Parthia Health helps hospitals, clinics, and healthcare institutions determine whether AI adoption is feasible, financially sound, and clinically safe — before committing budgets to unproven technology.
Vendor-neutral. Evidence-based. We don't sell AI — we protect your investment in it.
Hundreds of AI vendors compete for your budget with impressive demos and unvalidated promises. But your institution is unique — its workflows, its data, its people. What worked in a demo may fail on your floor.
Every AI company advising you on "digital transformation" is also trying to sell you their product. Their feasibility study will always conclude that you need what they sell.
Beyond the licensing fees: staff hours lost to training, workflow disruption, IT integration costs, and organizational resistance to the next innovation attempt.
While uncertainty paralyzes decision-making, operational inefficiencies keep draining budgets. The right question isn't "AI: yes or no?" — it's "which problem, which tool, and when."
Most institutions don't know. We audit your data infrastructure, EHR integration capacity, and data quality before recommending anything.
We build independent financial models based on your actual volumes, costs, and staffing — not marketing projections.
Technology that clinicians reject is money lost. We assess workflow fit and change-readiness as part of every feasibility study.
We evaluate regulatory posture, clinical validation evidence, and liability exposure before any tool reaches your patients.
Every engagement starts with an independent study of whether AI adoption makes sense for your institution — and if so, where. You receive a clear, board-ready report covering:
Sometimes the right answer is "not yet." When it is, we tell you — and show you what to fix first.
A structured path designed for healthcare leadership teams — transparent at every step, with clear deliverables and no long-term lock-in.
We meet your leadership and clinical teams, map your pain points, and identify where costs and inefficiencies concentrate.
Week 1–2Data audit, workflow analysis, and independent ROI modeling. You get a board-ready report with a clear go / no-go recommendation.
Week 3–6If the case is sound, we evaluate the market vendor-neutrally and recommend the best-fit solution — or a custom build when nothing fits.
Week 7–10We stay at your side through piloting, staff adoption, and outcome measurement — until the results are real and measured.
OngoingWe act as your independent strategic partner — from identifying the right problems to implementing the right solutions.
We analyze your operational and clinical data to identify the highest-impact problems — and tell you honestly whether AI is the right answer for each one, backed by an independent financial model.
We evaluate available AI solutions against your specific context — data maturity, budget, workflows, and regulatory needs. We take no commissions from vendors, so our recommendation is only ever about your fit.
When no suitable market solution exists, we co-develop a tailored AI product with vetted technology partners — with your institution owning the requirements and the outcome metrics.
We systematically review clinical and operational literature to ground every recommendation in published evidence — turning research findings into deployable, measurable improvements.
We start where ROI is fastest and regulatory friction is lowest — your operational backbone.
The difference between a technology vendor and an independent advisor determines whose interests the recommendation serves.
Exactly where we specialize. Our engagement begins with a feasibility assessment: we audit your data infrastructure, analyze your operational pain points, and build an independent financial model. In 4–6 weeks you'll have a clear, evidence-based answer about whether AI investment makes sense for your institution — and precisely where to start if it does.
A failed enterprise AI pilot typically costs between $200K and $1M+ once you account for licensing, integration, staff hours, and workflow disruption. A rigorous independent feasibility assessment costs a small fraction of that — and either prevents the loss entirely or dramatically increases the odds your investment succeeds.
Not at all — it's the most common situation we encounter. Fragmented data changes the roadmap, not the destination. Our assessment identifies which use cases are viable with your current infrastructure, which require preparation, and what that preparation realistically costs and takes.
No. We accept no commissions, referral fees, or partnerships that would compromise our independence. When we recommend a technology, it's because it's the best fit for your context — and we're equally comfortable recommending that you wait, negotiate harder, or build custom.
Then you've saved yourself a very expensive mistake — and you'll receive a concrete preparation roadmap: which data, infrastructure, or process gaps to close first, in what order, and at what estimated cost. Many of our most valuable engagements end with "not yet, and here's why."
Yes. Smaller organizations often have the most to lose from a bad technology bet — and the most to gain from targeted, right-sized solutions. We scale our assessments to your size, and our operational use cases (inventory, scheduling, reporting) frequently deliver the fastest ROI in smaller settings.
Request an initial conversation. We'll listen to your situation, tell you honestly whether a feasibility assessment makes sense for you, and outline exactly what you'd receive.
Request your feasibility assessment No commitment. No vendor pitch. Just an honest first conversation.