Data On Demand
AI Solutions
Harness machine learning for forecasting, anomaly detection, and decision optimization.
AI Solutions
DoD's AI Solutions bundle predictive models, explainability, and operational actions into production-ready tools. Use cases include demand forecasting, fraud detection, and prescriptive price optimisation. The platform supports model management, A/B experimentation, and human-in-the-loop workflows for rapid iteration.
Key capabilities
Forecasting across products, regions and channels
Scalable forecasting models that account for seasonality, promotions and product hierarchies.
Real-time anomaly detection with alerting
Continuous monitoring for anomalies with automated alerts and triage workflows.
Prescriptive recommendations and scenario simulation
Actionable prescriptions and scenario simulations to test outcomes before execution.
Explainable AI for stakeholder trust
Built-in explainability to surface drivers behind model predictions for stakeholders.
Model monitoring & drift detection
Detect model drift and set automated retraining triggers to maintain accuracy.
Automated feature engineering and data enrichment
Automatic feature pipelines that enrich data and reduce manual preprocessing.
Use cases
Demand forecasting for retail assortments
Real-time fraud detection for payments
Prescriptive pricing for promotions
Case study
Reduced stockouts by 35% and improved fill rates across 120+ centers in Q2.
Implementation
Data ingestion
Connect ERP, POS and inventory feeds; validate schema and freshness.
Model configuration
Select forecast horizon and tuning parameters; map KPIs to business definitions.
Pilot & validate
Run a 4-week pilot with holdout testing and measure accuracy & business impact.
Rollout
Gradual rollout with monitoring and rollback flags.
Frequently asked questions
How quickly can we onboard models?
Typical onboarding is 4–8 weeks depending on data readiness; early pilots can show value within 2–4 weeks.
Do you support custom model architectures?
Yes — DoD supports custom models alongside our managed options; we provide deployment, monitoring, and rollout tooling.
What data quality is required?
We need at least 3–12 months of cleaned transactional data depending on the use case; our ingestion tools include validation checks to speed this up.
Can we export model predictions?
Yes — predictions can be exported to S3, pushed to downstream systems via connectors, or served through an API for real-time scoring.