Case Study: ML architecture validation for fleet safety risk prediction platform
Challenge
A fleet safety software company needed external validation of their machine learning and data engineering architecture. Their system analyzes data from diverse, incompatible sources (cameras, accelerometers, accident reports, violation records, and more) to predict driver risk.
Solution
- Conducted comprehensive discovery process examining domain context, product requirements, and all existing data sources and pipeline architectures
- Performed deep technical review of feature transformations, modeling architecture, and historical architectural decisions to understand evolution and constraints
- Facilitated cross-functional discovery workshops, bringing together internal teams to surface unknown data assets and product insights
- Evaluated model performance measurement approaches and success criteria within the company's explainability-first framework
- Assessed MLOps infrastructure, identifying deployment, monitoring, and model retraining workflow gaps
- Delivered detailed technical report, serving as both validation documentation and architectural reference guide
Results
- Provided external validation that the existing model architecture performed well within critical explainability and interpretability constraints
- Identified specific accuracy improvements and MLOps infrastructure enhancements to optimize staff time allocation
- Enabled shift from bespoke manual workflows to higher-value feature development work through MLOps gap identification
- Delivered ML feature roadmap guidance, leading to strategic pivot toward product features that better leverage existing model capabilities
- Positioned company for improved market capture through validated technical due diligence documentation
The comprehensive ML architecture review validated the company's technical approach while identifying operational improvements that freed their data team for higher-value work and strategic product development.
Work with Insight Softmax
If you have a problem that can be solved with data, we can help. Our problem-solving approach works across company sizes and industries. Contact us to set up a free consultation.
Book now