Table Tools
Table Tools allow Agents to interact with structured data in Endless. They provide the ability to insert, update, search, and compare data directly inside tables, making Agents more autonomous in managing business information.
These tools are essential when the Agent needs to store new information, update existing records, or search across large datasets for relevant answers.
📝 Insert Row in Table
What it does: Inserts a new row into a specific table with information collected during the conversation.
When to use:
Collecting user feedback.
Storing contact details from leads.
Recording structured inputs that Agents gather step by step.
Important: The Agent will only call this tool after ensuring it has collected all required fields for the table.
✏️ Update Row in Table
What it does: Updates existing records in a table with new or corrected information.
When to use:
A customer updates their contact details.
Correcting errors in a record.
Tracking process stages (e.g., status change from Pending → Completed).
🔎 Semantic Search in Table
What it does: Allows Agents to run semantic searches inside table rows. Instead of relying only on exact matches, the Agent can interpret meaning and context of the query.
When to use:
Finding relevant user feedback (even if the exact keywords differ).
Searching for contextual information in descriptive fields.
Recalling similar cases from historical datasets.
⚠️ Key Requirement: Semantic search only works if the column is explicitly enabled for semantic indexing.
While configuring the table, toggle Enable Semantic Search for the columns where you want the Agent to run contextual queries (e.g., free text, notes, messages).
Columns without this option enabled will be ignored in semantic queries.
🔍 Similarity Search in Table
What it does: Finds records that are most similar to the input provided by the user.
When to use:
Searching for users with similar names or IDs.
Matching product descriptions.
Detecting duplicates or related records.
Difference from Semantic Search:
Similarity Search → looks for closest matches based on embeddings (vectors).
Semantic Search → interprets meaning and context, broader and more flexible.
✅ Best Practices
Always design tables with clear column names and descriptions.
Use semantic search only for text-heavy columns where meaning matters (e.g., feedback, notes, support tickets).
For structured fields (e.g., CPF, Email, Phone), prefer Similarity Search for better precision.
Agents will automatically gather all required variables (like column values) before executing insert or update actions.
👉 With these tools, your Agents can not only answer queries, but also write, update, and search structured datasets, becoming a powerful interface between conversations and your company’s internal data.
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