Scale AI provides data labeling and annotation services for machine learning, offering access to a global workforce and sophisticated tools for training AI models with high-quality labeled data
Scale AI provides data labeling and annotation services for machine learning, offering access to a global workforce and sophisticated tools for training AI models with high-quality labeled data On Nagent, Scale ai is exposed as a fully-configurable artificial intelligence integration that any agent can call — 40 actions, and API key authentication. No code is required to wire Scale ai into your workflow — connect it once via the External Integrations panel and reuse it across every agent you build.
Agent builders use Scale ai to automate the kinds of tasks artificial intelligence 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 Scale ai 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 Scale ai, with input parameters and output schema. Drop these into any step of an agent built in Helix.
SCALE_AI_ADD_STUDIO_ASSIGNMENTSTool to add project assignments to team members in Scale AI Studio. Use when you need to assign specific projects to team members by their email addresses. This action creates new assignments for the specified team members and projects.
Input parameters
Array of email addresses of teammates to assign projects to.
Array of project names to assign to the specified teammates.
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
SCALE_AI_ADD_TASK_TAGSTool to add tags to an existing task. Use when you need to tag or categorize tasks for organization and filtering. Automatically avoids duplicate tags.
Input parameters
List of tags to add to the task. Tags must be non-empty strings. If a tag already exists on the task, it will be ignored to avoid duplication.
The unique identifier of the task to add tags 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
SCALE_AI_CREATE_BATCHTool to create a new batch within a project. Use when you need to group multiple tasks together for organizational and processing purposes.
Input parameters
Name identifying this batch. Must be unique among all batches belonging to a customer.
The name of the project this batch (and its tasks) belong to.
The full URL (including the scheme http:// or https://) or email address of the callback that will be used when tasks are completed.
Only applicable for Rapid projects. Create a self label batch by setting this flag to true.
Only applicable for Rapid projects. Create a calibration batch by setting this flag to true.
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
SCALE_AI_CREATE_DOCUMENT_TRANSCRIPTION_TASKTool to create a document transcription task where workers transcribe and annotate information from single or multi-page documents. Use when you need to extract structured data from documents like invoices, forms, or screenshots.
Input parameters
Language code for the attachment (Default: 'en-US')
Arbitrary labels for task organization (maximum 5 tags allowed)
Batch name; automatically associates task with the batch's project
Task title
Name of the project to associate this task with
Array of field definitions describing what data to transcribe
Geometry type for annotations: 'box' (axis-aligned rectangles) or 'polygon' (rotated rectangles). Default: 'box'
Custom metadata as key-value pairs for storing additional structured information
Task priority level (Range: 0-100, Default: 30)
Arbitrary unique identifier for task deduplication and later querying
URL of a single document to be transcribed. Either attachment or attachments is required
Pre-labels to accelerate annotation, matching the task's response schema
Array of URLs for multi-page documents. Either attachment or attachments is required
Task description
Markdown-enabled instructions explaining the task to taskers
Full URL (including scheme) or email address for completion notification
Number of responses needed (Default: 1)
If true, unsets unique_id if task errors after submission
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
SCALE_AI_CREATE_IMAGE_ANNOTATION_TASKTool to create an image annotation task where annotators label images with vector geometric shapes (box, polygon, line, point, cuboid, ellipse). Use when you need to annotate objects in images with bounding boxes, polygons, or other geometric annotations.
Input parameters
Up to 5 arbitrary string labels for task organization and filtering
Name of the batch to associate this task with. Required for Scale Rapid projects. If batch is specified, project need not be specified as task will automatically be associated with the batch's project
Read-only pre-drawn annotations
Defines connections between annotations
Image padding in pixels applied to all sides
Name of the project to associate this task with
Custom key-value pairs for arbitrary data (max 10KB)
Horizontal image padding in pixels. Overrides padding parameter
Vertical image padding in pixels. Overrides padding parameter
Task priority level: 10 (low), 20 (medium), or 30 (high)
Arbitrary identifier that must be unique across account. Prevents duplicate task creation
URL to the image to be annotated
Specifies annotation shapes and their configurations. At least one geometry type must be provided (box, polygon, line, point, cuboid, or ellipse)
Pre-labels from model predictions for refinement. Contains annotations array matching response schema
Markdown-enabled instructions for annotators explaining how to do the task. Omit for Scale Rapid unless overriding project defaults
Full URL (http/https) or email address for completion notification
Metadata about the image being annotated.
