eHealth Ventures: Israel can lead AI Healthtech… If startups focus on real-world impact

“We believe that AI in healthcare must be grounded in clinical utility and measurable outcomes. As investors, we are cautious of hype and prioritize startups that demonstrate real-world validation, ethical data practices, and a clear path to adoption,” said Ophir Shahaf and Talor Sax from eHealth Ventures. “Israel has the potential to lead in this space by leveraging its unique blend of technical excellence and access to centralized healthcare data.”

The pair joined CTech for its VC AI Survey to share insights on how Israel operates within the VC space, especially regarding AI and healthcare. “We appreciate the opportunity to contribute to this survey and look forward to continued collaboration across the AI and venture communities,” they added.

eHealth Venutres Team

You can learn more in the interview below.

Fund ID
Name and Title: Ophir Shahaf, Talor Sax
Fund Name: eHealth Ventures
Founding Team: Talor Sax, Dr. Yossi Rosenblum, Yossi Lovton, Adv. Orly Sternfeld, Ophir Shahaf, Rose Schwartz, Aryeh Stern, Tali Lipszyc
Founding Year: 2016
Investment Stage: Early stage
Investment Sectors: Healthcare

On a scale of 1 to 10, how has AI impacted your fund’s operations over the past year - specifically in terms of the day-to-day work of the fund's partners and team members?

5 - We’ve started using advanced tools such as large language models like ChatGPT and Microsoft Copilot. These tools support tasks like due diligence preparation, drafting investment materials, and refining presentation decks. However, these are still limited in scope and aren’t yet core to our investment processes. They serve as productivity tools, not decision-making ones.

• CRM and Relationship Management: Improving our ability to track interactions, manage deal flow, and maintain personalized, timely communications with entrepreneurs, co-investors, and other stakeholders.
• Email Processing and Internal and External Communication: Streamlining routine correspondence and prioritizing important conversations, allowing team members to focus on strategic interactions.

Overall, AI has become indispensable, enhancing not only the efficiency of our operations but also the quality and strategic value of the work performed by our partners and team.

Have you already had any significant exits from AI companies? If so, what were the key characteristics of those companies?

No significant exits yet from AI companies.

Is identifying promising AI startups different from evaluating companies in your more traditional investment domains? If so, how does that difference manifest?

We are a fund focused on healthtech, so for us AI is a supporting technology, not the main product. We still assess the company based on the clinical need, regulatory pathway, market potential, and go-to-market plan. AI adds a layer of complexity and promise, but it is never the only consideration.

What specific financial performance indicators (KPIs) do you examine when assessing a potential AI company? Are there any AI-specific metrics you consider particularly important?

The KPIs we consider are generally the same as for any early-stage health-tech company: clinical progress, validation, pilot studies, engagement with health systems or payers, and regulatory milestones. AI-specific KPIs such as model performance, accuracy, and generalizability are evaluated, but only in the context of the clinical value they bring.

How do you approach the valuation of early-stage AI startups, which often lack significant revenues but possess strong technological potential?

We approach valuation by focusing on several qualitative factors: the strength of the team, depth of domain expertise, proprietary access to datasets, defensibility of the AI model, and clinical or commercial traction. While lack of revenue is common, we still expect some validation—be it pilots, LOIs from hospitals, or early usage metrics. We also look at benchmarks from similar companies and evaluate whether the startup has a realistic path to regulatory clearance and reimbursement, which are key in healthcare

What financial risks do you associate with investing in AI companies, beyond the usual technological risks?

In healthtech, we often see AI companies underestimating the costs of data acquisition, clinical validation, and regulatory compliance. There is also significant risk of overpromising capabilities and encountering slower-than-expected adoption in clinical environments. Infrastructure and model maintenance costs can also be burdensome. AI startups, particularly in healthtech, often underestimate the cost and complexity of acquiring high-quality, annotated data that is clinically relevant. Regulatory uncertainty also introduces financial risk, especially if an AI solution needs to be significantly altered to meet FDA or CE standards. Another risk is over-reliance on third-party infrastructure (e.g., cloud costs) which can become unsustainable. There’s also a dependency on external APIs or data sources that may change terms or availability.

Do you focus on particular subdomains within AI?

Not specifically. We focus more on the clinical need and value proposition. The choice of AI technology is secondary and must fit the problem the company is solving.

How do you view AI’s impact on traditional industries? Are there specific AI technologies you believe will be especially transformative in certain sectors?

AI has tremendous potential to disrupt traditional industries by automating tasks, improving decision-making, and reducing operational costs. In healthcare, we foresee major transformation in diagnostics (radiology, pathology), care coordination, billing, and clinical documentation. Generative AI could reshape how medical content is created and tailored for both clinicians and patients. Additionally, predictive analytics powered by AI could enable earlier intervention and better chronic disease management.

What specific AI trends in Israel do you see as having strong exit potential in the next five years? Are there niches where you believe Israeli startups particularly excel?

We see strong exit potential in AI applications at the intersection of healthcare and data-driven decision-making. Israeli startups are particularly strong in computer vision for medical imaging, remote patient monitoring using AI-powered analytics, and digital pathology. There's also significant momentum in AI for clinical trial optimization and real-world evidence generation. Thanks to Israel’s robust academic ecosystem and early adoption by health providers, companies that can demonstrate clinical and economic value are well-positioned for acquisition by global med-tech or pharma companies.

Are there gaps or missing segments in the Israeli AI landscape that you’ve identified? What types of AI founders are you especially looking to back right now in Israel?

While Israel has a wealth of technical AI talent, we find that some segments — like operational AI for health systems (e.g., hospital logistics, payer automation, claims management) — are underrepresented. We’d like to see more startups addressing these critical infrastructure needs. We’re especially looking to back founders who combine strong AI expertise with deep understanding of clinical workflows or healthcare economics. Multidisciplinary teams that include both technologists and healthcare professionals tend to build more viable, scalable solutions.