
© 2025 Artificial Beingz
Models for forecasting, risk, vision and decision-making, built on your data, measured against a baseline and monitored after they ship.
01
Predictive Modeling
Every model starts against a simple baseline. If it can't beat the baseline clearly, it doesn't ship.
Typical problems:
- Default and prepayment risk in lending
- Tenant screening and arrears prediction
- Churn, pricing and propensity models
- Explainable outputs, such as per-applicant reason codes for lending decisions
1model = xgb.XGBClassifier(2 max_depth=5, n_estimators=600, learning_rate=0.03,3 early_stopping_rounds=50,4)5model.fit(X_train, y_train, eval_set=[(X_val, y_val)])67# Reason codes for each applicant, not just a score8explainer = shap.TreeExplainer(model)9reasons = explainer.shap_values(X_applicant)02
Forecasting & Anomaly Detection
Forecasts that account for trend and seasonality and come with honest uncertainty ranges, plus alerts for anything that doesn't fit the pattern.
Applications:
- Occupancy, demand and cash-flow forecasting
- Anomaly detection on transactions and payments
- Sensor and telemetry monitoring for predictive maintenance
03
Computer Vision
Classification, object detection and segmentation for problems where the data is images or video.
Where we've applied it:
- Sports analytics: tracking player movement and game events
- Healthcare: medical image analysis and annotation
- Document and property imagery
04
MLOps
A model that works in a notebook isn't finished. We put models into production and keep them healthy after launch.
Setup:
- MLflow experiment tracking and model registry
- Feature pipelines shared between training and serving
- Drift and performance monitoring with alerts
- Scheduled retraining with an approval step before promotion
Related
Related capabilities
Data Engineering
Lakehouse platforms, pipelines and governance on Databricks and Spark.
Learn more →Model Fine-Tuning
LoRA and full fine-tunes on open models, with evals before and after.
Learn more →Data Analytics & BI
Semantic layers and dashboards people trust, in Power BI, Tableau, Looker or Databricks SQL.
Learn more →