Editable pre-drawn annotations with optional locking capabilities
Reference images displayed to annotators but not labeled. Cannot include the task's primary attachment
Captures additional metadata per annotation
Permits adding new annotations beyond base_annotations
Unsets unique_id if task errors after submission
Allows modification of base_annotations position/attributes
Allows removal of base_annotations
Permits label changes to base_annotations
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
SCALE_AI_CREATE_LIDAR_ANNOTATION_TASKTool to create a lidar annotation task where annotators mark objects with 3D cuboids in 3D space. Use when you need to annotate LIDAR frame sequences with 3D object detection.
Input parameters
Task labels (max 5 per task).
Batch name; auto-associates with batch's project.
Object types to annotate. Maximum 50 objects supported.
Project name for task association.
Custom key-value pairs (max 10KB).
Task priority: 10, 20, or 30.
Custom unique identifier for task deduplication.
List of URLs to the Frame objects you'd like to be labeled. Frames should be time-ordered naturally.
Markdown-enabled task instructions for annotators.
The full url (including the scheme http:// or https://) of the callback when the task is completed.
Specifies file format: 'json' (default) or 'protobuf'.
Conversion rate of point data units to meters.
Polygon types to annotate.
Enables polygon annotations.
Frame capture frequency.
Maximum labeling distance from sensor in meters.
Sampling rate for full frame labeling. With rate k and n frames total, labeled frames are 1st, (k+1)th, (2k+1)th, etc.
Additional per-annotation attributes.
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
SCALE_AI_CREATE_LIDAR_SEGMENTATION_TASKTool to create a LiDAR segmentation task where annotators assign semantic class labels to individual LiDAR points. Use when you need to annotate point cloud data with object classes such as vehicles, pedestrians, roads, buildings, etc. Either 'project' or 'batch' must be provided in the request.
Input parameters
Up to 5 arbitrary labels per task for organization and filtering purposes.
Batch name to associate with this task. If batch is provided, the batch's project is auto-assigned. Either 'project' or 'batch' must be provided.
Object classes for which semantic information is desired. Annotators will assign these semantic classes to each LiDAR point.
Project name to associate with this task. Either 'project' or 'batch' must be provided.
Key-value pairs (max 10KB) for structured task information. Use this to store custom data related to the task.
Task priority level. Valid values are 10 (low), 20 (medium), or 30 (high).
Arbitrary unique identifier across your account. Use this to prevent duplicate task creation.
URLs to Frame objects you'd like to be labeled. Each URL should point to a valid frame data file.
Markdown-enabled task instructions with examples to guide annotators.
Full URL (http:// or https://) for task completion notification. Scale will send a POST request to this URL when the task is completed.
File format of the attachments. Must be either 'json' or 'protobuf'.
Additional attributes to capture per annotation. Define custom attributes for the annotation process.
Reset unique_id if task errors. Set to true to allow resubmission of failed tasks with the same unique_id.
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
SCALE_AI_CREATE_NAMED_ENTITY_RECOGNITION_TASKTool to create a named entity recognition task for labelers to highlight text entity mentions. Use when you need to extract and label entities such as people, organizations, or locations from text.
Input parameters
Custom labels (maximum 5 per task)
The text from which to extract named entities
Batch association (required for Scale Rapid projects)
Array of label definitions for entity types to identify
Project association for the task
Custom metadata object for the task
Arbitrary unique identifier for the task
Array of attachments with additional context
Markdown-enabled instructions for task completion
Webhook URL for task completion notifications
Array of relationship definitions between entities
Controls newline character handling in text
Permits overlapping text spans in annotations
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
SCALE_AI_CREATE_SEGMENTATION_ANNOTATION_TASKTool to create a segmentation task where annotators classify pixels in an image according to provided labels. Use when you need pixel-wise semantic segmentation of images.
