What is Fount
Fount is an AI platform built by DataPOEM that helps you understand not just what is happening in your business, but why it is happening, and what to do next.
Fount represents DataPOEM's breakthrough in causal AI technology. This proprietary Large Causal Architecture doesn't just identify patterns, it reveals why things happen and predicts what will happen next.
Most forecasting tools look at past patterns and try to extend them forward. That works when the world is stable. But real businesses deal with changing prices, promotions, media spend, competition, and external factors. Pattern-based models struggle to explain or adapt to this complexity.
Fount takes a different approach. It learns cause-and-effect relationships across your data, so instead of just predicting outcomes, it helps you understand the drivers behind them. This means you can ask questions like "What happens if I increase media spend?" or "How will a price change impact demand?" and get answers you can trust.
The Fount Developer Portal provides direct access to this capability via APIs. You can integrate causal forecasting, scenario simulation, optimization, and decision intelligence into your own applications, workflows, or internal tools, without having to build these models from scratch.
This is built for teams working on revenue planning, marketing effectiveness, demand forecasting, and business strategy, especially where decisions depend on multiple interacting factors.
If you're looking for faster, more reliable forecasting that actually explains outcomes and supports decision-making, you're in the right place.
What problems Fount solves
Fount is designed for business problems where outcomes are shaped by multiple interacting factors.
In demand forecasting, it predicts SKU-level sales while accounting for drivers such as pricing, promotions, seasonality, and external conditions. This allows teams to move beyond static forecasts and understand what is driving demand.
In demand and supply planning, it improves alignment between forecasts and operational decisions. Teams can plan inventory, distribution, and procurement with better visibility into future demand and its drivers.
In pricing and promotion strategy, Fount estimates the impact of changes on demand, revenue, and margins. This enables teams to evaluate scenarios before execution, rather than relying solely on historical trends.
It is also used for marketing impact measurement, where it separates baseline demand from incremental impact. This helps teams understand the true contribution of their campaigns.
Beyond these examples, Fount can be applied to any forecasting problem involving time series data. It adapts across industries, use cases, and levels of granularity. Across all applications, the core value remains consistent: understanding the drivers behind outcomes and enabling better decisions based on that understanding.
If your problem involves multiple variables influencing results, and you need both accurate forecasts and clear explanations, Fount is built for that purpose.
Who it's for
Fount is built for teams where decisions depend on understanding the why behind outcomes, not just tracking what happened.
- Revenue and growth planning teams who need to model the impact of pricing, promotions, and investment decisions before committing to them
- Marketing effectiveness teams measuring the true causal contribution of campaigns, channels, and spend, separate from baseline demand
- Demand forecasting and supply planning teams who need SKU-level accuracy that accounts for real-world drivers, not just historical patterns
- Data and platform engineers integrating causal forecasting and decision intelligence into internal tools, workflows, or applications via API
- Business strategy teams running scenario simulations to evaluate trade-offs across pricing, distribution, and market expansion