Cases overview
Time-series forecastingacross industries
One general time-series base, seven domains: energy, transportation, finance, weather and environment, healthcare and public health, manufacturing and supply chain. For energy, transportation, weather and environment, and public health we publish live forecasts on public data and score them point by point as actuals arrive; transportation also has a backtest demo on real benchmark data. One page per domain covers pain points, approach, target specs and boundaries.
Energy & Power Systems
Multi-scale renewable forecasting, power grid dispatch, and dynamic market risk.ViewTransportation
Backtest on real traffic speeds from San Jose, Tokyo and Los Angeles: pick a moment, forecast ahead, then reveal the actual values.ViewQuantitative Finance & Risk
Regime-shifting volatility, high-frequency order-book dynamics, and macro cross-asset linkages.ViewMeteorology & Climate Intelligence
High-resolution atmospheric sensing, extreme weather trajectories, and hydrological forecasting.ViewHealthcare & Public Health
Forecasting public-health surveillance series such as influenza-like illness, plus trends in continuous vital signs and physiological signals.ViewSmart Manufacturing & Equipment
Multi-sensor telemetry, process parameter tracking, and early degradation warning.ViewModern Supply Chain & Retail
Hierarchical demand forecasting, multi-echelon inventory optimization, and logistics bottlenecks.View
General Base + Domain Training
Why stop training isolated modelsfrom scratch for every site
Training and maintaining a dedicated model from scratch for every wind farm, road and strategy is costly to engineer and slow to start. SequenxAI starts from a general time-series model pretrained at scale to handle cold starts and shared patterns, then tunes it to key industries and customer scenarios, delivered through one interface.
- 01
Cold-start ready
When a new site or sensor comes online with little history, the general model gives usable forecasts right away, without waiting months for data to accumulate.
- 02
Domain & scenario tuning
On top of the general base, dedicated training for the physical constraints and business cycles of domains such as power and transportation balances breadth with vertical accuracy.
- 03
Quantile decision intervals
Full quantile intervals instead of a single point forecast quantify uncertainty for dispatch and risk control.
- 04
One interface as models evolve
From the cold-start general model to industry-specific models, the calling convention and data spec stay the same, so business systems never need a rewrite.
Enterprise Co-Creation
Evaluate forecastson your own time series
Have unique sequence and decision challenges? Book a benchmark or private PoC to confirm feasibility and boundaries on your own data.