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Image(1) Web Cargo Agents support connecting to a variety of data sources, allowing for comprehensive grounding across the organization:
Data TypeExamples (Source Categories)Purpose
CRM ObjectsHubspot Deals, Salesforce AccountsStructured data necessary for Go-To-Market (GTM) operations and automation.
Knowledge BasesNotion, Google Docs, Internal FilesUnstructured documentation (playbooks, FAQs) used for internal expertise (ie: ICP, selling points)
Product DataUsage databases, Analytics platformsStructured/semi-structured data for use cases like churn detection or qualification based on usage.
Custom DatabasesSQL databases, Cloud Data Warehouses (Bigquery, Snowflake, Redshift)Internal data sources accessible via dedicated integration models.
Resource Configuration and Query Modes
Query ModeMechanismData Type FocusWhen to Use
SQLUses the LLM to generate and execute structured SQL queries against the resource (e.g., Hubspot Deals).Structured Data (Databases, CRM Tables)When the query requires filtering, sorting, or aggregation of specific fields.
VectorUses vector similarity search to find text chunks that are semantically (conceptually) related to the Agent’s query.Unstructured Data (Documents, PDFs, Transcripts)When the query is conceptual and requires finding relevant passages within large bodies of text.
Configuration Details Once a resource is selected, by clicking on it, you can access the configuration details:
  • Model: Specifies the specific data object or service to be queried (e.g., Deals object within Hubspot).
  • Prompt/Guidelines: Custom instructions provided to the LLM on how to phrase queries or interpret the resource data (e.g., Always prioritize high-value deals).
  • Filter & Selected Columns: Allows administrators to restrict the data the Agent can access.
    • Filter: Defines specific conditions (e.g., only retrieve deals in ‘Discovery’ stage).
    • Selected Columns: (SQL Mode only) Limits the fields returned, improving performance by reducing context window overhead.
  • Limit: Sets the maximum number of records or results returned by the query, balancing result quality against retrieval cost and speed.