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Vikrama.
Healthcare

Clinical AI, patient systems, and health data infrastructure. Built for compliance, not demos.

We build the systems that sit between patient data and clinical decisions.

Healthcare teams run on fragmented systems, manual handoffs, and data that doesn't move between departments. We design AI-powered clinical workflows, patient engagement platforms, and data infrastructure that meets HIPAA requirements and ships into production.

Why AI in Healthcare is different.

Healthcare has more data than almost any industry and less ability to act on it. EHR systems hold decades of patient history, but 97% of hospital data goes unused. Clinical teams spend 30% of their time searching for information instead of applying it.

The organizations deploying AI into clinical workflows are seeing 25-40% reductions in administrative burden and measurable improvements in patient outcomes. The ones still running pilot programs are watching their best clinicians burn out on documentation and manual handoffs.

The gap is not about ambition. Every health system wants AI. The gap is compliance-aware execution: who can ship into an EHR workflow, pass a HIPAA security review, and earn clinician trust in the same quarter. That is a very specific skill set.

The Problems That Slow You Down

01

Data silos across clinical and operational systems

Patient records in one system, billing in another, scheduling in a third. 30% of clinical time spent finding information instead of using it.

02

HIPAA compliance slows everything down

Every new tool needs compliance review. Teams default to "no" because "maybe" takes too long. Innovation stalls behind approval queues.

03

AI projects that never reach the bedside

PoCs that show 92% accuracy in notebooks but can't handle real-world data variance, EHR integration, or clinician workflows.

04

Patient engagement stops at appointment reminders

SMS reminder and a satisfaction survey. Nothing in between: no medication tracking, no care plan visibility, no proactive outreach.

These aren't pitch deck scenarios. Every use case maps to a system pattern we've built and deployed in production.

What We Build in Healthcare

Prior Authorization Automation

VP of Revenue Cycle Management
Problem

Manual review of insurance prior auth requests delays treatment 5-10 days per case, costs $20-50/submission, 15-20% denial rates.

System

LLM+NLP extracts clinical data from EHR notes, matches against payer policies via RAG, auto-generates submissions or flags gaps pre-submission.

Processing time from days to hours, denial rates down 30%.

Claims Fraud Detection

Director of Special Investigations Unit
Problem

Upcoding and phantom billing cost $100B+ annually; manual audits cover only 5% of claims volume.

System

XGBoost ensemble on claims history, procedure codes, provider patterns, combining supervised classification and unsupervised clustering for anomalies.

85-90% F1-score fraud detection, investigation time cut 50%.

Readmission Risk Prediction

Chief Medical Officer
Problem

Generic LACE scores mispredict 20% of Medicare readmissions; $1B+ in preventable costs.

System

Gradient boosting on hospital-specific EHR data (LOS, comorbidities, ED visits), real-time pre-discharge risk scores in clinician dashboards.

Prediction accuracy 15-20% better than LACE, 30-day readmissions down 10%.

Radiology Workflow Prioritization

Director of Radiology
Problem

20-30% urgent scans mixed with routine cases, critical reports delayed 2-4 hours in high-volume ERs.

System

CNN-based triage on scan metadata + image features, auto-sorting PACS queues with explainable heatmaps.

Priority case turnaround cut 40-60%.

Clinical Documentation

Chief Information Officer
Problem

Clinicians spend 2-3 hours/day on EHR note entry; billing delays of $10-15/encounter from incomplete records.

System

Ambient voice-to-text LLM fine-tuned on specialty templates, bidirectional FHIR integration with Epic.

Documentation time reduced 90%.

Nurse Staffing Optimization

VP of Nursing Operations
Problem

Manual scheduling based on averages mismatches real-time volumes. 15% overtime costs, $52K per nurse turnover.

System

LSTM time-series on EHR, weather, seasonality data. Dynamic shift adjustment via optimization solver.

Staffing accuracy up 25%, overtime down 20%.

Supply Chain Inventory Management

Supply Chain Director
Problem

10-20% perishable waste ($2-5M/year per 300-bed hospital), stockouts delay surgeries.

