Find where your healthcare AI product breaks. Before your investor does.
Pressure Test runs the interrogation your next meeting will. First session free.
Pressure Test runs the interrogation your next meeting will. First session free.
Pressure Test surfaces the gaps. The courses and advisory work are built to close them — each one aimed at a different stage of the same problem.
Two failure modes. Most founders experience both before they can name either. The first is market selection: the product works but the market you chose can't buy it — wrong procurement process, wrong evidence requirements, wrong budget owner. The second is trust infrastructure: the pilot succeeded but the deal stalled because your buyer's compliance team, procurement, and legal have questions your product team never anticipated. Both feel like a sales problem. Neither one is.
Here's where the gaps show up:
The product is almost never what's broken. What's missing is the infrastructure around it — the right market, the right evidence, the right procurement readiness. Most companies find out after the deal goes quiet.
Companies where I've built, shipped, or sold
Built products at companies backed by
If advisory isn't the right fit yet, these are the structured starting points — built from the same frameworks, designed for founders who need to do the work themselves first.
Before you build the wrong proof strategy or spend another year in the wrong segment.
Two full days, one week apart, for founders getting interest but no traction who aren't sure if the problem is the product, the pitch, or the market. Delivers a Healthcare-Market Fit Map: buyer prioritization grounded in procurement reality, proof requirements across six categories rated by time-to-close, and a clear verdict on whether to pursue, validate, or reposition.
Apply on MavenGreat pilot. No contract. That's not a sales problem.
A 3-week course for founders with working products and stalled deals. Covers the product-side work that makes enterprise deals closeable: positioning, procurement documents, pilot structure, and evidence. No pipeline frameworks, no closing techniques. Built from 18 years on the inside of healthtech, watching good products fail to get bought because nobody built what the buyer actually needed to see.
Apply on MavenWorking outside healthtech, or leading AI adoption inside a larger org? Mandate to Action is an executive sprint that turns AI strategy conversations into a governance structure and 90-day execution plan. Starts with a 90-minute Signal Check.
Every engagement is built around the problem in front of you.
Ongoing strategic support plus ad hoc calls for the decisions that can't wait. Regulatory path, GTM sequencing, fundraising positioning, vendor vs. build decisions. Includes pitch feedback, financial model review, and narrative development when fundraising is active. Best engaged 6-8 weeks before a raise, but useful at any point where the next decision feels high-stakes. A regular thought partner, not a deliverable factory.
Delivers a sharpened value prop, persona-level messaging, and a case study framework you can use in sales conversations. Two weeks. You walk away with language that works in the room where the deal gets decided, not the room where the demo happens.
Sequencing features against regulatory milestones, buyer requirements, and fundraising timelines. What to launch as wellness now vs. what needs clinical validation. What to promise in the next board deck and what to hold back.
I've navigated this at AliveCor (FDA-cleared cardiac AI, first medical device accessory for Apple Watch) and Clip Health (FDA-authorized diagnostics under EUA). The sequencing decisions you make now determine whether you're enterprise-ready in 12 months or still explaining why you're not.
Mapping the path into a specific buyer segment. Buyer personas, objection handling, competitive positioning, and sequencing recommendations. One segment at a time, done right.
I've sat on the buying side of these decisions at companies selling into Moderna, Gilead, Novartis, BMS, and J&J. I know what makes procurement move and what makes them stall.
Deeper involvement on specific workstreams: product strategy, enterprise readiness, operating model design. Limited to two fractional clients at a time. Not a name on your deck. An operator in the work.
Your team can model the multiple. But when the target says "FDA-ready," "AI-powered," or "enterprise-grade," how do you know if that's real? Most deal teams aren't built to evaluate whether the AI claims, regulatory posture, and product architecture will survive post-close.
A 48-hour preliminary assessment. Enough to know whether the product claims hold up and whether full diligence is worth the investment. Credits toward a full engagement if you proceed.
A structured evaluation across four dimensions:
Regulatory Reality — Will this pass enterprise procurement? Compliance posture across FDA, HIPAA, EU AI Act, and SaMD classification. Not whether they checked the boxes, but whether the boxes were the right ones.
