70%+
Less time in the EMR
Azure OpenAI assistant on top of the EMR, HIPAA designed in from sprint one.
Everyone has an AI pilot.
Almost nobody has a second one.
A data, AI, and BI practice for healthcare and manufacturing. Production-grade systems, sequenced. Multi-year renewals with the same senior team.
- US HealthTech Startup70%+ less time in the EMR
- US Medical Device Manufacturer$4M returned to profit in 6 months
- US Health Systems15-25% clinic capacity recovered
- Global Outdoor Equipment Manufacturer20 hrs/week returned to planners
- US Accident Law Firm60%+ faster document review
The way we work, in one line each.
- HIPAA awareClinical AI in private Azure
- FHIR nativeEpic / Cerner / Meditech
- Microsoft partnerFabric, Azure OpenAI, Synapse
- Multi-year renewals3× with the same medical device client
- Global deliveryUS, Canada, Australia, India
Four measurements from live deployments.
Every figure is from a client engagement in the last thirty months. Anonymized under NDA. Read the case index for the mechanics.
$19M
Inventory loss identified
Consumption, billing, transfer, and location records consolidated. Monte Carlo placement models. Colorado pilot, then national rollout.
20
Returned to planners
Bottleneck analysis first, then daily data automation, then Microsoft Fabric consolidation. ROI landed before any modelling.
3×
Contract renewals
With the same senior team, on the same medical device account. The rest of the client roster tells the same story.
Three pillars. One senior team.
“Results-driven and iterative. We often deliver working prototypes within weeks, not months.”
I
Data Strategy and BI
Seven-phase engagement. Use case inventory, value and feasibility scoring, data readiness, governance, sequenced roadmap. The output is a decision, not a workshop summary.
- 4 sessions · 1 written roadmap
- 12-month sequenced portfolio
- First build ships the quarter after
Read the pillar
II
Data Engineering and Analytics
FHIR-native pipelines for healthcare. ERP, supplier, and regional consolidation for manufacturing. Warehouses and analytics platforms that survive contact with your data.
- Epic / Cerner / Meditech
- Microsoft Fabric consolidation
- 20 hrs/wk returned in one build
Read the pillar
III
Applied AI and GenAI
Azure OpenAI assistants that sit on top of the EMR, HCC risk adjustment NLP, private-tenant GPT-4 for legal, and natural-language layers over forecasting. Every solution ships with evaluation and monitoring.
- 70%+ faster EMR navigation
- 60%+ faster legal review
- GenAI over Microsoft Fabric
Read the pillar
Same EMR. Same data. A different way in.
Our largest practice. Azure OpenAI assistants that sit on top of the EMR, 90-day access programs on Epic, HCC risk adjustment NLP, and seven-phase AI strategy engagements that turn a backlog of forty use cases into a scored twelve-month sequence.
Placement, forecasting, and operational AI.
Anchor work in medical device supply chain and global outdoor equipment. Same senior team, same delivery discipline, moved from EHR data assembly to ERP, supplier, and regional consolidation on Microsoft Fabric.
A structured sequence, not open-ended discovery.
Five stages, scoped so the output is a decision or a shipped system, not a workshop summary. Rhythm holds whether the engagement lasts four sessions or nine months.
- 0.1
Discovery and Requirements
Ambition, constraints, stakeholders, and what a good outcome looks like. Sequenced so the plan survives contact with your data.
- 0.2
Data Assessment and Roadmap
Fixed-scope, seven-phase assessment across four two-hour sessions. Written roadmap document you can hand to whoever builds the thing.
- 0.3
Build. Engineering and Analytics
Production-grade pipelines, warehouses, and reporting on Azure, Microsoft Fabric, or the platform of your choice. First slice ships in weeks.
- 0.4
Applied AI and Go-Live
Azure OpenAI, agents, NLP, and forecasting shipped into daily operations with evaluation and monitoring baked in from the start.
- 0.5
Support and Scale
Managed support and roadmap iteration. Multi-year renewals with the same senior team. 3× on the medical device account, and counting.
Production go-lives. Not slideware.
Six beliefs, one per line. Everything else on the site is these beliefs put to work.
- Small, senior teams.
You work directly with senior practitioners. Data architects, delivery managers, and analysts based in the US and Canada, supported by a dedicated India offshore delivery team.
- Executive-level trust.
