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About Datoin

Datoin is a no-code machine learning platform that lets business teams build and deploy models through a visual interface. It offers reusable templates for common needs like churn, sales improvement, and workload forecasting, and connects to enterprise data sources for unified processing. Users can run models in cloud or on-prem environments, monitor performance in real time, and scale applications across departments. Key capabilities: Visual, no-code model building Template library for business use cases Enterprise data integration and preprocessing Cloud or on-prem deployment options Monitoring for deployed models and workflows Best for: SMBs that want ML automation without a dedicated data science team.

Datoin Details

Vendor
Datoin
Year Launched
2016
Location
52 K H Road, Maruthi Nagar, Malleshpalya Extension, Bangalore, India, Karnataka
Deployment
cloud
Training Options
documentation, videos
Countries Served
All Countries
Languages
English, Spanish, French, German, Italian, Chinese, Japanese, Russian.
Users
Data Analysts, Data Scientists, Business Analysts, Machine Learning Engineers
Industries Served
Small to medium-sized businesses, manufacturing, financial services, technology, retail, and back-office operations.
Tags
Artificial Intelligence, Machine Learning, Data Analysis, Predictive Analytics, Automation, Natural Language Processing, Time Series Analysis

Datoin's In-App Market Place

Does Datoin have an in-app market place?

Yes

How many Mini-Apps in the marketplace?

1

Mini Apps

NA

Pricing Options

Free trial
Free version
Request a quote
Promo Offer

Accepted Payment Currencies

USD ($), EUR (€), GBP (£), JPY (¥), AUD (A$), CAD (C$), CHF (CHF), CNY (CN¥), SEK (kr), NZD (NZ$), KRW (₩), INR (₹)

Pros & Cons

  • Easy-to-use no-code platform for ML deployment.
  • Pre-built templates accelerate ML adoption.
  • Works with both cloud and on-premise systems.
  • Integrates with diverse enterprise data sources.
  • Supports a wide range of business functions.
  • Lack of transparent pricing information.
  • Limited information on advanced customization features.
  • May require some technical support for complex ML use cases.

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