Vahana Labs helps healthcare executives and investors decide where technology can create meaningful enterprise value — and what has to change for that value to actually appear.
The question is not simply whether the technology works.
It is whether the organization can capture the value.
Choose where AI deserves investment, what should scale, what should stop, and how value will be measured.
Find where technology should improve margin, capacity, throughput or quality — and why the expected leverage has not appeared.
Decide what should be standardized, automated, integrated, centralized or deliberately left alone.
Test whether a technology thesis can realistically translate into operational and financial value.
We ask five questions:
Growth, margin, capacity, quality, speed, cash or risk.
The actual constraint, not just the visible symptom.
Process, standardization, automation, software, AI — or some combination.
Workflow, roles, governance, evidence and decision rights.
A measurable bridge from investment to operating performance.
A focused assessment of a consequential AI or technology decision.
We examine the value pool, operating constraint, technology thesis and path to value capture.
Fund. Fix. Test. Narrow. Defer. Or stop.
For organizations that know where they want technology to create value but need the operating model, sequence and governance to make it happen.
Ongoing strategic support for CEOs, operating partners and boards making interconnected AI, technology and operating decisions.
Vahana Labs is led by Arvita Tripati, a healthcare technology operator with nearly two decades of experience across digital health, SaMD, diagnostics, clinical AI, product, regulatory strategy and enterprise adoption.
Her work has spanned early-stage companies through global healthcare organizations, including environments involving the FDA, NHS, VA, Gilead and Moderna.
Because in regulated healthcare, technology strategy cannot be separated from the operating system around it.
More on the backgroundWe help determine where the value should come from, what must change to capture it, and what evidence should exist before you scale.
Discuss a decision →