We start by understanding your problem through business translation.
Project Scope Definition:
Data Source Assessment.
Project Scope Recommendation.
We apply the latest machine learning and best practices in developing the intelligence loop that creates dependable, reliable data outcomes.
Data modeling & validation
App development & sharing
Your private AI is only as good as your data.
Our data maturity model will promote your accelerated AI transformation.
Eisengard AI's Data Maturity Model
Collection & Architecture
"Quality, Reliability and Interoperability "
In this initial phase, establish a solid foundation for your AI journey. Understand your data, ensuring its ethical use, integrity, and accessibility.
"Descriptive Reports and Accesibility"
Focus on defining problems clearly and exploring your data to diagnose issues. Formulate and validate models while making data accessible through visualization.
Leverage historical data for predictive analytics, and design A/B tests to refine hypotheses. Continuously iterate and adapt your approaches.
"Real-time & Personalized"
Provide tailored insights, continuously improve your processes, and reduce communication friction to enhance efficiency. Use systems to deliver insights effectively.
Enable networked decision-making, facilitating bidirectional insights and fostering a culture of learning and adaptation for fluid and agile operations.
Data Integration + AI learning