Direct relationships with CEO, VP, and owner-partner buyers. Multi-year renewals with the same clients. A law firm's first AI-in-production system. 3× on the medical device account.
- Compliance from sprint one.
HIPAA designed in, not retrofitted. Governance positions on clinical safety, privacy, and model risk agreed up front, so approval is not the thing that kills the project at month five.
- Cloud-agnostic, Microsoft-fluent.
Azure OpenAI, Microsoft Fabric, Synapse, Databricks by default. AWS and GCP where the client is already there. Never the model that dictates the sequence.
- Prototypes in weeks.
Results-driven and iterative. First build ships the quarter after the roadmap. Twenty hours a week returned to planners before any modelling shipped, in one recent engagement.
- Say no early.
We would rather say this now than three weeks in. Anti-fit criteria are documented on every service. Chemistry checks happen on the discovery call, not the invoice.
The problems arrive first.
Every engagement starts with a sentence like one of these three. We keep them on file as a reminder of what our clients actually come in the door with.
“We know our no-show rate. It is on a dashboard. But by the time we see it, the slot is already gone and the patient who needed it is still on a waitlist.”
“We know roughly what each site uses, so we stock to the average. Then half our locations run short while the other half sits on stock nobody will ever use.”
“By the time the forecast is finished it describes a quarter that already happened. We are not planning. We are reporting, late.”
Frequently asked, answered plainly.
The questions that come up most often before a first call.
DATA4AI Consulting Inc. is a data, AI, and BI consultancy founded by Guryash Singh Dhall. We help healthcare and manufacturing organizations turn operational data into decisions and AI pilots into systems people actually use. Our work spans production-grade AI on Azure OpenAI, Microsoft Fabric platforms, EHR integration, HCC risk adjustment, inventory placement, and demand forecasting. Delivery across the US, Canada, Australia, and India.
Three pillars from a single senior team: Data Strategy and BI (assessment, roadmap, executive advisory), Data Engineering and Analytics (pipelines, warehouses, cloud platforms), and Applied AI and GenAI (Azure OpenAI, agents, NLP, computer vision, production deployment). We take engagements that end in a decision or a shipped system, not a workshop summary.
Both. Healthcare is our largest practice (EMR-integrated AI, no-show reduction, HCC risk adjustment, ACCESS Model readiness, ACO analytics). Manufacturing is a growing practice with anchor work in consigned inventory placement for medical device manufacturers and demand forecasting on Microsoft Fabric for global outdoor equipment brands. Same senior team, same delivery discipline.
Data Assessment and Roadmap runs as four two-hour sessions with a written roadmap deliverable, scheduled immediately after signing. Access and no-show programs are 90-day pilots on Epic. AI Strategy is a seven-phase engagement with the first build ready to ship the quarter after the roadmap lands. Larger platform builds run in the range of six to nine months.
Cloud-agnostic in principle, Microsoft-heavy in practice: Azure OpenAI, Microsoft Fabric, Azure Data Factory, Synapse, Databricks. Also comfortable with AWS and GCP where the client is already there. For GenAI we use Azure OpenAI and the Claude API. For orchestration and workflow automation, n8n and Azure Functions.
HIPAA is designed in from the first sprint, not retrofitted. Clinical AI runs in secure Azure environments, PHI stays within your tenant, and access control is built into the architecture rather than the perimeter. Governance positions on clinical safety, privacy, and model risk are agreed up front so approval is not the thing that kills the project at month five.
A fixed-scope Data Assessment and Roadmap: four two-hour sessions with your team, one written assessment and roadmap document you can hand straight to whoever builds the thing. Scheduled post-signing. From there we scope the build together.
Small, senior, agile teams. Data architects, delivery managers, and analysts based in the US and Canada, supported by a dedicated India offshore delivery team. You get senior expertise at a competitive cost, and can scale speed up or down as needed. Executive-level trust with CEO, VP, and owner-partner buyers.
Production go-lives, not slideware. Multi-year renewals with the same clients. A law firm's first AI-in-production system. 3x contract renewals with a repeat medical device client. And the constraint we work with is honesty about fit. If we would not deliver value, we say so before an engagement, not three weeks in.
Delivery across the US, Canada, Australia, and India. Named client work spans US health systems, US medical device manufacturing, a US accident law firm, US healthtech startups, and a global outdoor equipment manufacturer with regional teams across continents.
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.
Within one business day
US, Canada, Australia, India
Healthcare and manufacturing