Primitive Ventures is a global venture investment firm with a focus on blockchain and related technologies. At Primitive, we're proudly thesis-free, and instead spend all of their waking hours finding and supporting the people building truly valuable things.

Primitive Ventures

Yield Guild Games (YGG) is a decentralized autonomous organization (DAO) for investing in non fungible tokens (NFTs) used in virtual worlds and blockchain-based games. The organization’s mission is to create the biggest virtual world economy, optimizing its community-owned assets for maximum utility, and sharing its profits with its token holders.

Yield Guild Games

a technology venture capital firm supporting the next generation of founders advancing the development of web3

Artichoke Capital

Animoca Ventures seeks out, finances, and supports creators who will grow into the Internet's titans of the future. It is based on web3 and blockchain.

Animoca Ventures

Ravikant Capital

Variant is a web3-focused early-stage fund. According to the firm, the next iteration of the internet would turn consumers into owners. Variant was established in 2020 in New York, United States.

Variant

Sapien

Sapien, established in 2023, is a data labeling company dedicated to enhancing AI model training through scalable, high-quality data labeling services. By combining advanced technology, blockchain rewards, human feedback, and domain expertise, Sapien enables AI model development across multiple industries, including healthcare, finance, and education technology, among many others. The company's approach to data labeling through gamification and positive reinforcement ensures superior data quality output and high retention rates from labelers, and cost-effectiveness for customers. Sapien's commitment to quality, scalability, and customer focus, along with its mission to foster ethical and impactful AI advancements, sets it apart as a leading trusted partner for businesses developing high-performance AI models.

Sapien offers data labeling services for training AI models. The company has developed a novel approach to data labeling by gamifying the process with blockchain-based rewards. This incentivizes a global network of human labelers, referred to as "Sapiens," to provide accurate annotations, enabling Sapien to build high-quality AI training datasets.&nbsp;

The toolkit to build machine learning applications at scale

Machine Learning Infrastructure

Sapien raises $10.5 million in seed funding

Sapien offers data labeling services for training AI models. The company has developed a novel approach to data labeling by gamifying the process with blockchain-based rewards. This incentivizes a global network of human labelers, referred to as "Sapiens," to provide accurate annotations, enabling Sapien to build high-quality AI training datasets.&nbsp;Sapien's platform allows businesses to upload raw data, receive instant quotes, pre-pay, and have their data labeled by the network of taggers. The company serves customers across various industries, including healthcare, Web3, education, and developers of large language models (LLMs).Key customers and partnershipsIts notable customers include Alibaba, Baidu, carVertical, and University of Toronto.

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

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 AI firm Sapien has secured $10.5 million in seed funding. Contributors include Variant, Primitive Ventures, Animoca, Yield Guild Games, HF0, as well as angel investors such as Gabby Dizon and Kevin Jiang.
 The company plans to use these funds to enhance their matching tools and infrastructure for enterprise data pipelines and AI workers. Furthermore, they will develop AI-20, a standard for decentralized training data.
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Sapien

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