Grist
Your team tracks everything in Grist, from orders to inventory to customer records. Now your AI agent can query, add, and update that data during live conversations. Customers get precise answers pulled straight from your spreadsheets, no manual lookups required.
Your AI agent reads, writes, and queries Grist documents mid-conversation, turning relational spreadsheets into a real-time customer support backend.
Grist
Real examples of how businesses use AI agents to pull answers from Grist relational spreadsheets, keeping support fast and data accurate.
A customer messages asking about their membership renewal date. Your AI Agent queries the Grist members table by email, retrieves the renewal date, plan tier, and payment history, and responds with a clear summary. The customer gets an answer in seconds. Your support team stops hunting through spreadsheet rows to answer routine account questions.
A website visitor chats with your bot and expresses interest in a demo. After qualifying the lead, your AI Agent adds a new record to your Grist sales pipeline table with the prospect's name, company, budget range, and conversation notes. Your sales rep opens Grist the next morning to a fully populated lead, complete with context.
A wholesale buyer asks if you have 500 units of a specific SKU available across all warehouses. Your AI Agent runs a SQL query against Grist joining the inventory and warehouses tables, sums available quantities, and confirms stock levels. The buyer gets an accurate cross-warehouse count without anyone running a manual report.
Grist
FAQs
The agent uses Grist's List Records API with filter parameters. For example, to find a customer by email, it passes a JSON filter like {"email":["john@example.com"]}. Grist returns matching rows with all columns. The agent can also sort and limit results for efficiency.
Yes. Grist supports read-only SQL SELECT queries through its API, including JOINs, aggregations, and WHERE clauses. The agent sends the SQL statement to the Run SQL Query endpoint, and Grist executes it against the document's underlying SQLite database, returning structured results.
Tars requires a Grist API key with access to the relevant team site (subdomain). The API key inherits the permissions of the user who generated it. For read-only use cases, create a key from an account with viewer access. For write operations, the account needs editor permissions.
No. The agent queries your Grist documents in real time via the API. Records, columns, and attachments are fetched live during each conversation and used only to formulate responses. Tars does not maintain a separate database of your Grist content.
Yes. The Grist integration supports table creation, column metadata updates, and schema modifications through the API. Your agent can programmatically add new tables with specified columns or change column labels and types when your data structure evolves.
Grist gives your non-technical team members a spreadsheet interface to manage data while providing a full relational database API for your AI agent. Your team edits data visually in Grist while the agent reads it programmatically. No SQL expertise needed on the human side.
Yes. The integration supports listing, downloading, and uploading attachments in Grist documents. Your agent can retrieve a PDF invoice attached to an order record and share the download link with the customer, or accept file uploads and attach them to the appropriate row.
The agent handles empty results gracefully. If a query returns no matching records, it informs the customer that no information was found for their criteria, asks them to verify the details, and offers to connect them with a team member if needed.
Don't limit your AI Agent to basic conversations. Watch how to configure and add powerful tools making your agent smarter and more functional.
Privacy & Security
At Tars, we take privacy and security very seriously. We are compliant with GDPR, ISO, SOC 2, and HIPAA.
Email - sales@hellotars.com
.png)
%201.png)
%201.png)
