ceven

Gigasheet

Ingests massive datasets into Gigasheet, runs automated cleaning and filtering workflows, and exports processed results to S3 or other storage.

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Why use Ceven?

  1. AI native Gigasheet integration

    • Describe the outcome and Ceven picks the right Gigasheet calls, fills the parameters, and checks the result.
    • Structured, agent friendly tool schemas so each call runs reliably instead of by guesswork.
    • Rich coverage for reading, writing, and querying your Gigasheet data, across all 150 of its actions.

  2. Managed auth

    • Built in OAuth with automatic token refresh and rotation.
    • One place to manage, scope, and revoke Gigasheet access.
    • Per user and per environment credentials instead of shared keys.

  3. Agent optimized design

    • Actions are tuned from real success and error rates so reliability climbs over time.
    • Full execution logs so you always know what ran in Gigasheet, when, and on whose behalf.
    • The agent pauses and asks when Gigasheet is unclear instead of plowing ahead.

  4. Enterprise grade security

    • Fine grained access so you control which agents and people can reach Gigasheet.
    • Least privilege by default, read scopes first and only the writes a workflow needs.
    • A full audit trail of every Gigasheet action to support review and sign off.

Supported tools

Every action Ceven's agents can run on Gigasheet, and when to use it.

Upload from URL
Use this when you have a public or pre signed link and want to ingest data directly into a sheet.
Import from S3
Pull objects or prefixes from an AWS S3 bucket into your Gigasheet Library.
Append rows
Add new rows to a sheet by specifying column names. Use after verifying the sheet handle.
Combine files
Merge several Gigasheet files based on a common header or shared column name.
Unroll delimited column
Explode a column containing delimited data into multiple rows to flatten the dataset.
Apply filter template
Fetch and apply a saved filter model to a specific sheet to isolate data subsets.
Rename columns
Make all columns in a dataset unique to prevent conflicts in downstream processing.
Update cell
Change a specific cell value by providing the column name and row number.
Initiate export
Queue an export job for a dataset, optionally applying a filter state first.
Export to S3
Push processed Gigasheet data to an AWS S3 bucket after generating an export handle.
Get dataset columns
Pull all column metadata including IDs, names, and types for a specific dataset handle.
Get dataset views
List all views associated with a dataset to see how data is currently segmented.
Get filter templates
Retrieve all saved filter templates available for the authenticated account.
Share file
Grant email based access to a specific Gigasheet file for other team members.
Delete sheet
Remove a sheet or folder by handle. Set recursive to true to delete folder children.
Get dataset metadata
Pull the general metadata for a dataset using its unique handle.
Delete sheet or folder by handle
Tool to delete a sheet or folder by handle. Use after obtaining the handle of a sheet or empty folder. Set recursive=True to delete all children of a folder.
Get Client State Current Version
Tool to fetch the current client state version metadata for a sheet. Use after obtaining a sheet handle to determine the current version identifier for creating views.
Get Connector Connections
Tool to list connector connections. Use after setting a valid Gigasheet API token.
Get Dataset by Handle
Tool to get dataset metadata. Use after you have obtained the dataset handle.
Get Dataset Export Download URL
Tool to retrieve the download URL for an exported dataset. Use after initiating an export and obtaining its handle.
Get Docs Formulas Functions
Tool to retrieve all supported formula functions. Use after authenticating with a valid API token.
Apply Filter Template On Sheet
Tool to fetch a saved filter template's model for a given sheet. Use when you need the exact filter structure for a specific sheet and template.
Generate New Handle
Tool to generate a new unique dataset handle. Use when you need a fresh FileUuid before creating or referencing datasets.
Get User Autofill Info
Tool to fetch autofill info for the authenticated user. Use after setting a valid Gigasheet API token.
Get Authenticated User Info
Tool to fetch the authenticated user's details. Use after setting a valid Gigasheet API token.
Append Rows to Sheet by Name
Tool to append rows to a sheet by column names. Use after verifying the sheet handle and column names.
Initiate Dataset Export
Tool to initiate an export of a dataset. Use when you need to queue an export job with optional filtering. Use after preparing any filter state. Example: Initiate export for sheet `sheet_abc123` with filters: `{"gridState": {"filterModel":
Insert Blank Row in Dataset
Tool to insert a blank row with null values into a dataset. Use after determining the insertion index.
Rename Columns to Unique
Tool to rename all columns in a dataset to unique names. Use when duplicate column names could cause conflicts in downstream processing.

