This Journey will take you through the DataNeuron Pipeline.

01

Ingest

Upload your data sources to the DataNeuron Automated Learning Platform.

02

Structure

Structure the Masterlist based on the Taxonomy or Hierarchy of your dataset.

03

Validate

Validate auto-labelled paragraphs that have been generated by the DataNeuron ALP.

04

Train

DataNeuron’s AutoML automates the model training and model creation process.

Optional

Predict

Perform predictions on the ingested dataset or in real time through the API without writing any code.

05

Deploy

Deploy your model by exporting the masterlist, labelled datasets or use the model block through APIs.

06

Iterate

Manage your Masterlist from the DataNeuron ALP which supports Incremental or Evolving Annotation.

DataNeuron helps you accelerate and automate human-in-loop labeling for developing AI solutions. Powered by a data-centric platform, we automate data labeling, the creation of models, and end-to-end lifecycle management of ML.

Our Aim is to accelerate the development of AI models and provide explainability of AI.

Learn More

Finance

Science

Emotion

Media

Healthcare

Legal & Tax

Philosophy

ITeS

WHITEPAPER

Automatic Data Annotation: Next Breakthrough

2021

FEATURE CATALOG

DataNeuron Feature Catalog

2021

CASE STUDY

How well does the DataNeuron ALP handle the Finance Use Case?

2021

CASE STUDY

How well does the DataNeuron ALP handle the Medical Use Case?

2021

WHITEPAPER

Announcing The New DataNeuron Platform: Redefining Data Labelling through Automation for the AI-First World

2021

CASE STUDY

How well does the DataNeuron ALP handle the Tax & Legal Use Case?

2021

WHITEPAPER

Artificial General Intelligence: DataNeuron is Redefining Data Labeling Across Domains

2021

CASE STUDY

How Automation drove higher accuracy in Text Annotation of Contracts?

2021

CASE STUDY

How Automation drove higher accuracy in Text Annotation of Contracts?

2021