Skip to main content
CubegleData · AI · Cloud
Service / AI & ML

AI and Machine Learning

We build machine learning and AI on the data foundation we've already made reliable — from forecasting models to an AI insight layer over existing dashboards.

Common challenges we solve

  • Trends and anomalies buried in dashboards nobody has time to read closely
  • Analysts spending hours writing commentary by hand
  • No consistent way to share insight across teams

Our approach

  1. 01Start from a well-modeled dataset, not raw exports
  2. 02Choose the simplest model that solves the business problem
  3. 03Put monitoring around any model that ships to production

Capabilities

  • Predictive scoring and forecasting models
  • Anomaly detection and NLP/classification
  • ML pipelines and MLOps monitoring
  • AI-generated insight layers on top of existing BI (AutoInsights)
  • Generative and agentic AI proofs of concept

Deliverables

  • Trained, monitored models in production
  • Documented model assumptions and limitations
  • Insight layer or scoring output wired into existing dashboards

Related case studies

Let's talk about what your data should be doing for you

Tell us where you are today and where you're trying to get to. We'll respond with a clear, honest read on the path forward.