Product Durability — Will this survive real enterprise deployment? Integration readiness (EHR, billing, SSO), the gap between what sales promises and what the product delivers, and whether unit economics hold at scale.
Organizational Substance — Did they build a company or a demo? Leadership depth, quality systems, design controls, and roadmap credibility relative to the team's actual capacity.
AI Integrity — Is the AI real, defensible, and governable? Model validation on representative clinical data, not benchmarks. Data provenance and population coverage. Whether "AI-powered" means a validated model or a marketing claim wrapped around a rules engine.
Deliverable: Red/yellow/green scoring with an overall verdict (Scale-Ready, Conditional, or Rewrite Required). Risk-prioritized findings, remediation cost estimates, IC-ready summary, and executive debrief.
Turnaround: 2-3 weeks for full diligence. 48-hour preliminary read available for fast-moving deals, creditable toward the full engagement.
Priority deal support and quarterly regulatory briefings for firms with active healthcare portfolios. Retainer-based. You get a direct line when a deal is moving fast and a standing check-in when it's not.
I joined as the first employee at a clinical trial technology company. Interviewed buyers, narrowed the platform to 2 workflows instead of building broad, and wrote a one-page MVP charter before a line of code was written. Built the engineering function before we hired a VP of Engineering, then grew the overall team from 0 to 65 across three countries. Handled sales enablement including FDA, ICH, ISO, and GDPR maturity objections and qualification audits, and securing a Top 5 biopharma as a client. Revenue grew 200% year over year. ARR expanded 3.8x. Retention stayed above 90% through Series A.
At a company where nobody had managed quality for years, I came in and a single audit cycle surfaced 84 non-conformances in three months and $2.3M in quality costs the board hadn't seen. At a separate company, 10 quality system gaps and MDR filing delays months past FDA deadlines. I know what to look for in diligence because I've been the person who had to find it and fix it on the inside.
As an EIR at the University of Michigan, I evaluated a voice AI mental health product with a psychiatrist-inventor. The technology worked. I ran discovery interviews with psychiatrists. Every one of them said some version of "that looks really cool" and none of them said "I need this." No workflow pain. No billing hook. No urgency. They were getting by without it. I diagnosed it as a vitamin, not a painkiller, and recommended licensing the technology to an existing EHR platform instead of building a standalone company.
"Arvita crushes challenging problems and creates order where there is uncertainty. I hired her and she became an integral member of the leadership team. I hired her again to join me on the founding team at Korio."
"I love Arvita's discipline and the structure of her thinking. Her work through the Foundry was thorough, well-organized, and genuinely useful. I can't thank her enough—we're actively working to match her to her next technology."
18 years on the inside of healthtech at AliveCor (FDA-cleared cardiac AI, first medical device accessory for Apple Watch), Vineti (CAR-T supply chain powering $8B+ in therapeutic revenue, acquired by J&J), Clip Health (FDA-authorized diagnostics, YC-backed), and Endpoint Clinical (clinical trial technology, acquired by LabCorp). Products serve Moderna, Gilead, NHS, Novartis, Roche/Genentech, BMS, J&J, AbbVie, and Takeda.
At four of those companies, I also served as CISO and DPO—responsible for security posture, data privacy, and HIPAA compliance across products handling patient data, CAR-T supply chain records, and clinical trial information. That combination of product leadership and security ownership is why I catch the risks that pure product advisors miss and pure security consultants can't contextualize.
Carnegie Mellon CDAIO. MBA, Babson College. Regulatory affairs and quality engineering credentials for medical devices. Former EIR at University of Michigan—evaluated a lab-stage technology and killed it when the demand wasn't there.
Currently: Diligence team, NDVC. Pop-up board member, IOVC. Illumyn Board Fellow. Advisor at Alchemist Accelerator, Redesign Health, Plug & Play Medtech, Rutgers University, and The Batchery. Board member, Red Dot Ranch Foundation.
If what's on this page maps to where you are, book a call. We'll figure out in 20 minutes whether there's a fit and what working together would look like.
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