Overview

Founded in the Silicon Valley in 2012 with offices worldwide, H2O.ai is a leading open source data science and machine learning platform used globally by Fortune 500 companies and trusted by over 18,000 organizations and hundreds of thousands of data scientists.

CIGNEX Datamatics is a certified partner of H2O.ai and aims to democratize AI for everyone i.e., making it easier, faster and cheaper to deliver expert data science as a force multiplier for every enterprise.

Currently used by visionary companies such as PricewaterhouseCoopers, Armada Health, Wells Fargo, Tech Mahindra, Intel, ING, PayPal and Capital One, H2O.ai is having a positive impact across industries with its award-winning solutions which are:

  • H2O Driverless AI
  • H2O Q
  • Sparkling Water
  • Enterprise Puddle
  • Enterprise Support

H2O: Democratizing Artificial Intelligence

Used by over 18,000 organizations globally, H2O is fairly popular in both the R & Python communities. With a focus on supporting one of the most widely used statistical & machine learning algorithms, (including gradient boosted machines, generalized linear models, deep learning etc.) H2O is a complete open source platform, with industry leading functionalities.

Working on existing big data infrastructure such as bare metal, or top of existing Hadoop or Spark clusters, H2O has the capability to consume data straight from HDFS, Spark, S3, Azure Data Lake or any other additional data sources, into its in-memory distributed key value store.

 

Key Features

Prominent Algorithms

Develop algorithms from the grass root level for distributed computing as well as both supervised and unsupervised approaches i.e., Random Forest, GLM, GBM, XGBoost, GLRM, Word2Vec etc.

Access from R, Python, Flow etc.

Build models in H2O, or use H2O Flow,(a graphical notebook based interactive user interface) with a plethora of  languages such as R, Python etc.

AutoML

Automate the machine learning workflow with AutoML (includes automatic training and tuning of many models)

Distributed, In-Memory Processing

Support huge datasets with fast serialization between nodes and clusters.
Distributed processing helps speed up to 100x faster with fine-grain parallelism, enabling optimal efficiency without degradation.

Simple Deployment

Enable fast and accurate scoring in any environment, with easy to deploy POJOs and MOJOs

Industry Use Cases

  • Wholesale / Commercial Banking
  • Know Your Customers (KYC)
  • Anti-Money Laundering (AML)
  • Card / Payments Business
  • Transaction Frauds
  • Collusion Fraud
  • Real -Time Targeting
  • Credit Risk Scoring
  • In-context Promotion
  • Retail Banking
  • Deposit Fraud
  • Customer Churn Prediction
  • Auto-Loan

 

  • Early Cancer Detection
  • Product Recommendations
  • Personalized Prescription Matching
  • Medical Claim Fraud Detection
  • Flu Season Prediction
  • Drug Discovery
  • ER and Hospital Management
  • Remote Patient Monitoring
  • Medical Test Predictions

  • Predictive Maintenance
  • Avoidable Truck-Rolls
  • Customer Churn Prediction
  • Improved Customer Viewing Experience
  • Master Data Management
  • In-context Promotions
  • Intelligent Ad Placements
  • Personalized Program Recommendations

  • Funnel Predictions
  • Personalized Ads
  • Credit Scoring
  • Fraud Detection
  • Next Best Offer
  • Next Best Customer
  • Smart Profiling
  • Prediction
  • Customer Recommendations
  • Ad Predictions and Spend

Why CIGNEX Datamatics?

  • Certified Partner of H2O.ai
  • Over 170 Experienced AI experts to ensure successful implementations and deployment