“We focus on future potential rather than current revenues”

“We see AI as a transformative force across every industry and remain committed to backing Israeli founders who can combine deep technology with commercial execution,” said Lior Hanuka, CEO at HiCenter Ventures. “When valuing early-stage AI startups, we focus on future potential rather than current revenues. We assess market size, team strength, and the defensibility of data and models. For AI specifically, we also evaluate network effects, how more usage and data improve the model over time, and the scalability of cost structures.”

HiCenter is a technology entrepreneurship and investment center, which has been promoting tech ventures in Haifa since 2008. The center has facilitated the growth of over 90 companies, bringing more than 900 million NIS to Haifa’s economy, aided by private investments and grants.

Hanuka joined CTech for its VC AI Survey to share some insights on how the company is adjusting to a world taken up by artificial intelligence. “The goal is to distinguish between technical promise and true commercial potential,” he added.

Lior Hanuka, CEO of HiCenter

You can learn more in the interview below.

Fund ID
Name and Title: Lior Hanuka, CEO
Fund Name: HiCenter Ventures
Founding Team: Hila Ehrenreich, Einat Klein, Moran Ben Harosh, Itzik Kushel
Founding Year: 2009
Investment Stage: Seed, Pre-Seed
Investment Sectors: We have no strict sector preference and focus instead on backing exceptional AI founders with scalable, global potential.

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?

7. Over the past year, we have adopted AI-driven tools for faster data analysis, benchmarking, and trend identification, which significantly reduced the time needed for initial screening. While human judgment remains essential for final decision-making, AI enhances efficiency, improves accuracy, and allows our team to focus more on strategic considerations rather than manual tasks.

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

Not yet.

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

Yes. In AI ventures, the core question is the use case: what problem the product solves and how monetization can be achieved at scale. Alongside the standard evaluation pillars—team quality, market size, product maturity, and go-to-market strategy—we also examine AI-specific factors such as the quality and accessibility of data, the defensibility of the underlying models, and the pace of adoption in the target industry.

Increasingly, we also consider ethical AI, bias mitigation, and governance readiness, as these are critical to long-term scalability and global adoption.

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?

When assessing AI companies, we look beyond traditional financial metrics and focus on indicators that are unique to the sector. These include the quality and defensibility of data assets, the unit economics of scaling GPU and cloud costs, and the time required to productize models and deliver them to customers.

We also examine model performance, reliability, and bias mitigation, as well as customer adoption and retention, since real-world stickiness validates the ROI of AI products. Finally, we evaluate compliance with emerging AI governance and privacy frameworks, which is becoming a critical factor for long-term scalability.

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

When valuing early-stage AI startups, we focus on future potential rather than current revenues. We assess market size, team strength, and the defensibility of data and models. For AI specifically, we also evaluate network effects, how more usage and data improve the model over time, and the scalability of cost structures.

The goal is to distinguish between technical promise and true commercial potential.

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

Investing in AI companies carries financial risks that extend beyond technology. High cloud and GPU costs can quickly erode margins, while reliance on external data sources may limit scalability and profitability. The rapid pace of market change and aggressive new entrants increase pricing pressure and shorten product lifecycles. On top of that, evolving regulatory requirements can raise costs and delay revenue.

Do you focus on particular subdomains within AI?

No.

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 is transforming traditional industries by automating processes, enhancing decision-making, and enabling new business models. Machine learning, NLP, and generative AI are already driving change in healthcare, finance, food tech, and business insights.

We also see a strong impact in manufacturing, logistics, energy, retail, and cybersecurity, where AI improves efficiency and resilience.

Ultimately, these technologies are not just streamlining operations, they are reshaping competitiveness across entire sectors.

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?

In the next five years, Israeli AI startups will show the strongest exit potential in cybersecurity, where AI-driven threat detection and data protection are in high demand. Fintech and insurtech solutions around compliance, fraud prevention, and risk analysis also present significant opportunities. We also see strong potential in medical AI, especially imaging and clinical decision support, and in energy optimization, where AI drives efficiency and sustainability.

In addition, Israel’s defense and government-related AI capabilities remain an area with strategic global interest.

Finally, the Blue Economy could be truly transformative, as AI reshapes oceans, ports, shipping, and aquaculture fields where Israel can become a global leader.

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?

Israel is strong in cybersecurity and infrastructure, but there are clear gaps in applied AI for sectors like healthcare, energy, and manufacturing.

Another gap is in product-oriented founders: there is plenty of world-class technical talent, but fewer entrepreneurs who can translate breakthroughs into global category leaders.

We are especially looking to back founders who combine deep technical expertise with domain-specific knowledge in these industries. The ability to move quickly to market, build scalable teams, and execute commercially is just as important as technical excellence.

Our focus is on entrepreneurs who can turn advanced models into sustainable, industry-changing businesses.