Amadeus Capital is a global technology investor that invests in technology companies at all stages, from seed to venture buyout; they also buy stakes from other investors or founders, to ensure that companies and entrepreneurs have the runway they need to succeed. They invest in a broad variety of sectors including enterprise and infrastructure software, consumer and business services, medical technology and healthcare IT, and cleantech and resource efficiency. It has the imagination to see where new businesses can be created and the technical insight, operational experience and global network to help entrepreneurs make their vision a reality. The Company was founded in 1997 and since has backed more than 130 companies and raised over $1bn for investment.

Amadeus Capital Partners

Partech is a global tech investment firm headquartered in Paris, with offices in Berlin, Dakar, Dubai, Nairobi, and San Francisco. We are a team made up of independent thinkers. We are unconstrained by hype, trend or fixed ways of working. We believe in the power of alliance in action, working together and side-by-side with the founders we back, in the shared pursuit of success. We bring together capital, operational experience and strategic support for the entrepreneurs we back from seed through to growth stage. Born in San Francisco 40 years ago, today we manage €2.5bn AUM and our current portfolio of 220 companies in 40 countries, across 4 continents.

Partech

Air Street Capital invests in AI-first companies.

Air Street Capital

Miele Venture is a venture arm of Miele Group.

Miele Venture

Temasek Holdings is a lender provider. The company offers debt financing and focuses on transforming economies, increasing middle-income populations, developing comparative advantages, and emerging champions. Financial services, transportation, industrial, consumer, real estate, telecommunications, media, technology, and life sciences are among the industries served by the firm.

Temasek Holdings

Radical Ventures is an early-stage venture capital firm investing in entrepreneurs applying deep technology to transform massive industries. With a primary focus on artificial intelligence, Radical Ventures partners with entrepreneurs with global ambition to build enduring companies. The firm is based in Toronto, Canada, with offices in London (UK), and Palo Alto (US)

Radical Ventures

V7 is a powerful AI training data platform that enables you to annotate images, videos, documents, and medical imaging files. It is the quickest way to obtain high-quality annotated data for training your computer vision models. You can utilize auto-labeling features to accelerate your annotation projects, manage your MLOps workflows, or hire professional annotators for assistance.  With advanced auto-labeling, quality assurance (QA), and team collaboration tools, V7 will help you reduce your data annotation time by 10x and assist you in developing more accurate AI solutions. Annotate any dataset with ease and seamlessly integrate V7 into your training data management and model development pipeline.  You can seamlessly integrate V7 with your existing tech stack and import/export annotations with ease. Additionally, V7 empowers you to have complete control over your models, tasks, and datasets through the open API, Darwin-py SDK, and CLI.

V7 is a company that provides AI-powered data labeling and workflow automation solutions. The company offers a platform called Darwin that automates the process of labeling large datasets for computer vision applications. The company's technology aims to reduce the time-consuming task of manually tagging and labeling data, which is crucial for training AI algorithms. V7's platform utilizes a system called AutoAnnotate, a general-purpose AI model for computer vision that can detect object boundaries in images or videos and label them rapidly.

Training an AI system is time consuming, but this startup says it has a solution

AI data labelling startup V7 raises £27m

V7 Labs expands from data labeling into workplace automation

V7 - Build Trustworthy AI at Scale

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London GenAI company V7 tops Sifted’s B2B SaaS Rising 100 ranking

V7 is a company that provides AI-powered data labeling and workflow automation solutions. Founded in 2018, V7 offers a platform called Darwin that automates the process of labeling large datasets for computer vision applications. The company's technology aims to reduce the time-consuming task of manually tagging and labeling data, which is crucial for training AI algorithms. V7's platform utilizes a system called AutoAnnotate, a general-purpose AI model for computer vision that can detect object boundaries in images or videos and label them rapidly. Internal measurements indicate that AutoAnnotate can label a high-quality piece of training data in about 2.5 seconds, compared to up to two minutes for a human.
In April 2024, V7 expanded its offerings with the launch of V7 Go, a workplace automation platform that uses AI to extract information from various file types and automate business processes. V7 Go allows users to input files and describe tasks in plain English, after which the software creates a searchable tabular index of the information and generates steps to complete the task. The platform combines computer vision AI for identifying objects in images with language-based models for understanding text, with large language models coordinating these processes to develop task completion steps.
Key customers and partnerships
V7's clients include over 300 AI companies and academic institutions such as Stanford, MIT, and Harvard. The company's technology has been used in various industries, including agriculture, where FruitCast, a startup spun off from the University of Lincoln's food-tech institute, uses V7's platform to train AI-powered robots for strawberry ripeness assessment. As of April 2024, V7 Go was being used by several customers, including an asset management firm for extracting data from confidential memos, a biotech company for mining information from scientific research papers, and a freight company for automating the processing of shipping documents. Tuza, a UK company that helps businesses adopt payment solutions, reported that V7 Go saved them weeks of engineering time by allowing commercial teams to build workflow automations without requiring machine learning experts.

V7 is a company that provides AI-powered data labeling and workflow automation solutions. The company offers a platform called Darwin that automates the process of labeling large datasets for computer vision applications. The company's technology aims to reduce the time-consuming task of manually tagging and labeling data, which is crucial for training AI algorithms. V7's platform utilizes a system called AutoAnnotate, a general-purpose AI model for computer vision that can detect object boundaries in images or videos and label them rapidly.The company also offers V7 Go, a workplace automation platform that uses AI to extract information from various file types and automate business processes. V7 Go allows users to input files and describe tasks in plain English, after which the software creates a searchable tabular index of the information and generates steps to complete the task. The platform combines computer vision AI for identifying objects in images with language-based models for understanding text, with large language models coordinating these processes to develop task completion steps.Key customers and partnershipsIt serves customers across healthcare, finance, legal, insurance, logistics, biotechnology, manufacturing, and real estate such as Alaris, CenterLine, Sony, Roche, Boston Scientific, and Mercedes-Benz.

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

V7

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