30 actions · scroll to see them all

Frequently asked questions

Ceven leverages the Gigasheet backend which is designed specifically for big data. Unlike traditional tools that load the entire file into memory, Gigasheet processes data in a way that supports billions of rows. When Ceven triggers an action, it sends the command to the Gigasheet API, and the heavy lifting happens on their distributed infrastructure. This means you can run filters, merges, and unrolls on datasets that would normally crash Excel or Google Sheets. Ceven simply manages the orchestration of these tasks, monitoring the job status and notifying you when the processed dataset is ready for export or further analysis.
Yes. Ceven can use the Create or Update Filter Template action to define specific data cleaning rules and then apply those templates across multiple sheets. For example, if you have a standard way of scrubbing PII or removing null values, you can save that as a template. Ceven can then pull a list of all your datasets, identify which ones need cleaning, and apply the template sequentially. It can also use the Rename Columns to Unique tool to ensure that your data is formatted correctly before it is sent to another application or a data warehouse.
Gigasheet enforces API rate limits that vary based on your subscription tier. If Ceven triggers too many concurrent requests, particularly during large scale folder deletions or bulk sheet updates, you may encounter a 429 Too Many Requests error. Ceven handles this by implementing an exponential backoff strategy, meaning it will automatically wait and retry the request. However, for extremely high volume workloads, we recommend organizing your data into fewer, larger sheets rather than many small ones to reduce the total number of API calls required to manage your library.
The S3 integration is a two way street managed by Ceven. To bring data in, Ceven uses the Import from S3 action, which tells Gigasheet to pull an object from your bucket. To get data out, Ceven first calls the Initiate Dataset Export action to create a processed version of your filtered data. Once that export is ready, Ceven uses the Export Gigasheet to S3 action to move that specific file into your designated AWS bucket. This allows you to use Gigasheet as a temporary processing layer without needing to manually download and upload files.
Yes, Ceven can use the Combine Files by Name action to perform joins on your data. You just need to specify the files you want to merge and the shared column name that acts as the key. This is particularly useful for enriching a primary dataset with information from a secondary lookup table. Ceven can automate this by searching for all files with a specific naming convention, extracting their handles, and then executing the combine command to create a single, unified dataset for your final analysis.
Gigasheet is primarily a batch processing tool rather than a real time database. Ceven can simulate real time updates by scheduling frequent Append Rows or Update Cell calls, but there is an inherent delay as Gigasheet processes the changes. For the best performance, we recommend batching your updates into larger chunks. Instead of updating one cell at a time, use the append action to add groups of rows. This reduces API overhead and ensures that your views and filters update more efficiently across your large datasets.
Ceven uses the Share File action to manage who can see your data. You can instruct the agent to grant access to specific email addresses after a dataset has been cleaned or merged. Because Ceven operates using the permissions of the authenticated user, it can only share files that the user already owns or has administrative rights to. This ensures that your data security model remains intact, as the agent cannot escalate privileges or share sensitive datasets with unauthorized users beyond the scope of your Gigasheet account settings.
Ceven relies on unique dataset handles to identify files. If a file is deleted, any workflow attempting to use that handle will return an error. To prevent this, Ceven can be configured to run a Get Dataset by Handle check before performing any write or manage operations. If the handle is no longer valid, the agent can search for a replacement file using the same name or alert you that the source data is missing. This ensures that your automated pipelines do not fail silently when files are reorganized in the Gigasheet library.

Alternatives to Gigasheet

Other tools that solve a similar problem. Ceven supports these too, so you can switch or run more than one at once.

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