GG Technologies was founded with a simple belief: every retail brand — no matter the size — should have access to enterprise-grade demand intelligence.
We started Foresight because we saw a gap. Large retailers had access to sophisticated forecasting tools, but small and mid-market brands were left guessing. We set out to change that.
Built on advanced time series prediction modeling, Foresight combines proven statistical methods with retail-specific enhancements — full P&L forecasting, model hierarchies, AI-powered portfolio insights, and confidence intervals that actually mean something.
Our goal is demand intelligence for everyone. Not dashboards full of vanity metrics, but actionable forecasts that help you buy smarter, stock better, and grow faster.
Founded
2026
Forecast Models
Advanced Time Series Prediction Modeling
SKU Hierarchy
Integrated
Store Hierarchy
Integrated
Forecast Horizon
26 Weeks
CEO & Founder
Jonathan is an innovative data leader with deep expertise in retail analytics and demand planning. With years of experience helping retail organizations transform raw data into strategic advantage, he founded GG Technologies to bring enterprise-grade demand intelligence to brands of every size.
His hands-on experience building forecasting systems, optimizing inventory strategies, and driving data-informed decisions across retail operations is the foundation Foresight was built on — a tool shaped by real-world retail challenges, not theoretical models.
Jonathan holds a Master of Science in Data Science from the University of Notre Dame.
We'd rather ship a forecast that's 85% right than promise the moon. Every model ships with honest confidence intervals.
We're not a generic BI tool with forecasting tacked on. Every feature is designed for inventory planners and demand teams.
Open about our methods. Transparent about our data. Clear about what our models can — and can't — do.
Weekly releases. Constant improvement. We treat our product the way our users treat their inventory: always optimizing.
Battle-tested time series prediction modeling with full trend and seasonality decomposition — see the long-run direction and weekly patterns driving each forecast.
Events and holidays are baked into the model. A dedicated Regressor Component chart isolates their impact so you can see exactly how each event shifts demand.
Every forecast includes 80% confidence bands. AI Insights flags SKUs running above or below these bounds, so you know exactly where to focus.