Machine Learning
as a service

We have helped companies of all sizes to create customised Machine Learning solutions that has helped solve critical business problems & catalyse growth.

Companies are dealing with data like never before. With the vast amount of data it has become quite clumsy to analyse them, unless you leverage Machine Learning & AI.

Now getting actionable insights is easier whether you want to increase the ROI of your marketing campaigns or forecast your demand & sales for your omnichanel business.

• Define ML Use Case
• Data Exploration
• Select Algorithm
• Data Pipeline & Feature Engineering
• Build ML Model
• Iterate to improve model performance
• Present results, tell a story from data
• Plan for Deployment
• Deploy & Operationalize Model

Pluto7 has built proven pre-configured Demand Forecasting models using Artificial Intelligence and Machine Learning that works on Google Cloud Platform that helps improve the forecast accuracy of even hard to forecast products or offerings using traditional methods.

• Collecting Demand History and Current Pipeline
• Gauging Market Interest
• Selecting Demand Attributes
• Cleansing Unstructured Data
• Integrating Third Party Data like PPC data
• Integrating Shipments Data
• Perform Product & Customer Segmentation
• Final Outcome Will Be Recommended Demand Forecast for the Period

Machine Learning for
Demand Forecasting

Demand forecasting is one of the cornerstones of revenue management business practice. The ability to manage dynamically changing demands, gives visibility on the potential future performance of an operation.

Machine Learning
for Marketing

Businesses are eager to understand how customers engage with their products and services online. By understanding customer experience and engagement levels, businesses can be more responsive with their audiences and improve demand forecasting accuracy.

Pluto7 has built proven pre-configured Marketing Artificial Intelligence and Machine Learning model(s) that works on Google Cloud Platform that helps accelerate the ability of an enterprise for the most effective marketing campaigns.

• Build your DMP.
• Joining your data silos in Google Cloud.
• Adding external/third party datasets to your current data.
• Understanding your use cases. Initial use cases could be propensity analysis, optimizing your Ad spends, traffic optimizations or forecasting traffic in segments for your ad placements.
• Building the model / ML algorithm.
• Creating an API for multiple teams across the organization to use the ML models built.
• Creating an API for multiple teams across the organization to use the ML models built.