Input parameters
Arbitrary labels to assign to task. Maximum 5 per task
Batch name for task association; overrides project requirement
Array of strings or LabelDescription objects describing different types of objects for image segmentation. Maximum 50 labels.
Name of the project to associate this task with
Set of key/value pairs to attach to task object. Maximum 10KB
Custom identifier; must be unique across your account
URL to the image requiring segmentation
Pre-labeled annotations for refinement by annotators. Editable annotations that a task should be initialized with, useful for model pre-labeling scenarios
Markdown-enabled string or iframe embed Google Doc explaining how to do the segmentation
Full URL (including http:// or https://) or email address for callback notification
Whether this image can be completed without every pixel being labeled
Describes file type; currently supports 'image' only
Reference images in \[{"attachment": "<url>"}\] format; cannot include task URL
Additional attributes to capture per annotation with structure containing type, description, choices, and conditions
Auto-reset unique_id if task errors post-submission
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
SCALE_AI_CREATE_TEXT_COLLECTION_TASKTool to create a textcollection task for collecting information from attachments and/or web sources. Use when you need to gather structured data from documents, websites, images, or other content by having taskers fill out defined fields.
Input parameters
Arbitrary labels for task organization (maximum 5 tags allowed)
Batch name; automatically associates task with the batch's project
Task title
Array of field definitions describing data to collect
Project name to associate this task with
Custom metadata as key-value pairs
Task priority level. Must be one of: 10, 20, 30, 40, or 50. Default: 30
Unique identifier for task deduplication and later querying
Pre-labels to accelerate annotation, matching the task's response schema
Array of attachments to collect information from
Task description
Markdown-enabled instructions explaining the task to taskers
Full URL (http:// or https://) or email address for completion callback
Number of responses needed (default: 1)
If true, unsets unique_id if task errors after submission
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
SCALE_AI_CREATE_VIDEO_ANNOTATION_TASKTool to create a video annotation task where annotators draw geometric shapes around specified objects across video frames. Use when you need to annotate video content with bounding boxes, polygons, lines, points, cuboids, or ellipses. Accepts either individual image frames or video files.
Input parameters
Up to 5 arbitrary labels per task
Batch name; automatically associates with the batch's project
Pixel padding around all video frame edges
Project name for task association
Key-value pairs for structured task info (max 10KB)
Left/right padding in pixels; overrides padding if set
Top/bottom padding in pixels; overrides padding if set
Task priority level where higher values indicate higher priority
Arbitrary unique identifier for later retrieval (must be unique across all projects)
Video file URL (mp4, webm, or ogg format). Required if attachment_type is 'video'.
Frames per second to annotate
Mapping of annotation types to their configurations. At least one geometry type must be specified.
Array of image frame URLs. Required if attachment_type is 'image'.
Task instructions in markdown format or Google Doc URL explaining the annotation task
Full URL or email address for completion notification
Either 'image' or 'video' to specify input format. Use 'image' for individual frames or 'video' for video files.
List of event descriptions to annotate in the video
Additional attributes to capture per annotation with type, description, choices, and conditions
If true, unsets unique_id if task errors post-submission
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
SCALE_AI_CREATE_VIDEO_PLAYBACK_ANNOTATION_TASKTool to create a video playback annotation task where annotators draw shapes around specified objects in video files. Use when you need to annotate videos with bounding boxes, polygons, lines, points, cuboids, or ellipses for object detection and tracking.
Input parameters
Up to 5 arbitrary labels per task
Batch name; required for Scale Rapid projects
Pixel padding around all video frame edges
Project name for task association
Key-value pairs for structured task info (max 10KB)
Left/right padding in pixels; overrides padding if set
Top/bottom padding in pixels; overrides padding if set
Task priority level where higher values indicate higher priority
Arbitrary unique identifier for later retrieval (must be unique across all projects)
URL to video file in mp4, webm, or ogg format
Frames per second to capture for annotation
Mapping of annotation types to their configurations. At least one geometry type must be specified.
