We've done this in a lot of rooms.
Between us, we've built:
Industrial
- Automated pre-sales profitability analysis for an industrial consultancy: a prospect's P&L and transaction data in, a finished, analyzed deck delivered in minutes, no analyst in the loop. Case study →
- Post-migration data rebuild and pricing segmentation for three HVAC parts and equipment distributors: $9.6M in identified upside in under two months. Case study →
- Mobile vision platforms for infrastructure inspection
- Field applications identifying industrial components in the field
- Hardware-to-cloud pipelines moving image data off municipal vehicle fleets for pothole and blight detection
Healthcare
- Supply chain analytics across an eight-hospital network: connecting data across systems to manage inventory, control cost, and track KPI performance
- Asset utilization analysis in imaging operations that changed how leadership allocated equipment
- Automated application scoring for a surgical residency program using machine vision and generative AI: hundreds of faculty hours saved, with better predictive accuracy than the process it replaced. Case study →
Education
- Dashboards and predictive models for a 41-school charter network: multivariate and logistic regression, decision trees, identifying what drove student performance
- The data infrastructure underneath
Public sector
- Statewide COVID-19 vaccine distribution tracking: the system a US state used to track provider inventories and distribute vaccine from the CDC through local health districts to individual providers
The context changes from industry to industry. The underlying data and process problems don't. What we do is learn your specific industry and your specific processes, and then deliver what's actually needed.
Let's talk
Let us know if you've got something that needs shrinking.