The Startup Magazine
FEBRUARY 16, 2022
He has a wealth of experience in the data vertical, having served in previous roles at companies such as Intel, AllScripts, and Vision.bi. Others in that cohort included Zviki Shimon (CFO), Yair Areli (senior VP of global sales), Nir Mandel (VP of product management), and Aviv Canaani (VP of marketing). ” Product Focus.
VC Cafe
FEBRUARY 15, 2017
Since AI and ML startups cut across verticals (analytics, fintech, health, adtech, security, etc), it’s easier to group them under the “machine intelligence” umbrella, coined by Shivon Zillis , a partner at Bloomberg Beta. Noteworthy Machine Intelligence startups in Israel ??
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Cracking the Code
JANUARY 25, 2021
Building a ubiquitous platform that enables B2B payments at the right time and place, integrating with other suppliers’ offerings, improves the customer experience, extends Melio’s reach and fuels the rise of adoption within vertical SaaS products. 25% of the value of the 10 public cloud companies born in Europe and Israel.
Cracking the Code
MARCH 28, 2022
Back in 2016, Europe and Israel had only four public companies worth less than $9B combined and local cloud companies had raised just $900M throughout 2015. Today, Europe and Israel have generated 23 public companies worth $231B and private cloud financing reached c. Annualised, this would be 2.7x larger than last year!
VC Cafe
SEPTEMBER 21, 2023
So much has happened in the generative AI space globally, and in Israel since we published the previous version of the Israeli generative AI landscape, back almost exactly five months ago. For example, Munch , providing automated vertical video clips from long form content or KwaKwa , the latest product by Piggy, powering communities.
VC Cafe
NOVEMBER 7, 2022
Generative AI will really become magic when it moves from 'playful' to 'useful' – we will use multiple generative AI tools at work in the future, like we use grammarly and canned responses today… AI will become more vertical, and specific per role — Eze Vidra (@ediggs) November 5, 2022.
VC Cafe
JULY 7, 2023
Most of the companies that raised these mega rounds are relatively early stage in terms of product and monetisation (if at all) and about half of the companies that raised large sums, are developing LLMs, which generally requires deep pockets to cover 1) cloud costs, 2) expensive deep learning engineers 3) get the data to train the models.
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