How we unlock value from your time series data

Unlike common AI models, Ikigai’s patented Large Graphical Model (LGM) uses multidimensional graphs to represent the relationships between sets of random variables such as sales data, inventory levels, budgets, and customer trends. Designed for tabular and time series data, LGMs are highly effective at harmonizing multiple data sources and forecasting critical business trends like revenue, inventory levels, and supply chain performance.

• Learn generative representation of sparse tabular data
• Correlate data to create synthetic data
• Identify anomalies and outliers
• Generate forecasts on limited data

Ikigai’s unique eXpert-in-the-loop capability seamlessly blends AI and human experience for the ‘X-factor,’ enabling domain experts such as supply and demand planners to train and improve the AI models with industry-specific knowledge and intuition.

• Easily identify anomalies and points of interest
• Review, accept, reject or adjust predictions with a few clicks
• Continuously improve machine learning runtimes
• Drive more accurate data reconciliation, forecasting, and planning

For AI outputs to be trusted and adopted by business decision-makers, they need to be easily understood and explained. Ikigai incorporates explainability throughout its platform with transparent model metrics, interactive visualizations, and eXpert-in-the-loop feedback.

• Verify prediction accuracy with confidence intervals
• Evaluate temporal patterns, trends, and seasonality
• Understand model results from generated forecasts
• Overlay external data such as weather and promotions
• Correlate products with limited history to similar products