Bloomberg Beta is an early-stage venture capital firm with $375M under management, capitalized solely by Bloomberg. The fund exists to expand Bloomberg’s horizons by investing in companies built by extraordinary founders that make business work better, with a focus on machine intelligence.

Bloomberg Beta

SignalFire is a complete redesign of the modern venture firm based on six years of careful study, development, and iteration on how to fuel today's entrepreneur. Their distributed network approach gives access to some entrepreneurs, product, and engineering leaders in virtually every key discipline and industry, provided by a centralized team of investors and engineers trained at General Catalyst, Bessemer, KPCB, Google, and Yahoo. They have developed a centralized infrastructure to help with recruiting, business development, customer acquisition as well as educational and community events. They invest in leaders with an uncommon passion and perspective for leveraging data and technology solutions to upend substantial markets.

SignalFire

SAV(Scale Asia Ventures) is a Palo Alto-based early-stage venture fund focused on Enterprise Software, Data-driven Life Sciences, and AI-powered Vertical Industries. Fund backers include institutional funds, prominent family offices, and publicly-traded conglomerates in the U.S as well as S. Korea, Japan, and Singapore. SAV is committed to providing its portfolios with strong U.S. and Asia market expertise and a unique global network of strategic corporate partners.

SAV (Scale Asia Ventures)

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

Palumni VC invests in the next generation of Palantir alumni founded and led companies.

Palumni VC

A founder-centric early-stage fund investing in enterprise data opportunities.

Octave

Liquid2 Ventures provides technology startups with seed-stage investments and is based in San Francisco, California. The firm was founded in 2015 by Joe Montana, Mike Miller, and Michael Ma.

Liquid 2 Ventures

Early stage venture capital investment firm.

lobby capital

In physics, 11.2 km/s is the escape velocity from Earth's gravity. They focus on emerging technologies such as AI, cybersecurity, robotics, quantum, new space, computational therapeutics, synthetic biology.  ​They believe great people are leading indicators of a company's success. 11.2 Capital’s technical background, operational experience, and a strong network of amazing advisors and international partners particularly in Asia deliver a unique set of resources to entrepreneurs. While they are happy to help companies across the full range of early-stage company questions, areas where they concentrate include technical recruiting, partnerships (OEM and distribution partnerships for smart hardware companies, data partnerships for data-driven healthcare companies), customer introductions (CISO introductions for security companies, provider introductions for healthcare companies), and follow-on financings.

11.2 Capital

Kolena

Kolena is an ML testing platform that allows ML teams to rigorously test their model behavior. With Kolena, ML teams can identify and track failure modes to help engineering, sales, and customers better understand model performance and identify gaps. Kolena is the creator of a machine learning testing and analytics platform used to ensure the quality of machine learning and related technologies. Clients can use the company's platform to streamline and rectify machine learning and analytics projects by providing a testing infrastructure for machine learning software models and updates.

Kolena offers an AI/ML testing, debugging, and validation platform. The platform organizes training data, allowing developers to create specific test cases for their AI model and visualize performances. It assists in identifying AI biases and ensuring the trustworthiness of AI models.

The toolkit to build machine learning applications at scale

Machine Learning Infrastructure

Kolena Launches AI / ML Model Quality Platform to Enable Rapid, Accurate Testing and Validation of AI Systems

Kolena offers an AI/ML testing, debugging, and validation platform. The platform organizes training data, allowing developers to create specific test cases for their AI model and visualize performances. It assists in identifying AI biases and ensuring the trustworthiness of AI models.Key customers and partnershipsThe company’s customers include several Fortune 500 companies as well as government organizations.Funding and financialsIn September 2023, Kolena raised USD 15 million in a <a href="https://sp-edge.com/updates/22178">Series A</a> funding round led by Lobby Capital. It aimed to use the fresh funds for R&amp;D with the aim of enhancing its platform.

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

PROMINENT_CATEGORY

<div>
 
 Kolena, a platform for AI testing and validation, revealed its platform focused on the quality of AI/ML models. The company's goal is to improve AI adoption through better testing and assurance of the quality of AI/ML models.
 The AI/ML model quality platform delivers a testing procedure to highlight the strengths and weaknesses of AI/ML models. The platform considers all aspects of AI/ML methods and brings in pre-training data quality functions. Important features include testing models before deployment, automated testing workflows, and getting insights into the performance of models. There are plans to introduce monitoring of models after deployment.
 The platform was introduced after a 24-month closed beta involving Fortune 500 companies, AI startups, government entities, and AI standardization institutes in Europe. During this beta period, Kolena took the opportunity to perfect and add more capabilities to its platform through cooperation with the customers who had early access.
 
</div>

Kolena

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