Amplify Partners invests in technical founders solving technical problems for the enterprise. They invest in early-stage companies pioneering novel applications in machine intelligence and computer science.

Amplify Partners

Redpoint has partnered with visionary founders to create new markets and redefine existing ones since 1999. The firm invests in startups across seed, early, and growth phases. In total, Redpoint manages $4 billion across multiple funds.

Redpoint

Creandum is a leading European early-stage venture capital firm backing some of Europe's most successful tech companies including Spotify, iZettle, Depop, Klarna, KRY, Epidemic Sound and Small Giant Games. Creandum has offices in Stockholm, Berlin, London and San Francisco.

Creandum

Lux Capital manages over $5 billion in assets focused on founding, seed, early-stage, and growth investments at the intersection of technology and the sciences. Lux takes an active role in helping entrepreneurs build successful businesses in high-growth sectors. Its investment team has built over 20 companies from scratch. Lux's investment strategy ensures portfolio companies are better connected, have a deeper insight, and command industry leadership faster than their competitors.

Lux Capital

Howard University is a nationally acclaimed, research-oriented institution, which was founded to provide stellar education to African-American students. Howard may be the most well-known Historically Black University (HBCU). Located in the culturally rich U Street/Shaw neighborhood of Washington, DC, Howard finds itself surrounded by politics and artists. Students come to Howard not merely for a rigorous education, but to have a well-rounded, culturally inspired, politically informed university experience. Howard offers bachelor’s degrees in a wide range of studies, has graduate programs, and offers doctorate programs in law, medicine and pharmaceutical studies. Students are able to take advantage of research studies to build their resumes, as well as study abroad programs to enlighten their global perspectives. Howard University is a competitive institution that boasts some of the best professors and professionals in their field. Faculty and students alike are proud to be members of such a prestigious and historically significant institution.

Howard University

Eastlink Capital is a Menlo-Park based venture capital firm with the current fund focusing on AI infra and applications.  Our investment thesis focuses on identifying exceptional founders with unique technologies that solve critical problems in huge markets with 10x better performance and lower cost. We differentiate ourselves by leveraging domain expertise in product/tech to identify winners before signals become clear. We are highly experienced in cross-border activities and have track records of helping our portfolio companies, including financing, recruiting and going to markets particularly in Asia.

Eastlink Capital

Gaingels is a venture investment syndicate in service of the LGBT+ community and its allies, investing in companies with LGBT+ founders and C-suite leaders at all stages of growth, as well as in more established companies resolved on building more inclusive teams, with a global portfolio of 130+ companies and $70M in deployed investment capital to date.  The Gaingels network also actively supports its portfolio in identifying and recruiting diverse talent to their C-suite and board leadership teams and fosters a vibrant global community of industry leaders, investors, operators, and entrepreneurs who share a common goal for positive social change through business and successful investments.

Gaingels

Quiet Capital is a technology investment firm.

Quiet Capital

Pre-seed/seed fund writing first checks into engineer-led enterprise startups focused on data technologies (AI/ML/deep learning/data infra)

Zero Prime Ventures

Essence Fund is engaged in financial management services.

Essence Fund

Definition is a venture capital investment firm that invests in category-defining software companies.

Definition

Factorial Capital

Modal Labs

Modal develops machine learning software to help run code in the cloud. The software enables users to run or deploy machine learning models, massively parallel compute jobs, task queues, web apps, and more. It also writes the code to launch hundreds of custom containers and runs scripts in the cloud faster than on the local machine.

Modal Labs provides a cloud-based AI model deployment platform that helps data teams and AI app developers run code in the cloud without the need to configure the required infrastructure. The company built its container system from scratch using the Rust programming language. Additionally, the platform offers storage, endpoints, and observability features while supporting parallel processing for faster data processing.

The toolkit to build machine learning applications at scale

Machine Learning Infrastructure

Modal Labs Selects Oracle as its Cloud Infrastructure Provider of Choice

Modal Labs provides a cloud-based AI model deployment platform that helps data teams and AI app developers run code in the cloud without the need to configure the required infrastructure. The company built its container system from scratch using the Rust programming language. Additionally, the platform offers storage, endpoints, and observability features while supporting parallel processing for faster data processing.The platform can be used for various use cases, including language models, image, video, 3D applications, and audio applications. The company provides access to the platform through a subscription-and-usage-based model, determined by the amount of compute processing used per month. Key customers and partnershipsIts notable customers include Ramp, Tesla, Hunt, and Carbonfact.Funding and financialsIn October 2023, Modal Labs raised USD 16 million in <a href="https://sp-edge.com/updates/22570">Series A</a> funding led by Redpoint Ventures. It was to use the funds for product development and recruitment.

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

Modal Labs, a cloud-based AI model deployment platform, has secured $16 million in a Series A funding round led by Redpoint Ventures, with participation from Amplify Partners, Lux Capital, and Definition Capital. This brings the company's total funding to $23 million. The funding will primarily be used to hire new employees, with plans to expand the team from 14 to 17 by the end of the year, as well as for product development. Modal Labs was launched in 2021 and provides a cloud-based infrastructure that enables data teams and AI app developers to run code in the cloud without the need for infrastructure configuration.

Modal Labs

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