Nanonets provides an AI-driven Intelligent Document Processing API that transforms unstructured documents into structured data, enabling efficient data extraction and workflow automation.
Available to claim
Build and ship the Nanonets plugin to earn 21 points when we merge it to main. You have 1 hour to link an issue, then 3 hours to open a PR with the plugin scaffold.
Tool to create a new image classification or OCR model. Use when you need to initialize a model before uploading training images. Provide a list of categories/classes that the model should learn to identify or extract.
Permanently deletes an OCR model from Nanonets. Use this action when you need to remove a trained model that is no longer needed. This action is irreversible - once deleted, the model and all its training data cannot be recovered. Prerequisites: Obtain the model_id from the 'Get all OCR models' action first.
Retrieves all models (OCR and Image Classification) in the user's NanoNets account. Returns model details including ID, type, status, accuracy, and extractable fields/categories. Use to discover available models before performing predictions or training operations.
Retrieve all prediction files (OCR results) for a NanoNets model. Use this tool to: - List all documents/images that have been processed by an OCR model - Get prediction results including extracted text and field values - Access file URLs and processing status for each prediction The response includes prediction labels with extracted text, confidence scores, and bounding box coordinates for each processed file.
Tool to retrieve details of an OCR model. Use when you need full metadata of a model by its ID.
Tool to retrieve training images for an OCR model. Use when you need to page through images associated with a model before training or analysis.
Tool to retrieve a list of all workflows in your Nanonets account. Use when you need to inventory or inspect all configured workflows.
Retrieve a paginated list of documents processed by a NanoNets workflow. Returns document metadata including processing status, upload timestamp, verification status, and page details. Use this to monitor document processing progress or access extracted data from previously uploaded documents.
Update AI Agent guidelines for an OCR model. Sets instructions for how the AI should handle field and table predictions. Only works for Instant Learning models. Use this to customize extraction behavior for specific document types.
Tool to upload a training image file to a specified OCR model. Use when adding a local image file to train the model. Supported file formats include PNG, JPEG, and PDF.
Tool to upload training images by URL to a specified OCR model. Use when adding URLs of images to a model for training purposes.
No webhooks.