System

Prophet/XGBoost demand forecasting on usage, expiration, supplier data, with auto-reorder via ERP integration.

Inventory costs down 10-20%, waste down 30%.

Clinical Trial Patient Matching

Head of Clinical Operations
Problem

Manual EHR screening misses 70% eligible patients; enrollment delayed weeks, costing pharma $1M+ per study.

System

BERT NLP scans EHR phenotypes against trial criteria, ranks matches with propensity scores.

Matching time from weeks to hours, enrollment 2-3x.

Building the system is half the job. Growing the business around it is the other half.

How We Grow Healthcare Brands

AEO for Treatment Queries

Director of Digital Marketing, VP of Patient Acquisition, CMO
Problem

Health systems are losing patient acquisition to AI answers. When someone searches "best treatment for lower back pain," ChatGPT and Perplexity answer directly, citing Mayo Clinic, Cleveland Clinic, and WebMD. Mid-size providers with strong clinical outcomes but weak digital presence get zero citations. Organic Google traffic is already down 25-30% for symptom and treatment queries. Mayo Clinic appears in roughly 40% of ChatGPT health queries because of structured FAQ schema and clinician-attributed content. AI models cite structured, authoritative content. Everything else gets ignored.

Build

AEO audit of your top 100 treatment and condition queries across ChatGPT, Perplexity, Gemini, and Copilot. Condition page restructure with FAQPage and MedicalCondition schema, clinician-attributed Q&A pairs, treatment comparison tables, and citation-ready statistics. Clinician authority layer tying every page to a named physician with credentials (AI models weight E-E-A-T signals heavily for YMYL health content). AI citation monitoring dashboard with weekly tracking across all major models. Content cluster buildout: 10-20 new condition pages per month, structured for both Google snippets and AI citation, connected to appointment funnels. All workflows HIPAA-compliant, no PHI in tracking. 6-8 weeks to first measurable citation improvements.

15-25% AI citation rate within 90 days (from a typical 0-2% baseline). 25-40% organic traffic growth within 6 months as AI referral traffic compounds.

LinkedIn HCP Lead Nurture for Pharma

Head of Demand Generation
Problem

Life sciences get 1K+ LinkedIn connections/month but under 5% convert; CAC $500+ for demo meetings.

Build

LinkedIn ads to HubSpot forms, compliant nurture (educational content, webinars), HCP-specific lead scoring.

MQL conversion 3x to 15%, CAC down 35% to $325.

HIPAA-Compliant HubSpot Lead Scoring

VP Marketing Operations
Problem

2K leads/year from forms, 70% go cold; manual follow-up misses high-intent surgical consults.

Build

HubSpot with encrypted PHI fields, ML lead scoring, pre/post-op email sequences, EHR integration.

Lead-to-appointment conversion up 40% to 12%, pipeline growth 50% in 3 months.

AI Ads for Telehealth Bookings

Growth Marketing Director
Problem

Google Ads CPC $15-50 for therapy searches, under 2% conversion; no ChatGPT/Gemini sponsored presence.

Build

Gemini/ChatGPT sponsored answers + Google PMax for "therapist near me," booking CTAs, GTM attribution.

2.5x ROAS vs Google alone, CAC reduced 30% to $200-300.

Technical SEO + AEO for Clinic Locations

SEO Director
Problem

Multi-location providers rank #2-5 local; 40% searches end without clicks from AI overviews.

Build

Location pages with schema, clinician bios/FAQs for AEO, GBP optimization, directory link building.

50% organic traffic increase in 6 months, 20% booking lift.

LinkedIn Content for Physician Outreach

Head of Medical Affairs Marketing
Problem

Pharma reps post sporadically; under 1% engagement from HCPs.

Build

AI-generated clinician-reviewed posts (studies, trials), carousel series, gated webinars.

50% follower growth, 4x engagement, 15% lead conversion.

Frequently asked questions

AI moves fast. Stay ahead.

No spam. One actionable email per week on AI systems and growth.

Shipping AI into clinical workflows is hard. We've done it.

Start with a 2-week diagnostic. We'll map your highest-impact opportunities and build a roadmap your compliance team approves.