Start time in seconds for video annotation
Array of image frame URLs. Use this instead of attachment if attachment_type is 'image'.
Task instructions in markdown format or Google Doc URL explaining the annotation task
Full URL or email address for task completion notification
Video duration range in seconds \[start, end\]
Either 'image' or 'video' to specify input format. Defaults to 'video' for video playback tasks.
Pre-labeled annotations for refinement. Keys are frame identifiers, values are arrays of annotations.
List of event descriptions to annotate in the video
Additional attributes to capture per annotation with type, description, choices, and conditions
Whether annotators can add new annotations beyond base_annotations
If true, unsets unique_id if task errors post-submission
Whether annotators can modify existing base_annotations
Whether annotators can remove base_annotations
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
SCALE_AI_DELETE_TASK_TAGSTool to remove specified tags from a Scale AI task. Use when you need to clean up or modify task tags.
Input parameters
List of tag strings to remove from the task
ID of the task to remove tags from
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
SCALE_AI_DELETE_TASK_UNIQUE_IDTool to remove the unique identifier from a task. Use when you need to remove a task's unique identifier for enhanced data management control.
Input parameters
ID of the Task to modify
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
SCALE_AI_FINALIZE_BATCHTool to finalize a batch so its tasks can be worked on. Use when you need to finalize a batch for Scale Rapid and Studio customers. For other customer types, this endpoint returns success without performing any action.
Input parameters
The name of the batch to finalize. This batch must exist before it can be finalized.
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
SCALE_AI_GET_ASSETSTool to retrieve file assets with filtering capabilities by project and metadata. Use when you need to list or search for files uploaded to Scale AI, filtered by project and optionally by metadata. Supports cursor-based pagination for large result sets.
Input parameters
Cursor for pagination to retrieve the next page of results. Use the cursor value from a previous response to get the next page.
Project filter to retrieve assets associated with a specific project. This parameter is required.
Metadata filter to retrieve assets matching specific metadata criteria.
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
SCALE_AI_GET_BATCHTool to retrieve the details of a batch with the specified name. Use when you need to check the status or configuration of an existing batch.
Input parameters
The batch identifier to retrieve
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
SCALE_AI_GET_BATCH_STATUSTool to retrieve the current status of a batch and task completion counts. Use when you need to monitor batch progress or check how many tasks are pending or completed.
Input parameters
The name of the batch to retrieve status for
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
SCALE_AI_GET_FIXLESS_AUDITSTool to retrieve fixless audits by task ID or audit ID. Use when you need to fetch audit information for quality assessment. At least one of task_id or id must be provided.
Input parameters
Identifier for the specific audit. At least one of task_id or id must be provided.
Identifier for the task being audited. At least one of task_id or id must be provided.
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
SCALE_AI_GET_PROJECTTool to retrieve details about a specific Scale AI project using its unique identifier. Use when you need to get project metadata including type, name, parameter history, and creation timestamp.
Input parameters
The unique project identifier to retrieve. This is the project name.
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
SCALE_AI_GET_QUALITY_LABELERSTool to retrieve training attempts matching provided filter parameters. Use when you need to assess labeler performance and understanding of task instructions. At least one of quality_task_ids or labeler_emails must be provided.
Input parameters
Maximum number of training attempt records to return per request.
Pagination token for retrieving subsequent result pages. Use the next_token value from a previous response to get the next page of results.
Filter results by labeler email addresses. At least one of quality_task_ids or labeler_emails must be provided.
Filter results by specific quality task identifiers. At least one of quality_task_ids or labeler_emails must be provided.
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
SCALE_AI_GET_STUDIO_ASSIGNMENTSTool to retrieve current project assignments of all active team users in Scale AI Studio. Use when you need to view team member assignments and workload distribution. Excludes invited or disabled team members.
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
SCALE_AI_GET_STUDIO_BATCHESTool to retrieve basic information about all pending batches in Studio. Use when you need to list batches organized by priority level.
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
SCALE_AI_GET_TEAMSTool to retrieve basic information about all team members associated with the account. Use when you need to list team members, check roles, or view notification preferences.
