguration
	URL	Url
File	Description	Description
	URL	Url
	Document size	DocumentSize
	File Type	FileType
	Document creation date	DocumentCreationDate
	Document modification date	DocumentModificationDate
	Access Type	AccessType
Storage Container	Description	Description
	URL	Url
	Location	Location
	External System Label	ExternalSystemLabel
Database	Description from source system	DescriptionFromSourceSystem
	Owner in source	OwnerInSource
	Data Source Type	DataSourceType
Schema	Description from source system	DescriptionFromSourceSystem
	Owner in source	OwnerInSource
	Data Source Type	DataSourceType
Table	Description from source system	DescriptionFromSourceSystem
Table	Owner in source	OwnerInSource
Column	Description from source system	DescriptionFromSourceSystem
	Column Position	ColumnPosition
	Is Nullable	IsNullable
	Is Primary Key	IsPrimaryKey
	Primary Key Name (if the column is the primary key)	PrimaryKeyName
	Original Name	OriginalName
	Technical Data Type Tip You see the technical data type in the Technical Data Type field in the At a glance sidebar of the Column asset. If the At a glance sidebar is hidden, click . For columns that have a structured technical data type, Array or Struct, click the hyperlink to see the structure of the data in a dialog box. In other locations, for example, in Table assets, click the View Array or View Struct button to open the dialog box. Example	TechnicalDataType

Synchronized metadata per agent type

The Databricks AI integration catalogs several types of Databricks AI agents: Knowledge Assistants, Multi-Agent Supervisors, AI Information Extraction tiles, Text Classification tiles, and Genie Agents. They expose different metadata to Databricks, so what is synchronized in Collibra Platform differs by type. If an agent is missing metadata you expected, it is likely due to one of these type-specific cases rather than a synchronization failure.

The following table summarizes what is synchronized for each type, grouped by category:

Synchronized metadata	Knowledge Assistant	Multi-Agent Supervisor	Genie Agent	AI Information Extraction	Text Classification
Agent structure:
AI Agent Version and AI Agent Tool	Yes	Yes	Conditional	Yes	Yes
Traceability:
Tool links to a Table asset	Yes	No	Yes	No	Yes
Tool links to a Volume asset	Yes	No	No	Yes	Yes
Serving and monitoring:
AI Endpoint	Yes	Yes	No	Conditional	Conditional
AI Monitor	Yes	Yes	No	Yes	Yes
Basic agent information:
Instructions on AI Agent	Yes	Yes	Conditional	Conditional	Conditional
Instructions on AI Agent Version	No	No	No	No	Conditional
Creation Date in Source	Yes	Yes	No	Yes	Yes
Initiating User in Source	Yes	Yes	No	Yes	Yes
Modification Date in Source	No	No	No	Yes	Yes

Conditions:

For Genie Agents, AI Agent Version and AI Agent Tool assets are created only after at least one queried table is already ingested as a Table asset. Until then, only the AI Agent asset appears.
The AI Endpoint asset connects to the AI Agent Version asset through an AI Agent Deployment complex relation for Knowledge Assistants, Multi-Agent Supervisors, and AI Information Extraction and Text Classification tiles. That relation is what surfaces the AI Monitor asset on the version. For AI Information Extraction and Text Classification tiles, this AI Endpoint asset is a shared placeholder, populated only when the tile has scheduled scorers, and not a real serving endpoint.
For Genie Agents, the Instructions attribute is populated only if the Genie space is configured with text instructions. For AI Information Extraction and Text Classification tiles, it's populated only if the task specification defines instructions. Text Classification tiles can also get Instructions on the AI Agent Version asset under that same condition.
Modification Date in Source is unavailable for Knowledge Assistants, Multi-Agent Supervisors, and Genie Agents because the source APIs for these agent types do not expose a last updated timestamp.