F2 is an early stage VC firm that typically invests the first check into the most promising technology startups in cloud infrastructure and applied AI out of Israel. The partners have been investors, operators, and engineers in startups and multinational giants that have delivered outlier returns over the last 20 years. With $500 million assets under management, F2 has developed a systematic method for sourcing and backing exceptional founders before others are ready.

F2 Venture Capital

SeedIL Ventures is a seed stage investment fund focusing on Israeli related companies in any sector except medtech/biotech and heavy Hardware. After investment, SeedIL is committed to ensuring that portfolio companies reach their full potential by providing on-going coaching and connections through its extensive network, including the Limited partner's connections and intelligence.

SeedIL Ventures

NextLeap Ventures

ICONYC labs is a accelerator firm specializes in early-stage and startups. It invests in early-stage Israeli tech startups looking to accelerate growth and cut time to market.  ICONYC seeks investments in Enterprise Software, Internet of Things (IoT), Artificial Intelligence (AI), Digital Health, Drones, Fintech, Digital Media. Arie Abecassis and Eyal Bino founded it on March 29, 2015, with its headquarters in New York City.

ICONYC labs

Amiti is a venture capital firm based in Tel Aviv that invests in Israeli & Israeli related start-ups in Seed & A rounds. Amiti’s Partners seeded and helped scale Israel's best tech teams, among them Innoviz, Waze, AppsFlyer, Valens, Vayyar, Cycognito, Aidoc, NextSilicon and many more. Amiti's partners bring together 30 years of experience in investing in early stage start-ups, building market leaders and taking them to exit.

Amiti Ventures

OurCrowd is a venture investing platform that enables institutions and individuals to invest and engage in emerging companies. OurCrowd was started in 2013, driven by the idea that the business of building startups grows bigger and better when the global 'crowd' gains access to VC-level investment opportunities.

OurCrowd

NGP Capital is a global thesis-driven, early-stage VC with a vision to unleash the magic of technology.  With an AUM of 1.6B, NGP invests in B2B companies from Series A onwards in Europe and the US in enterprise software, industrial tech, cybersecurity, and infrastructure. For nearly two decades, NGP Capital has invested in more than 100 companies of which 18 are unicorns and 11 went on to IPO.

NGP Capital

Alpha Wave is an investment company that has three main verticals; private equity, private credit, and public markets. The objective of the private equity partnerships is to invest in best-in-class venture and growth stage companies and endeavors to be helpful, long-term partners to these exceptional founders and management teams; credit, which includes direct private lending to businesses looking for funding solutions; and public markets in an uncorrelated strategy. Alpha Wave has offices in New York, Miami, London, Monaco, Madrid, Abu Dhabi, Tel Aviv, Bangalore, and Sydney.

Alpha Wave Global

Lenovo Capital and Incubator Group is an accelerator and venture capital firm.

Lenovo Capital and Incubator Group (LCIG)

Astarc Ventures is an early stage investment fund which aims to partner with new age startups to help them grow into market leaders of tomorrow.

Astarc Ventures

Dataloop AI

DataLoop's data management and annotation platform streamline the process of preparing visual data for machine and deep learning.  Dataloop is used for building and deploying powerful computer vision pipelines – data labeling, automating data ops, customizing production pipelines, and weaving the human-in-the-loop for data validation. This eliminates data challenges for companies, allowing them to focus their resources on their core business.  The company was founded in 2017 and is based in Herzliya, Tel Aviv.

Based in Israel, Dataloop offers a data management platform for unstructured data that allows users to connect, search, and annotate data for training ML models. The platform leverages AI to automatically label any type of unstructured data including images, videos, LiDAR, text, and audio. Dataloop uses deep learning models, pre-trained classes, and smart trackers to run automatic annotations. It also uses human annotators to ensure quality of data. In addition, developers can use its automation pipeline feature to build event-driven data pipelines to automate the pre-labeling of data to be used in ML training. The company also offers a data management platform to sort, filter, query, and obtain insights from unstructured data. Dataloop also offers a GenAI Engine to fine-tune foundation models with proprietary enterprise data through continuous learning pipelines and reinforcement learning from human feedback (RLHF).

