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Ikigai Resources

Learn more about Ikigai and the world of AI with our growing library of resources.
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Guide
Evaluating AI Platforms for Time Series Insights and Forecasting
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September 9, 2024
Guide
Operationalizing AI: A Collaborative Guide for Data Scientists and Business Leaders
Business user
Data scientist
Executive
August 19, 2024
Businesses face complex decisions daily regarding sourcing, production, inventory, staffing, sales, and budgeting for their products and services. These decisions rely heavily on forecasting and planning work that must incorporate not only historical data but also expert insights and emerging trends. This framework helps business leaders and data scientists collaborate together for more successful AI deployments.
Infographic
How Prepared is your Business for AI Transformation?
Business user
Executive
Data scientist
August 19, 2024
An AI collaboration checklist for business leaders and operational data scientists
Ebook
Reconciling Disparate Data Sources with aiMatch and eXpert-in-the-Loop
Executive
Business user
Data scientist
July 24, 2024
In this eBook, we explore how Ikigai utilizes their patented generative AI approach, the Large Graphical Model, to solve the critical business problem of data reconciliation. You'll learn how aiMatch and eXpert-in-the-Loop work by walking through a step-by-step example of Ikigai at work.
Technical Whitepaper
Time2Vec: Enabling Forecasting with Limited Historical Data
Data scientist
Developer
Executive
July 24, 2024
Time series data is the backbone of forecasting, from predicting sales, consumption, cash, people's journeys through an organization, the movement of financial instruments and more. This sequential, time-stamped information is crucial for understanding the patterns within data that drive business decisions including trends, seasonality, and patterns. In this whitepaper, we'll explore how enterprises can address some of the challenges inherent in time series data, such as data noise and scarcity, to unlock the value of this vital data for decision-making.
Report
AI Ethics Council Report: Developing and implementing time series forecasting functionalities responsibly
Business user
Executive
IT
July 8, 2024
Traditional and machine learning methods of forecasting and planning can fall short in today's dynamic - and often uncertain - business landscape. Large Graphic Models (LGMs) address the complexities inherent in tabular and time series data, enabling more accurate analysis and decision making in complex and volatile business environments.
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