aiMatch learns the dataset ontology and the relationships between rows and columns within datasets, enabling faster data reconciliation and better downstream processing.
Our customers use aiMatch to do SKU mapping and new product launches in retail, auditing in insurance, compliance in the financial market, entity resolution across verticals, and more.
aiCast transforms time series data into tabular format, trains large graphical models (LGM), and identifies change points for better forecasting.
Customers have used aiCast to identify factors influencing forecasts and quantify the relationship between multiple time series.
aiPlan can evaluate the impact of possible decisions using historical data.
Customers have used aiPlan to create and find the optimal policies for all types of optimization problems.
Large graphical models (LGM) provide computationally convenient, probabilistic representation of data for AI tasks. Ikigai’s LGM learn generative representation of any sparse tabular data efficiently, solving a longstanding roadblock in which only experts produced domain- and task-specific graphical models.
Researchers design a user-friendly interface that helps non-experts make forecasts using data collected over time...
Using limited data, this automated system predicts a company’s quarterly sales...