Models

The right modelfor each kind of time series

Each model is built for one kind of time-series data. Pick a model to see what it does, what data it takes, and where it stands today.

General time-series foundation model for energy, transportation, finance and other series, available on the SequenxAI Platform

General time-series foundation model · Available on the SequenxAI Platform

One modelfor the rhythms of many domains

SequenxAI Omni is SequenxAI's general time-series foundation model, available on the SequenxAI Platform. It is built for energy, transportation, finance and other time series, and aims to forecast new, unseen series directly — point forecasts with quantile intervals — as a cold-start baseline that key industries then tune further.

How the model is meant to work Illustrative data

Multi-domain series → general foundation model → quantile forecasts

SequenxAI Omni structure: cyclical, trending, intermittent and other time series → a general time-series foundation model → direct forecasts with quantile intervals for new series

Structural sketch, not a live forecast.P10–P90

Design goals

What the model is built to do

These are the model's design goals, not verified capability commitments; accuracy conclusions rest on same-scenario comparison results.

  • 01

    Learning across domains

    Aims to learn the trends, cycles and seasonality shared by time series from many different sources, as one starting point across scenarios; industry expertise is added on top through domain tuning.

  • 02

    Zero-shot forecasting

    Forecasts new, unseen series directly, so a new site need not wait months for data; key industries and customer scenarios are then tuned on top.

  • 03

    Quantile intervals

    Outputs point forecasts with quantile intervals such as P10–P90, showing the plausible range of outcomes.

  • 04

    Verifiable evaluation

    Same-scenario comparisons on partners' real data, evaluated in a reproducible way.

Model summary

The model at a glance

Model type
General time-series foundation model
Input modality
Time series
Target domains
Energy · Transportation · Finance and more
Output
Point forecast + quantile intervals
Forecasting mode
Zero-shot cold start + domain tuning (design goal)

Target Scenarios

Built for high-stakes time-series decisions

Scope & Boundaries

What It Is — and Isn’t

It is:

  • SequenxAI's general time-series foundation model, available on the SequenxAI Platform; its inputs are time series
  • It is the model; data cleaning and quality reports come from the SequenxAI Platform
  • Built for energy, transportation, finance and other time series, aiming to forecast new series directly
  • Uncertainty expressed as quantile intervals that show the plausible range
  • Delivery scope agreed in writing with each customer, per scenario

It is not:

  • A general-purpose LLM or text / image / video generation model
  • A model claimed to lead on accuracy without public same-scenario benchmarks
  • A replacement for domain expert judgment

Getting started today

Want to forecaston your own data now?

The SequenxAI Platform provides forecasting through one API, cleaning data before it forecasts and returning auditable quality reports (beta). Contact the team when you want an evaluation on your own scenario.