Extracta.ai is an AI-powered platform that automates data extraction from various document types, including PDFs, images, and text files, without requiring prior training.
Extracta.ai is an AI-powered platform that automates data extraction from various document types, including PDFs, images, and text files, without requiring prior training. On Nagent, Extracta.ai is exposed as a fully-configurable ai document extraction integration that any agent can call — 10 actions, and API key authentication. No code is required to wire Extracta.ai into your workflow — connect it once via the External Integrations panel and reuse it across every agent you build.
Agent builders use Extracta.ai to automate the kinds of tasks ai document extraction 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 Extracta.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 Extracta.ai, with input parameters and output schema. Drop these into any step of an agent built in Helix.
EXTRACTA_AI_CREATE_CLASSIFICATIONCreates a new document classification configuration. Define a list of possible document types with their characteristics (name, description, unique words). Returns a classification ID that can be used to upload documents for automatic type prediction. This is the first step before uploading documents for classification.
Input parameters
Classification configuration details including document types.
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
EXTRACTA_AI_CREATE_EXTRACTIONCreates a new extraction configuration for processing documents. Define what fields to extract (e.g., names, dates, amounts) and processing options. Returns an extraction ID that can be used to upload and process files. This is the first step before uploading documents for extraction.
Input parameters
Extraction configuration details.
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
EXTRACTA_AI_DELETE_CLASSIFICATIONPermanently deletes an entire document classification process including all associated batches, results, and uploaded files. Use this when you want to remove a classification that is no longer needed. WARNING: This action cannot be undone.
Input parameters
The unique identifier of the classification process to delete. This ID is returned when creating a classification. WARNING: This action permanently deletes the entire classification process including all associated batches, results, and uploaded files.
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
EXTRACTA_AI_DELETE_EXTRACTIONPermanently deletes an extraction job and its configuration from the system. Use this when you want to remove an extraction job that is no longer needed. This action is idempotent - calling it multiple times with the same ID will not cause errors. Requires the extraction ID obtained from creating or viewing an extraction.
Input parameters
The unique identifier of the extraction job to delete. This ID is returned when creating an extraction and can be obtained from the Create Extraction or View Extraction actions.
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
EXTRACTA_AI_GET_BATCH_RESULTSRetrieves extraction results for a specific batch of documents. Returns the extracted data for each file in the batch, along with processing status and file information. If the batch is still processing, results may be empty or incomplete. Maintain 2-second intervals between consecutive requests to avoid rate-limiting.
Input parameters
Unique identifier of the batch to retrieve results for. This ID is obtained from the extraction batches.
Unique identifier of the extraction job. This ID is returned when creating an extraction using the Create Extraction action.
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
EXTRACTA_AI_GET_CREDITSRetrieves the current credit balance available on the account. The system operates on a per-page consumption model where 1 credit = 1 page of document processing. Use this action to check remaining credits before processing documents.
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
EXTRACTA_AI_UPDATE_CLASSIFICATIONUpdates an existing document classification by modifying its parameters. Use this to change the classification name, description, or document types (including their keywords and linked extractions). Requires the classification ID from a previously created classification.
Input parameters
Unique identifier of the classification to update. This ID is returned when creating a classification.
Updated classification configuration including name, description, and document types.
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
EXTRACTA_AI_UPDATE_EXTRACTIONUpdates an existing document extraction process by modifying specified parameters. Only fields provided in the request are modified; omitted fields remain unchanged. Use this to change the extraction's name, description, language, fields to extract, or processing options without recreating the entire extraction job.
Input parameters
The unique identifier of the extraction job to update. This ID is returned when creating an extraction and can be obtained from the Create Extraction or View Extraction actions.
Object containing the extraction parameters to update. Only fields present in this object will be modified; omitted fields remain unchanged.
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
EXTRACTA_AI_VIEW_CLASSIFICATIONRetrieves details of an existing classification configuration including name, description, document types, associated keywords, and linked extraction templates. Use this action to verify classification setup or retrieve configuration details for debugging and auditing purposes.
Input parameters
Unique identifier for the classification to view. This ID is returned when creating a classification.
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
EXTRACTA_AI_VIEW_EXTRACTIONRetrieves detailed configuration and status information for an existing extraction job. Returns the extraction's name, description, language, configured fields, processing options, and any associated batches. Use this action to: - Check the configuration of an extraction job - Verify the fields that will be extracted - View processing options (table extraction, handwriting recognition, etc.) - Monitor batch status if files have been uploaded for processing Requires: extraction_id from a previously created extraction (via Create Extraction action)
Input parameters
Unique identifier of the extraction job to view. This ID is returned when creating an extraction using the Create Extraction action.
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 79 agents privately built on Nagent that already use Extracta.ai.
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Connect Extracta.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 Extracta.ai, and click "Connect Now." You'll authenticate with an API key — Nagent handles credential storage and refresh automatically. Once connected, Extracta.ai is available to any agent in your workspace.
No. Nagent provides no-code integration for every tool. Once Extracta.ai is connected, you configure its 10 actions directly in the agent builder UI — no API calls, no boilerplate, no schema management.
Helix — Nagent's agentic agent builder — lets you drop Extracta.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 Extracta.ai event fires, the agent kicks off automatically.
Every Extracta.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 Extracta.ai ships with 10 pre-built ai document extraction actions, you can layer custom logic around them inside Helix — pre/post-processing steps, conditional branches, retries, or stitching Extracta.ai together with other connected tools. For deeper customization, talk to our team about Nagent's Agentic AI Lab — forward-deployed engineers who build Extracta.ai-based workflows tailored to your business.