Connect your data from any tool and track it from any device. Build and share reports, monitor trends, and discover insights.
Connect your data from any tool and track it from any device. Build and share reports, monitor trends, and discover insights. On Nagent, Databox is exposed as a fully-configurable analytics integration that any agent can call — 7 actions, and API key authentication. No code is required to wire Databox into your workflow — connect it once via the External Integrations panel and reuse it across every agent you build.
Agent builders use Databox to automate the kinds of tasks analytics teams previously handled manually. Concrete examples — each one is a single agent step in Nagent — include:
Every action and trigger is paired with a structured input/output schema (visible in the sections below), so when you wire Databox into Helix — our agentic agent builder — the editor knows exactly what each step expects and produces. Configure once, deploy anywhere across your Nagent agents.
Every operation an agent can call against Databox, with input parameters and output schema. Drop these into any step of an agent built in Helix.
DATABOX_CREATE_DATASETTool to create a new dataset in Databox data source. Use when you need to initialize a dataset with a title, data source ID, and primary keys for unique record identification.
Input parameters
Name of the dataset.
Array of field names used to uniquely identify records in the dataset. Each record must have unique values for these fields.
ID of the parent data source. This identifies which data source the dataset belongs to.
Output
Data from the action execution
Error if any occurred during the execution of the action
Whether or not the action execution was successful or not
DATABOX_CREATE_DATA_SOURCETool to create a new data source in Databox. Use when you need to create a logical container for datasets within a Databox account. Requires accountId, title, and timezone parameters.
Input parameters
A descriptive name for the data source (e.g., 'ERP System', 'Test Data Source').
The timezone for the data source in standard format. Available timezones can be retrieved via GET /v1/timezones. Common values include 'UTC', 'America/New_York', 'Europe/London'.
The unique identifier of the Databox account where the data source will be created.
Output
Data from the action execution
Error if any occurred during the execution of the action
Whether or not the action execution was successful or not
DATABOX_DELETE_DATASETTool to delete a dataset by ID in Databox. Use when you need to permanently remove a dataset. This operation is irreversible.
Input parameters
The unique identifier of the dataset to delete in UUID format. This operation permanently removes the dataset and is irreversible.
Output
Data from the action execution
Error if any occurred during the execution of the action
Whether or not the action execution was successful or not
DATABOX_DELETE_DATA_SOURCETool to delete a data source by ID in Databox. Use when you need to permanently remove a data source. This operation is irreversible and will delete all associated datasets.
Input parameters
The unique identifier of the data source to delete. This operation is permanent and irreversible.
Output
Data from the action execution
Error if any occurred during the execution of the action
Whether or not the action execution was successful or not
DATABOX_GET_DATASET_INGESTION_STATUSTool to check the status of a specific data ingestion for a dataset. Use when you need to verify whether a data ingestion was successful by providing the dataset ID and ingestion ID returned from the initial POST request.
Input parameters
The unique identifier of the dataset (e.g., '06feef1f-460d-49a1-b296-3e6c73511358').
The unique identifier returned from the data ingestion request (e.g., '8f0e9bba-f11b-46ae-8f60-8ff3ea878be9').
Output
Data from the action execution
Error if any occurred during the execution of the action
Whether or not the action execution was successful or not
DATABOX_LIST_ACCOUNTSTool to retrieve all Databox accounts accessible to the authenticated user. Use to identify account IDs required for subsequent API operations like data source creation.
Output
Data from the action execution
Error if any occurred during the execution of the action
Whether or not the action execution was successful or not
DATABOX_PUSH_DATA_V1Tool to push data points to a Databox dataset using the v1 API. Use when you need to ingest data records into a specific dataset by providing the dataset ID and an array of records matching the dataset schema.
Input parameters
Collection of data records to ingest. Each record's structure depends on your dataset schema and must include all primary key fields defined during dataset creation.
The unique identifier of the target dataset (UUID format).
Output
Data from the action execution
Error if any occurred during the execution of the action
Whether or not the action execution was successful or not
No publicly available marketplace agent is found using this tool yet. There are 63 agents privately built on Nagent that already use Databox.
Build on Nagent
Connect Databox to any Nagent agent in minutes — no API key management, no boilerplate. Just configure and deploy.
The five questions agent builders ask before adopting a new integration.
Open the External Integrations panel inside Nagent (app.nagent.ai/externalIntegration), find Databox, and click "Connect Now." You'll authenticate with an API key — Nagent handles credential storage and refresh automatically. Once connected, Databox is available to any agent in your workspace.
No. Nagent provides no-code integration for every tool. Once Databox is connected, you configure its 7 actions directly in the agent builder UI — no API calls, no boilerplate, no schema management.
Helix — Nagent's agentic agent builder — lets you drop Databox steps into any workflow visually. Pick an action (e.g., one of those listed above), fill in the inputs (Helix knows the required vs. optional schema for each parameter), and connect it to upstream/downstream steps. Triggers run as the entry point of an agent, so when a Databox event fires, the agent kicks off automatically.
Every Databox action and trigger ships with a fully-typed schema — input parameters with name, type, required flag, and description, plus the output payload shape. The schemas are documented in the sections above. Helix uses these schemas to validate your configuration at build time and to type-check the data flowing between steps.
Yes. While Databox ships with 7 pre-built analytics actions, you can layer custom logic around them inside Helix — pre/post-processing steps, conditional branches, retries, or stitching Databox together with other connected tools. For deeper customization, talk to our team about Nagent's Agentic AI Lab — forward-deployed engineers who build Databox-based workflows tailored to your business.