Context Sources

Context sources allow agentic workflows to automatically query your data during investigations. When configured, agents can fetch transaction data, customer information, and support history without manual intervention.

Overview

Context sources bridge your Connectors with agentic engines. While connectors establish the connection to your data, context sources configure how agents interact with that data during workflow execution.

Supported Context Source Types

Type	Connector	Agent Capabilities
SQL	Snowflake, Roe Tables	Natural language queries, schema discovery, data filtering
API	Zendesk	Ticket search, conversation retrieval, entity lookup

Configuring Context Sources

Context sources are configured when setting up an agentic workflow (like AML Investigation). Each context source requires:

Common Fields

Field	Required	Description
`connection_type`	Yes	Type of connector (`snowflake`, `zendesk`, `Roe Tables`)
`name`	Yes	Friendly name for this data source
`connection_id`	Yes*	UUID of the pre-configured connector (*not required for Roe Tables)
`description`	No	Helps the agent understand what data is available

SQL Context Sources

SQL-based context sources (Snowflake, Roe Tables) enable agents to query structured data using natural language.

Snowflake Configuration

{
  "connection_type": "snowflake",
  "name": "Transaction History",
  "connection_id": "conn_abc123",
  "table": "TRANSACTIONS",
  "description": "Customer transaction data including amounts, dates, and response codes"
}

Field	Description
`table`	Table name for the agent to query
`sql_query`	(Optional) Predefined SQL query—overrides automatic query generation

Roe Tables Configuration

Roe Tables are stored in Roe Tables and don’t require a separate connection.

{
  "connection_type": "Roe Tables",
  "name": "Alert History",
  "table": "alerts",
  "description": "Historical alert data with resolutions"
}

Agent SQL Capabilities

When configured with SQL context sources, agents can:

Discover Schema: Automatically understand table structure and column types
Generate Queries: Create appropriate SQL based on natural language instructions
Apply Filters: Add relevant WHERE clauses based on investigation context
Handle Errors: Recover from query issues and retry with corrections

Provide a detailed description to help the agent understand what data is available and when to use this source.

API Context Sources

API-based context sources (Zendesk) enable agents to interact with third-party services.

Zendesk Configuration

{
  "connection_type": "zendesk",
  "name": "Customer Support History",
  "connection_id": "conn_xyz789",
  "description": "Pull all support tickets for the customer"
}

The description field is crucial for Zendesk—it tells the agent what to search for:

Description Example	Agent Behavior
`"Pull all support tickets for this customer"`	Searches tickets by customer email/ID
`"Search for tickets mentioning fraud"`	Searches for fraud-related keywords
`"Get tickets with 'escalated' tag"`	Filters by specific tags

Example: AML Investigation Setup

Here’s a complete context source configuration for an AML investigation:

{
  "context_sources": [
    {
      "connection_type": "snowflake",
      "name": "Transaction Data",
      "connection_id": "conn_sf_123",
      "table": "TRANSACTIONS",
      "description": "Transaction history with amount, merchant, and response codes"
    },
    {
      "connection_type": "snowflake",
      "name": "Customer Profiles",
      "connection_id": "conn_sf_123",
      "table": "CUSTOMERS",
      "description": "Customer KYC data and account information"
    },
    {
      "connection_type": "zendesk",
      "name": "Support Tickets",
      "connection_id": "conn_zd_456",
      "description": "Customer support history and communications"
    }
  ]
}

How Agents Use Context Sources

During investigation, agents follow this flow:

Identify Data Need

Based on the SOP or investigation requirements, the agent determines what data is needed

Select Source

The agent chooses the appropriate context source based on the name and description

Generate Query

For SQL sources, the agent generates a natural language query that’s converted to SQL

Fetch Data

The query is executed and results are returned to the agent

Analyze Results

The agent incorporates the data into its investigation and analysis

Best Practices

Use Descriptive Names

Name context sources clearly (e.g., “Transaction History” not “Table1”)

Write Detailed Descriptions

Help agents understand when and how to use each source

Limit Table Scope

Specify specific tables rather than exposing entire databases

Use Read-Only Access

Configure connectors with minimal permissions for security

Connectors

Set up connections to your data sources

AML Investigation

Configure context sources for AML workflows

Get Started

Agents

SQL Workspace

Data Resources

Policies

Webhooks

MCP Server

Enterprise

Use Cases

Release Notes

Overview

Supported Context Source Types

Configuring Context Sources

Common Fields

SQL Context Sources

Snowflake Configuration

Roe Tables Configuration

Agent SQL Capabilities

API Context Sources

Zendesk Configuration

Example: AML Investigation Setup

How Agents Use Context Sources

Best Practices

Use Descriptive Names

Write Detailed Descriptions

Limit Table Scope

Use Read-Only Access

Connectors

AML Investigation

​Overview

​Supported Context Source Types

​Configuring Context Sources

​Common Fields

​SQL Context Sources

​Snowflake Configuration

​Roe Tables Configuration

​Agent SQL Capabilities

​API Context Sources

​Zendesk Configuration

​Example: AML Investigation Setup

​How Agents Use Context Sources

​Best Practices

Use Descriptive Names

Write Detailed Descriptions

Limit Table Scope

Use Read-Only Access

​Related Documentation

Connectors

AML Investigation

Overview

Supported Context Source Types

Configuring Context Sources

Common Fields

SQL Context Sources

Snowflake Configuration

Roe Tables Configuration

Agent SQL Capabilities

API Context Sources

Zendesk Configuration

Example: AML Investigation Setup

How Agents Use Context Sources

Best Practices

Related Documentation