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
SCALE_AI_GET_V1_TASKTool to retrieve detailed information about a specific task using its task ID. Use when you need to check task status, retrieve results, or analyze task metadata.
Input parameters
The unique identifier of the task to retrieve
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
SCALE_AI_GET_V1_TASK_RESPONSE_URLTool to retrieve secure authenticated task response data. Use when you need to access stored response data for 2D segmentation, video, and lidar tasks that cannot be included in the task JSON.
Input parameters
The unique identifier for the secure result URL
The unique identifier for the task
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
SCALE_AI_IMPORT_FILETool to import files from an external URL endpoint into Scale's system rather than uploading directly from local storage. Use when you need to import files from remote URLs for Scale AI projects or data labeling tasks.
Input parameters
The file URL to be imported. Files are subject to Scale's 80 MB per-file size limit.
Associates the imported file with a specific project; only used for Scale Rapid data labeling tool.
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
SCALE_AI_INVITE_TEAM_MEMBERTool to invite users by email to team with specified role. Use when you need to add new team members with roles like labeler, member, or manager.
Input parameters
Array of email addresses of teammates you want to invite.
Role of invited teammate. Must be one of: 'labeler' (Studio only), 'member', or 'manager'.
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
SCALE_AI_LIST_BATCHESTool to retrieve all batches in descending order by creation date. Use when you need to list batches with optional filtering by project, status, or time range. Supports pagination via limit and offset parameters.
Input parameters
Page size determining number of results per request.
Number of results to skip for pagination.
Filters by batch status. Valid values: 'staging', 'in_progress', or 'completed'.
Filters batches by project name.
Returns additional progress information about batches when set to true.
Maximum value of created_at for returned batches in ISO 8601 format.
Minimum value of created_at for returned batches in ISO 8601 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
SCALE_AI_LIST_PROJECTSTool to retrieve information for all projects in the Scale AI account with optional archived filtering. Use when you need to browse or manage project metadata. Returns project details including type, name, parameter history, and creation timestamps.
Input parameters
Maximum number of projects to return per page.
Number of projects to skip for pagination.
Filter to display only archived or unarchived projects. If not provided, all projects are returned.
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
SCALE_AI_LIST_TASKSTool to retrieve a paginated list of tasks in descending order by creation time. Use when you need to browse tasks with optional filtering by status, type, project, batch, tags, timestamps, or unique identifiers. Supports pagination via limit and next_token.
Input parameters
Filter by task tags. Only tasks with these tags will be returned.
Filter by task type (e.g., 'imageannotation', 'textcollection').
Filter by batch name. Only tasks belonging to this batch will be returned.
Results per page (1-100, default: 100). Controls how many tasks are returned in a single request.
Filter by task status. Can include multiple values from: 'completed', 'pending', 'canceled'.
Filter by project name. Only tasks belonging to this project will be returned.
Maximum created_at timestamp in ISO 8601 format (e.g., '2024-12-31T23:59:59Z'). Only tasks created on or before this time will be returned.
Filter by task unique identifiers. Can include multiple unique IDs to retrieve specific tasks.
Pagination token for retrieving subsequent pages. Use the next_token value from a previous response to get the next page of results.
Minimum created_at timestamp in ISO 8601 format (e.g., '2024-01-01T00:00:00Z'). Only tasks created on or after this time will be returned.
Minimum updated_at timestamp in ISO 8601 format. Only tasks updated on or after this time will be returned.
Maximum updated_at timestamp in ISO 8601 format. Only tasks updated on or before this time will be returned.
Minimum completed_at timestamp in ISO 8601 format. Only tasks completed on or after this time will be returned.
Maximum completed_at timestamp in ISO 8601 format. Only tasks completed on or before this time will be returned.
Filter by audit result status. Can include multiple values from: 'accepted', 'fixed', 'commented', 'rejected'.
Include presigned attachment URLs in the response. Set to true if you need to access task attachments directly.
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
SCALE_AI_POST_V1_TASK_SEND_CALLBACKTool to re-send a callback for a completed or errored task to the callback_url. Use when you need to manually trigger a callback resend for a task that has already been processed.
