- Managing Autopilot for Everyone
- Configuring Autopilot for Everyone
- Deploying the Admin App
- Deploying toolset automations
- Troubleshooting
Autopilot for Everyone admin guide
Context Grounding in Autopilot for Everyone allows you to search existing Context Grounding indexes to answer user queries.
For example, you want to query the HR documents of your organization, such as time and expense policies, or employee handbooks, using Autopilot. Using Context Grounding, an admin would create the index and enable it in Autopilot, which allows Autopilot to search the index to answer HR-related queries.
To use Context Grounding, make sure you meet the following criteria:
- Relevant PDF, CSV, JSON, DOCX, XLSX, and TXT documents are uploaded in a shared Orchestrator storage bucket.
- The index has been already created from the Orchestrator storage bucket.
Index creation is done in Orchestrator, in the tenant-level Indexes page. For details, refer to Indexes.
Index enablement and management in Autopilot is done via the Context Grounding configuration section in Automation Cloud™ > Admin > AI Trust Layer > Autopilot for Everyone.
Once the index is created, enable it in Autopilot through the Context Grounding, panel.
Access to Context Grounding indexes is managed at the folder level. Users can access indexes under the following conditions:
- The index exists in the folder
- The user is assigned to the same folder where the index is located
- The index is enabled in Autopilot
To add a Context Grounding index, follow the steps described in Creating indexes, in the Orchestrator user guide.
To enable an index for Autopilot for Everyone:
Changes are automatically saved.
To edit an index for Autopilot for Everyone:
- Navigate to the Automation Cloud > Admin > AI Trust Layer > Autopilot for Everyone tab, then choose the tenant where Autopilot for Everyone is installed.
- Expand the Context grounding settings section.
- For the desired index, select Edit. The Updating index opens.
- Modify the desired properties as needed.
- Select Save to update the index. The panel closes and you are returned to the Context Grounding table.
Changes are automatically saved.
To remove an index from Autopilot for Everyone:
- Navigate to the Automation Cloud > Admin > AI Trust Layer > Autopilot for Everyone tab, then choose the tenant where Autopilot for Everyone is installed.
- Expand the Context grounding settings section.
- For the desired index, select Delete. A confirmation message is displayed.
- Select Delete to delete the prompt, or Cancel to dismiss the action.
Changes are automatically saved.
This page explains how to enable the feature for a Context Grounding index and shares best practices for preparing data and writing queries.
About the tabular query feature
The tabular query feature helps Autopilot for Everyone understand and answer natural language questions using structured data, such as CSV files. With it, you can query data, run comparisons, and get insights from your indexed tables directly in chat.Enabling tabular query
To enable the feature, check the Enable tabular query box when setting up a Context Grounding index in Autopilot for Everyone.
Once enabled, Autopilot can answer natural language questions using the structured data in your indexed files.
Preparing data best practices
Your results depend on how clean and well-formatted your source data is. Use these tips to prepare and optimize your data for more accurate queries:
Ensure correct data types
Real or Integer), not as text.
To check the data types Autopilor has assigned to your columns, use this prompt:
- "List 5 rows of data in <index_name> and list all the fields with their data types."
Ensure clean numeric and percentage columns
20% as text, which prevents numerical queries from working correctly.
MM/DD/YYYY. Use the data type check query to confirm that date columns are parsed as Date Time rather than plain text.
Tabular query best practices
Clear prompts lead to better results. Keep these tips in mind when querying your tabular data:
Avoid complex schemas
Be careful with files that contain many columns. The more complex the data schema, the more likely it is that a natural language query will be misinterpreted.Be aware of null values
Calculations ignore rows with null or empty values in a queried column. For example, when you sum four columns, the system excludes any row that has a null in one of them. To avoid this, normalize your data and replace nulls with appropriate values.Specify your string match type
By default, the query engine compares strings using exact matches. To find partial matches, you must explicitly include them in your query:- For an exact match: "BCA Claims and Consulting Ltd"
- For a partial match: "BCA Claims and Consulting Ltd. or any of its subsidiaries". This query returns any result that contains the substring "BCA Claims and Consulting Ltd."
Use the debug view
For advanced troubleshooting, useCtrl+Alt+Shift+D to open the debug view. The panel shows how the query engine interpreted your natural language prompt, which can help you
diagnose unexpected results.
- Managing Context Grounding indexes
- Managing access for Context Grounding indexes
- Adding Context Grounding indexes
- Enabling Context Grounding indexes
- Editing Context Grounding indexes
- Deleting Context Grounding indexes
- Using tabular query with Context Grounding
- About the tabular query feature
- Enabling tabular query
- Preparing data best practices
- Tabular query best practices
