For founders who need commercial traction, AI capability, or both.
You have a product and maybe some pilots, but founder-led sales has hit a wall and your positioning isn't landing.
Or you know AI should be changing how your regulatory and commercial operations run, and nobody on your team can both scope that work and build it.
I work on both problems, with 18 years taking healthcare technology to market and a machine learning degree that is back in daily use. The proof is working software: I founded Keenr AI and built its 510(k) Predicate Finder, live at keenr.ai (opens in new tab).
If any of this sounds familiar, we should talk.
Primary fit: CEOs and founders at post-product health-tech, medtech, and life sciences companies, typically seed to early Series A, who need to accelerate growth but don't have the commercial firepower in-house. Particularly deep in medical imaging, radiology AI, and clinical trials.
You get a partner who moves fast and works alongside your team, not from the sidelines.
Also a fit: European companies entering the US market. Medtech consultancies turning services into products. Mid-size health-tech and medtech companies that need working AI systems and senior AI leadership without a full-time hire. Tech transfer offices navigating commercialization.
Every engagement is tailored to your specific challenge. I operate as an impact partner with shared accountability, not a consultant who prescribes frameworks and disappears. The focus is outcomes, not hours. The work falls into two practices.
For companies that have built something real and need it to sell.
Deals that actually close. Full-cycle business development: identifying targets, hunting opportunities, qualifying leads, and managing the process to get agreements across the finish line. A deep network across therapeutics, devices, and digital health to accelerate conversations and open doors.
A roadmap from product to revenue. Design and execute market entry strategies, whether launching a new product, entering a new segment, or expanding internationally. Deep experience in US market entry for European health-tech and imaging AI companies.
For a structured 4-6 week engagement with defined deliverables, see the GTM Accelerator.
The foundation that makes everything else work. Pressure-test your value proposition, sharpen your messaging, and align your product to what the market actually wants to buy. Clear positioning turns conversations into closed deals, especially in complex spaces like medical imaging and radiology AI.
New revenue hiding in plain sight. Uncover adjacent opportunities, productize services, or launch new offerings. Find high-margin use cases in your existing capabilities, particularly for consultancies and service businesses ready to scale.
Senior commercial leadership without a full-time hire. I step into CBO, VP BD, or similar roles on a fractional basis. Full integration with your team, operating and executing, not just advising.
From lab to market. Support for tech transfer offices, university ventures, and incubators, including technology evaluation, commercialization roadmaps, and buyer-ready materials that resonate with corporate BD teams and investors.
For companies that need AI built into how they operate. Strategy and the build from one person who has shipped in regulated healthcare.
Find out what's worth building. A short, structured engagement that maps your regulatory and commercial workflows and identifies where agentic AI removes real bottlenecks. You leave with a ranked roadmap and a clear build-versus-buy call on each use case.
Production systems with a defined scope and timeline. I design and ship agentic workflows for health-tech operations: BD intelligence systems that find and qualify targets, market and competitive intelligence engines, regulatory research workflows, and founder content engines. Each build includes documentation and handoff, with an optional maintenance retainer once it's running.
Senior AI leadership without the $300K+ full-time hire. I own your AI roadmap, ship the first systems myself, set up governance that stands up to HIPAA and FDA scrutiny, and train your team to run what gets built. Chief AI Officer, Head of AI, or whatever title fits your org chart.
Working proof: I founded Keenr AI, an agentic platform for medtech regulatory intelligence, and built its 510(k) Predicate Finder, live at keenr.ai (opens in new tab).
Try Keenr AI's 510(k) Predicate Finder (opens in new tab) More on the AI practice
Not sure where to start on the commercial side?
Take an assessment to see where to focus.
Take the 3-minute Commercial Readiness AssessmentA few examples of recent engagements (details anonymized for confidentiality):
Challenge
Transform a services-heavy business into a scalable, AI-native product company while protecting existing revenue.
What I Did
Outcome
Gross margins improved by 40% within six months. SaaS product launched. Business now has three distinct revenue streams with improved scalability.
Challenge
Business development depended on manual research, scanning trial registries and company news to find biopharma sponsors with imaging-heavy pipelines. Founder time was the bottleneck.
What I Did
Outcome
Target research that took hours per account now runs in minutes. The pipeline list refreshes weekly without consuming founder time.
Challenge
Enter the US market with limited resources, unclear product-market fit, and no local presence.
What I Did
Outcome
12+ qualified partnership conversations in first 4 months. First pilot launched within 6 months and converted to paid customer. Three additional pilots pending.
Challenge
Strong technology but unclear value proposition for the life sciences segment.
What I Did
Outcome
Sharper go-to-market messaging; improved sales conversations.
Challenge
A university tech transfer office had a promising theranostic imaging technology but unclear commercial pathways in a change-resistant industry.
What I Did
Outcome
University team received clear basis for investment decisions. Two high-priority applications identified with defined adoption pathway.
I started as a scientist. MS in machine learning, PhD in medical imaging, years in the lab running multi-modality preclinical imaging studies for pharma. I liked the science, but I kept asking different questions: why does this technology matter to anyone outside this building? Who is going to buy it? How?
I transitioned to a business development role at a med device company. That led to seven years in management consulting, advising Fortune 500 healthcare companies spanning payers, pharma/life sciences, and med-device on innovation strategy. I learned frameworks like jobs-to-be-done and lean startup, but more importantly I learned how companies actually make decisions, what holds them back, and how they could apply principles of innovation to be more nimble and find market success.
I then spent several years at mid to late stage SaaS and medtech startups. I have led customer success teams, built strategic partnerships, and built sales and BD motions from the ground up. Eighteen years total, mostly spent figuring out how to take innovations to market and build strong revenue streams.
Then large language models made my machine learning degree current again. Over the past two years I went back to building. I founded Keenr AI, an agentic platform for medtech regulatory intelligence. I built its 510(k) Predicate Finder, live at keenr.ai (opens in new tab), and I have multi-agent BD systems running inside client businesses today. Each one works because of the domain knowledge underneath it: knowing which workflows matter and what regulators and buyers expect.
Today the practice runs on two fronts. On the commercial side I help founders sharpen positioning and close partnerships, with deep experience in US entry for European health-tech companies. On the AI side I find the use cases worth building and then build them. Recent engagements include the transformation of a clinical trials consultancy into an AI-native product company and US market entry for a European radiology AI startup.
"AI commoditized the advice layer of consulting. What's left is judgment and working systems. That's what I sell."
Recent posts from LinkedIn.
Most professionals are still using AI the way they used ChatGPT in 2023. Type a question, get a summary, go back to their spreadsheet. A smaller group has moved into something fundamentally different: building agentic systems that execute multi-step workflows autonomously. The gap is compounding every month.
Dario Amodei said AI 'has gotten better than radiologists at doing scans.' Jensen Huang argued AI creates radiology jobs, not destroys them. Both got it partly right, partly wrong. The truth sits between the hype and the dismissal: AI won't replace radiologists this decade, but the nature of the work is shifting.
One year into building my own advisory practice, I confront an uncomfortable truth: AI has commoditized most expert knowledge. So what's actually left to sell?
Whether it's a stalled pipeline, a positioning problem, or an AI project that never shipped, tell me what you're working on. No pitch, no pressure. Just a conversation to see if there's a fit.
Prefer LinkedIn?
Connect with me (opens in new tab)Prefer email?
vinny@kspacegrowth.comThanks for reaching out. I'll be in touch soon.