Input parameters
The unique identifier for the task whose callback should be resent
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
SCALE_AI_REMOVE_STUDIO_ASSIGNMENTSTool to unassign projects from specified team members in Scale AI Studio. Use when you need to remove project assignments from one or more team members.
Input parameters
Array of email addresses of teammates to remove assignments from.
Optional array of project IDs to unassign from the specified team members. If not provided, all projects will be unassigned.
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
SCALE_AI_RESET_BATCH_PRIORITIESTool to restore batch priority order to default order (calibration batches first, then sorted by creation date). Use when you need to reset custom batch priorities back to the default ordering.
Input parameters
Filter parameter for groups to reset priorities
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
SCALE_AI_SET_BATCH_PRIORITIESTool to modify batch priority order in Scale AI Studio. Use when you need to adjust the priority order of pending batches. You must include all pending studio batches in the request.
Input parameters
Array of batch objects specifying the priority order. Must include all pending studio batches.
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
SCALE_AI_SET_PROJECT_ONTOLOGYTool to set ontologies on a Scale AI project. Ontologies define the labels or classes that tasks will reference, and projects maintain complete history of ontology versions. Use when you need to configure or update the classification labels for a project.
Input parameters
A collection of ontology entries as strings. Ontology choices must be unique throughout the ontology. These define the labels or classes that tasks in this project will reference.
The unique project identifier to set the ontology for. This is the project name.
A label identifying the specific version of the ontology being set. This is optional and helps track different ontology versions.
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
SCALE_AI_SET_PROJECT_PARAMSTool to set default parameters for tasks created under a project. Use when you need to establish or update default parameters that apply to future tasks unless overridden.
Input parameters
Project identifier (name). This is used in the URL path.
When true, merges new parameters with existing ones; defaults to false. Field-level overrides take precedence.
Default parameters for tasks created under this project. Any parameters specified here will be set if omitted in a task request.
Default priority for tasks created under this project.
Text combined with task-level instructions.
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
SCALE_AI_SET_TASK_METADATATool to set key-value metadata on an existing Scale AI task. Use when you need to attach custom metadata to track or organize tasks. This operation is idempotent.
Input parameters
The unique identifier of the task to set metadata on.
Key-value pairs of metadata to attach to the task. Accepts strings, numbers, dates, and other JSON-compatible values.
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
SCALE_AI_UPDATE_TASK_UNIQUE_IDTool to update or assign a unique identifier to a task. Use when you need to set a custom identifier for task tracking in your system.
Input parameters
ID of the task to modify. This is the Scale AI task identifier.
The unique identifier to be assigned to the task. This is a custom identifier that can be used to reference the task in your own system.
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
SCALE_AI_UPLOAD_FILETool to upload a local file to Scale's servers with a maximum size limit of 80 MB per file. Use when you need to upload files for Scale AI projects or data labeling tasks.
Input parameters
The local file to upload (max 80 MB).
A JSON object used to store additional data associated with the file.
A human readable name for the file.
Associates the file with a specific project; only used for Scale Rapid data labeling tool.
Unique identifier for upload idempotency; uploading with duplicate IDs returns 409 error.
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 91 agents privately built on Nagent that already use Scale ai.
Build on Nagent
Connect Scale ai 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 Scale ai, and click "Connect Now." You'll authenticate with an API key — Nagent handles credential storage and refresh automatically. Once connected, Scale ai is available to any agent in your workspace.
No. Nagent provides no-code integration for every tool. Once Scale ai is connected, you configure its 40 actions directly in the agent builder UI — no API calls, no boilerplate, no schema management.
Helix — Nagent's agentic agent builder — lets you drop Scale ai 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 Scale ai event fires, the agent kicks off automatically.
Every Scale ai 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 Scale ai ships with 40 pre-built artificial intelligence actions, you can layer custom logic around them inside Helix — pre/post-processing steps, conditional branches, retries, or stitching Scale ai together with other connected tools. For deeper customization, talk to our team about Nagent's Agentic AI Lab — forward-deployed engineers who build Scale ai-based workflows tailored to your business.