The toolkit to build machine learning applications at scale

Machine Learning Infrastructure

Dataloop

Dataloop AI Launches a Marketplace to Drastically Enhance AI Development Processes and Slash Time-to-Market

Based in Israel, Dataloop offers a data management platform for unstructured data that allows users to connect, search, and annotate data for training ML models. The platform leverages AI to automatically label any type of unstructured data including images, videos, LiDAR, text, and audio. Dataloop uses deep learning models, pre-trained classes, and smart trackers to run automatic annotations. It also uses human annotators to ensure quality of data. In addition, developers can use its automation pipeline feature to build event-driven data pipelines to automate the pre-labeling of data to be used in ML training. The company also offers a data management platform to sort, filter, query, and obtain insights from unstructured data. Dataloop also offers a GenAI Engine to fine-tune foundation models with proprietary enterprise data through continuous learning pipelines and reinforcement learning from human feedback (RLHF).Key customers and partnershipsIts notable customers include LinkedIn, Vimeo, Intel, and Toyota.Funding and financialsDataloop raised USD 33 million in a Series B funding round in November 2022 co-led by NGP Capital and Alpha Wave Ventures. It earmarked the funds towards global expansion, specifically for building teams in the US, Europe, and India. The company had a workforce of 60 employees and planned to grow it to 80 by the end of the year.

Datagen provides a self-service synthetic data platform that generates visual synthetic data of humans for computer vision applications. The platform allows users to write their own code to generate labeled synthetic data for faces, full body, and humans in motion in the form of images and videos to test and train AI models while retaining complete control over the data. The data covers a range of computer vision tasks including face landmark detection, face and hair segmentation, facial recognition and identification, full body pose estimation, full body segmentation, and behavior detection.Key customers and partnershipsThe company serves three of the top five global technology companies and Fortune 500 companies across the automotive, smart fitness, AR/VR/metaverse, smart office, and home security industries. Its notable customers include Google, Toyota, NVIDIA, IBM, and Intel.Funding and financialsIn March 2022, the company raised USD 50 million in a Series B funding round led by Scale Venture Partners. The funds were utilized to bolster its position in the market.Datagen reported to have recorded 8x growth in revenue in 2022.

Datagen

Weights &amp; Biases offers a platform that allows users to build models with experiment tracking, data set and model versioning, data visualization, hyperparameter optimization, and model management. The platform enables users to automatically retrain and re-evaluate models and centrally manage all model versions through every lifecycle stage—from development to staging to production. It also helps to visualize comparisons between model versions to evaluate performance and identify regressions before model deployment. It also offers toolkits such as <a href="https://sp-edge.com/updates/19172">W&amp;B Weave and W&amp;B Production Monitoring </a>to build and monitor data- and ML-powered applications, respectively, through interactive visualizations.The company also offers a <a href="https://sp-edge.com/updates/17880">suite of tools (W&amp;B Prompts) </a>to support large language model operations (LLMOps). W&amp;B Prompts includes tools and features for experiment tracking, debugging, and collaboration, as well as a one-click method to evaluate and score prompts through the OpenAI Eval’s framework.The company provides the platform through a free tier and under a subscription model for up to USD 50 per user per month.Key customers and partnershipsWeights &amp; Biases served more than 700,000 ML practitioners as of August 2023. Its notable include NVIDIA, Toyota, BMW Group, Samsung, Fujifilm, Truebill, and Clear Capital.The company has <a href="https://sp-edge.com/updates/18663">partnered with Lambda </a>, a GPU cloud computing provider, to offer its MLOps platform integrated with the infrastructure services of the latter, catering to enterprises dealing with AI and deep-learning workloads.Funding and financialsIn August 2023, the company raised <a href="https://sp-edge.com/updates/20874">USD 50 million in a strategic investment </a>round at a valuation of USD 1.25 billion, led by Daniel Gross and Nat Friedman. The round also saw participation from Sapphire Ventures, Coatue, Insight Partners, and other investors. The company aimed to utilize the fresh funds to further develop its ML tools, including the launch of W&amp;B Prompts.

