Two primary practices. One senior team.
Healthcare is our largest practice. Manufacturing is a growing one with anchor case work in medical devices and global outdoor equipment. Same delivery discipline across both.
Healthcare and Healthtech
Landing pageProduction-grade data and AI for provider organizations, healthtech products, and value-based care programs.
DATA4AI helps healthcare organizations turn EHR, claims, and operational data into decisions clinicians and executives actually use. We build EMR navigation and clinical AI on Azure OpenAI, no-show reduction on top of Epic, HCC risk adjustment automation, and FHIR-native platforms for ACOs and CMS ACCESS Model programs. Our work covers health systems, physician groups, ACOs, clinically integrated networks, physician enablement platforms, and healthtech startups building clinical, RCM, or population health software.
- Clinical AI and EMR navigation on Azure OpenAI
- Access and no-show reduction on Epic
- HCC risk adjustment automation
- Value-based care (ACCESS Model, MSSP, Medicare Advantage, commercial VBC)
- EHR integration and FHIR APIs (Epic, Cerner/Oracle, Meditech)
- Healthtech data platform design for clinical, RCM, and population health products
- Clinicians spending eleven minutes navigating the EMR for information the chart already contains
- No-show rates visible on a dashboard, but leaking $1M+ per year through a single 20-provider clinic
- AI backlogs with forty candidate use cases and no way to sequence which three ship this year
- HCC codes documented in prior notes but not captured in the current encounter, costing risk-bearing revenue
- FHIR API and CMS ACCESS Model readiness gaps that surface after budget is approved
- Azure OpenAI assistants that sit on top of the EMR, not replacing it, with HIPAA designed in from sprint one
- 90-day access programs on Epic that recover 15 to 25% of otherwise lost appointment capacity
- Seven-phase AI strategy engagements that turn a use case backlog into a scored twelve-month sequence
- HCC risk adjustment NLP on Azure and Microsoft Fabric that surfaces unaddressed codes pre-visit
- FHIR-native pipelines, ACO dashboards, and population health analytics on a unified lakehouse
Manufacturing and Supply Chain
Landing pagePlacement, forecasting, and operational AI for multi-site manufacturers and distributors.
DATA4AI works with manufacturers and distributors where the constraint is data assembly and placement, not model accuracy. We consolidate consumption, billing, transfer, and location records; run Monte Carlo and supply chain simulations for consigned inventory; and modernize demand planning onto Microsoft Fabric so forecast cadence goes from quarterly to weekly. Delivery models are proven in medical devices and global outdoor equipment, with the same senior team available across process, discrete, and CPG manufacturing.
- Consigned inventory and demand placement
- Demand forecasting on Microsoft Fabric
- Data pipeline consolidation across ERP, supplier, and regional inputs
- Generative AI for planner self-service
- Data assessment and modernisation roadmaps
- Consigned inventory averaged across sites, leaving half short and half over-stocked
- Quarterly forecasts built by hand from a dozen ERP, supplier, and regional inputs
- Planners spending twenty hours a week being a data pipeline
- Third-party quarterly data feeds that set the cadence for the entire planning cycle
- Data platform investments funded before anyone has pressure-tested the plan
- SKU and location-level placement models on Monte Carlo and supply chain simulation
- Weekly demand forecasting on Microsoft Fabric with best-fit models per product line
- Reverse-engineered supplier logic that moves cadence from quarterly to monthly
- Generative AI natural-language layer over forecast and dimension tables for self-service
- Fixed-scope Data Assessment and Roadmap that pressure-tests platform investments before build starts
Legal and Professional Services
Applied AI for document-heavy practices where intake volume is the constraint.
For document-heavy practices such as personal injury, insurance defense, immigration, and mass tort where matters follow a repeatable shape, we build private Azure AI pipelines that turn intake into structured summaries in hours instead of weeks. The first AI-in-production system for a US accident law firm cut document review time by more than 60% without any client files leaving the tenant.
- Every new matter arriving as hundreds of pages of scans
- Most expensive talent in the firm spending its time reading rather than lawyering
- Ad-hoc summaries that vary reviewer to reviewer
- Concerns about client files leaving the firm's environment
- Azure AI + GPT-4 deployed in a private tenant so client files never leave
- OCR and Azure Text Analytics pipelines for parties, dates, and legal entities
- Tuned prompts that produce structured summaries preserving legal nuance
- Web interface and REST API for upload, retrieval, and integration
Startups and Scaleups
Fractional senior engineering for teams that need to ship, not staff.
For healthtech and B2B startups building clinical, RCM, population health, or data-heavy products, we provide senior fractional engineering and AI leadership. Scalable data architecture, AI feature development, and investor-ready technical narratives, without the overhead of a full-time CTO hire.
- Pressure to ship AI features without building technical debt
- Uncertainty about the right data and AI architecture for the stage
- Limited budget for senior technical hires
- Need to demonstrate technical credibility to investors and enterprise customers
- Scalable data architecture designed to grow with the product
- MVP-to-production AI features with proper evaluation and monitoring
- Fractional CTO advisory for technical strategy and hiring
- Investor and enterprise-ready technical narratives and architecture documentation
Frequently asked, answered plainly.
The questions that come up most often before a first call.
We build the data and AI infrastructure required for value-based care performance, integrating Epic, Cerner, and other EHRs with payer claims feeds, operational data, and quality measures into a unified lakehouse. HCC risk adjustment NLP surfaces unaddressed codes pre-visit. Azure OpenAI assistants sit on top of the EMR without replacing it. No-show reduction programs recover 15-25% of otherwise lost appointment capacity in 90 days.
We work with multi-site manufacturers and distributors where the constraint is data assembly and placement, not model accuracy. Consigned inventory placement on Monte Carlo and supply chain simulation (proven with a US medical device manufacturer: $19M identified, $4M returned to profit in six months). Demand forecasting on Microsoft Fabric with a GenAI natural-language layer (proven with a global outdoor equipment manufacturer: 20 hours per week returned, quarterly to weekly cadence).
Yes. We work with healthtech startups building clinical, RCM, or population health products, including the Canadian and Australian ecosystems. Fractional CTO advisory, scalable data architecture, AI feature development, and investor-ready technical narratives, without the overhead of a full-time technical executive.
Let’s talk about the second pilot.
Working on a healthcare AI, manufacturing analytics, EHR integration, inventory placement, or demand forecasting project? Book a 20-minute discovery call. We will tell you honestly if we are the right fit.