Orbitware Data Specialization
LAB - IMMERSE IN OUR Process: Steps in building an ML solution
1
Identify business problem
2
Develop hypothesis
3
Acquire + explore data
4
Build a
model
5
Train the model
6
Apply and
scale
LABORATORY:
InSIDE OUR KITCHEN
YOUR TEAM TO BUILD ML MODEL AND PUT THEM INTO PRODUCTION
OR LEVERAGE ONE OF OUR PRE-BUILT ACCELERATORS: EXAMPLES OF Use Case/Industry
30+ Pre-designed Use Cases
by industry
Advertising and marketing technology
Communication service providers
Education
Energy and utilities
Enterprise technology and software
State and local Government
Financial services
Gaming
Healthcare
Life sciences
Manufacturing
Media and entertainment
Retail and consumer goods
Federal government
by use case
Customer Lifetime Value
Subscriber Churn Prediction
Customer Retention
Recommendation Engines
Faster, More Accurate Demand Forecasting
Clinical Data Lake
Safety Stock Analysis
Customer Segmentation
Alternative Data for Investing
ESG Investing
Life Predictive Maintanance (IoT)
Risk / Values at Risk Calculation
Quality of Service Video Streaming Analysis
Ad Effectiveness w/Forecasting & Attribution
Threat Detection at Scale With DNS Analytics
Disease Prediction
Digital Pathology Image Analysis
Anomaly Detection w/Geo Clustering
Reputation Risk
Transaction Enrichment
Rules-based AI for Financial Fraud Prevention
Product Matching with machine learning
Building forward-looking intelligence with external data
Modernizing investment data platforms