Weights & Biases

BentoML offers an open-source platform called Bento Cloud, for the deployment and scaling of AI applications. It is a fully managed platform that handles the complexities of AI infrastructure, providing serverless autoscaling as required during the development and production stages. The platform helps to ship models to production with advanced deployment options including online and shadow A/B testing, while also providing visibility through model performance monitoring. The platform integrates with an organization’s existing data stack and enables users to continuously deploy and improve models in production. The company offers its platform through a combination of subscription and usage-based model.In addition, BentoML also provides the following open-source platforms: 1) Yatai, for model deployment on Kubernetes and 2) bentoctl, for model deployment on any cloud platform.Key customers and partnershipsAs of January 2024, BentoML reported that over 1,000 organizations, comprising more than 3,000 members, use its platform. Its notable customers include Koo, Open Layer, Line, and Naver.The company entered into a strategic partnership with TomTom, a developer of location technology, to help integrate with various models as well as in LLM deployments.Funding and financialsThe company raised <a href="https://sp-edge.com/updates/19684">USD 9 million in seed funding </a>in June 2023 led by DCM Ventures, with participation from Bow Capital. It aimed to channel the newly acquired funds to enhance its platform and offer developers a range of tools for building, deploying, and scaling AI applications efficiently.

BentoML

Iguazio provides a serverless platform based on its open-source Nuclio framework that helps users to develop, deploy, and manage real-time AI applications without requiring them to manually manage underlying infrastructures such as servers and storage. The platform creates real-time intelligence for applications located at the edge, public cloud, and on-premise data centers and reduces bandwidth constraints by consolidating data into a repository and making it available for applications as required. The platform can ingest and transform data from any source, which is then used to train, evaluate, deploy, and monitor models in production.The company leverages Big Data and ML software such as Apache Spark, TensorFlow, and Kubernetes to manage software containers that enable applications to run across different computing environments.Key customers and partnershipsIguazio serves customers in the financial services, telecommunications, smart mobility, manufacturing, retail, AdTech, gaming, healthcare, energy, and utilities sectors. Notable customers include Samsung, Microsoft, NVIDIA, AWS, Google, and Intel.Funding and financialsIn January 2020, the company raised USD 24 million in a funding round led by INCapital Ventures. The funds were utilized to accelerate its growth, expand its reach into new global markets, grow sales, and facilitate new sales channels that include companies such as Dell Technologies

Iguazio

Cogito Tech provides image and video annotation to generate computer vision training data sets for ML &amp; deep learning (DL). The video annotation solution leverages AI-powered tools to convert video into a sequence of images and generates training data sets for ML-based AI models, including self-driving cars and drones. The AI model understands and derives insights from visual data to detect, identify, classify, and track objects in an image or video. Cogito also provides virtual assistants and chatbots to help users in the process of training ML algorithms. Cogito Tech also provides high-quality, ethically sourced datasets that are compliant and reliable to train ML models.In addition, the company provides services to fine-tune LLMs and GenAI applications through reinforcement learning techniques as well as stress test models through red teaming.Key customers and partnershipsAs of December 2022, the company served more than 150 customers across 25 countries in the retail, medical, automotive, agriculture, robotics, smart cities, security, and manufacturing industries. Notable customers includes Verizon Media, The University of Sydney, National Geographic, Tumblr, and Vimeo.

Cogito Tech

Platforms and frameworks that help developers build and train ML models.

Platforms that deploy and host the trained and tested models in production and integrate them into applications through APIs.

Platforms that generate artificial data that mimics the characteristics of real data, which is then used to train ML models at scale.

Platforms that help monitor and manage ML models in training and deployment to track performance, conduct variance analysis, and optimize performance.

Makers of hardware such as CPUs, GPUs, and other application-specific hardware required to train and run ML workloads.

Integrated solutions that handle the end-to-end processes of developing, training, deploying, and monitoring ML models.

Data exchange providers and platforms that offer data labeling services via manual and/or software methods, which are used as input to train ML models.

Includes companies that provide infrastructure to build AI/ML applications

Provides tools to build, monitor, and deploy GenAI applications

Industry is focused on offering platforms for other businesses to build AI-/ML-powered apps

Dataloop

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