Data Science and Machine Learning Engineering
Realize the value of AI.
We help organizations make proactive decisions through application of data analysis, statistical models, and machine learning to power their business with AI.
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We create models that enable more efficient business processes and personalized customer interaction through exploratory data analysis and hypothesis based analytics. Then, we manage, deploy, and monitor our ML-enabled solutions using MLOps.
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Predictive Analytics for Customer Relationship Management
Segmentation and Targeting
360 Degree View of the Customer Insights
Customer Lifetime Value
Campaign Analytics
Lead and Funnel Management Analytics
Retention and Churn Analytics
Cross/Up-sell Analytics and Recommendation Engines
Customer Journey Analysis
Web and Clickstream Analytics
Personalization
Predictive Analytics for Operations and Industry
Demand Forecasting
Inventory Management Analytics
Marketing Mix Optimization
Marketing and Advertising Attribution
Asset Maintenance
Propensity Modeling
Human Capital Analytics
Finance Analytics
Fraud and Anomaly Detection
Customer Support Analytics
Geospatial Processing and Analytics
Machine Learning Engineering
MLOps Standard Operating Procedures
Machine Learning Lifecycle Management
Experiment Tracking for Team Collaboration
Automated Training and Hyperparameter Tuning
Model Pipeline Orchestration and Deployment
Model Serving with Production Model Monitoring and Observability
Real-time Reinforcement with A/B, Challenger/Champion and Multi-Arm Bandits
Model Metadata Management and Governance
Custom Machine Learning Application Integration
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In addition to traditional machine learning, deep learning and reinforcement learning, our artificial intelligence experience will empower your business with natural language processing, chatbots, computer vision and image recognition to support a wide variety of use cases.
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Customer Targeting Engine.
Without accurate tools, marketing organizations have limited understanding of which customers to target with which marketing channels, content, and messaging. They also have limited understanding of which targeted customers are most likely to make a purchase and when. This hampers the sales organization in their forecasting accuracy and conversion efficiency. Without good insight to customers’ buying habits and plans, the revenue lift may be suboptimal from marketing campaigns and tactics. Additionally, the cost to target customers or implement a targeted marketing strategy is very high. Learn more.
We create models that enable more efficient business processes and personalized customer interaction through exploratory data analysis and hypothesis based analytics. Then, we manage, deploy, and monitor our ML-enabled solutions using MLOps.
Predictive Analytics for Customer Relationship Management
Segmentation and Targeting
360 Degree View of the Customer Insights
Customer Lifetime Value
Campaign Analytics
Lead and Funnel Management Analytics
Retention and Churn Analytics
Cross/Up-sell Analytics and Recommendation Engines
Customer Journey Analysis
Web and Clickstream Analytics
Personalization
Predictive Analytics for Operations and Industry
Demand Forecasting
Inventory Management Analytics
Marketing Mix Optimization
Marketing and Advertising Attribution
Asset Maintenance
Propensity Modeling
Human Capital Analytics
Finance Analytics
Fraud and Anomaly Detection
Customer Support Analytics
Geospatial Processing and Analytics
Machine Learning Engineering
MLOps Standard Operating Procedures
Machine Learning Lifecycle Management
Experiment Tracking for Team Collaboration
Automated Training and Hyperparameter Tuning
Model Pipeline Orchestration and Deployment
Model Serving with Production Model Monitoring and Observability
Real-time Reinforcement with A/B, Challenger/Champion and Multi-Arm Bandits
Model Metadata Management and Governance
Custom Machine Learning Application Integration
In addition to traditional machine learning, deep learning and reinforcement learning, our artificial intelligence experience will empower your business with natural language processing, chatbots, computer vision and image recognition to support a wide variety of use cases.
Customer Targeting Engine.
Without accurate tools, marketing organizations have limited understanding of which customers to target with which marketing channels, content, and messaging. They also have limited understanding of which targeted customers are most likely to make a purchase and when. This hampers the sales organization in their forecasting accuracy and conversion efficiency. Without good insight to customers’ buying habits and plans, the revenue lift may be suboptimal from marketing campaigns and tactics. Additionally, the cost to target customers or implement a targeted marketing strategy is very high. Learn more.
