Nanonets provides a browser-first environment for developing and deploying custom computer vision models, primarily focused on intelligent document processing and optical character recognition (OCR). Users can upload diverse document types, define data extraction fields, and train AI models directly within the web interface to automate data capture from unstructured and semi-structured visual data, making advanced document automation accessible without deep machine learning expertise.
N
Nanonets Website Full Guide (2026)
AI-based intelligent automation, strong in OCR and document processing.
WebsiteAIForms
3.9 (AI Aggregated)
Updated May 26, 2026
Introduction
Key Features
Core Capabilities
Document type classification engine
Custom field extraction builder
Pre-trained model library for common document
Annotation interface for model training
Additional Details
API endpoint generation for trained model
Data validation rule configuration
Batch document processing queue
Output data schema definition (JSON, CSV)
Use Cases
For Developers
Integrating Custom Document OCR into Application
Developers leverage the platform's API to embed trained computer vision models directly into their existing software, enabling automated data extraction from diverse document streams for backend processing or frontend display. This avoids building OCR pipelines from scratch
How to Use Nanonets
Initiate Model Training for a Document Type
Navigate to the web application, sign in, and select 'Create New Model'. Upload a sample set of documents (e.g., purchase orders) that represent the data you intend to extract
Nanonets Alternatives
Mighty AI
Former training data annotation company (Acquired by Uber).
Scale AI
Data platform for AI, labeling & annotation.
Amazon Rekognition
Image and video analysis service
Microsoft Azure Computer Vision
AI services for analyzing images and video
About Nanonets
Platforms
Categories
Domainnanonets.com
Useful Links
1 totalNanonets Status
Active
Service is operational