RANDOM FOREST is a boutique early-stage fund.
We focus on market disruptive ventures, based on cutting-edge Machine Learning and Artificial Intelligence technologies.
Along with our in-house algorithm team and experienced partners, we provide a unique offering of support to those startups we choose to invest in.
"Software is eating the world,
but AI is going to eat software"
Jensen Huang, CEO Nvidia
RANDOM FOREST was founded by a team of experienced entrepreneurs, CEOs, and AI professionals. Harnessing our broad entrepreneurial, technological and operational experience, we established a boutique venture creation foundry with a special focus on Artificial Intelligence.
The founders serve as business and managerial mentors for the portfolio companies, bringing their experience and connections to mission-critical tasks.
Former CEO of Nice Systems
Gideon Bar Sinai
Former CEO of Final
(an Algo-trading Unicorn)
Founder of Pontis
(acquired by Amdocs)
MEET THE TEAM
In today’s early-stage investment landscape, with increased numbers of startups and massive hype around disruptive technologies, we see the need for change in the way VCs evaluate companies and the way they onboard and support them.
Random Forest has considered these challenges seriously and consequently established a robust team of top talents. We have brought together a team of business professionals with the precise capabilities to grow our network, bring in the most inspiring entrepreneurs, and proactively discover unique investment opportunities.
Our team of in-house data scholars have deep, hands-on experience in leading and building projects and businesses in the fields of Deep Learning, Natural Language Processing and Predictive Modeling. Our unique team provides us with in-depth analysis to enhance our due-diligence process, as well as provides expert technology services to those we invest in, elevating their technology to achieve success.
We invest in ventures with superior technologies at their very early stage of formation, led by extraordinary entrepreneurs who are passionate about disrupting the market in which they operate. We support entrepreneurs with Machine Learning development services to accelerate their development, allowing their venture to enjoy faster growth.
Unique Technology Leads to Unique Valuation
SELECT & BUILD
We have developed a two-step methodology for screening and building successful AI ventures
We identify good businesses with a data-technology barrier.
Our proprietary due-diligence process enables us to invest in winning ventures by deep diving into the business and data aspects.
Our data scholars team-up with our selected entrepreneurs.
In the 6 month team-up program, chosen entrepreneurs work together with our in-house data scholars to accelerate their ventures.
Traditionally, we used to evaluate a “regular” software-based company on having the right talents, checking the company’s product and market, and ensuring the product fits the market and solves a big pain for its customers.
But, when it comes to evaluating AI companies, checking the same old product-market fit is just not enough. We now must also add data into the equation.
So instead of a product-market fit, we need to carefully check the Product-Market-Data (PMD) fit.
Data is now a big part of the equation, which calls for a paradigm shift in the way VCs invest.
Qbiq brings cutting-edge artificial intelligence, generative design, and optimization technologies to real-estate planning. With a click of a button, hundreds of cloud processors, loaded with thousands of years of architectural experience, process planning requests, analyze different layout alternatives, and optimize results.
We are constantly looking for talented AI experts to enhance our partners and our research teams.
PhD or MSc. in Physics, Mathematics, Computer Science, Statistics or Engineering from a top university
Experience in Machine-Learning or other Data Mining technologies
Excellent problem-solving capabilities with critical thinking skills
Enthusiastic and passionate for futuristic technology discoveries
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