Alven Capital is an early-stage venture capital firm with over $500 million under management. Alven backs primarily ambitious French and French-related entrepreneurs in the digital technology space. Alven’s sectors of interest include notably AI, data management platforms, Saas, security solutions, as well as disruptive consumer models with a particular focus on marketplaces and web brands.

Alven

Lakestar is a venture capital firm investing in technology companies led by exceptional entrepreneurs. Early investments included Skype, Spotify, Facebook, and Airbnb. Since raising the first fund in 2013, Lakestar manages an aggregated volume of over EUR 1bn across three early-stage funds, and more recently a growth fund.  The company has expanded and broadened its portfolio and holds investments in the likes of Opendoor, Oscar, GetYourGuide, Glovo, Sender, Eigen, Five, Revolut, and Hometogo to name a few. Lakestar has a presence in Berlin, Zurich, and London. Lakestar helps companies to identify new markets and expand into them rapidly, with a focus on the US and Europe. The team advises and supports portfolio companies in business development, recruitment, technology, and marketing. The investments range from early-stage companies to those in their growth stage.

Lakestar

2.12 Angels' goal is to be the highest value-add to Founders per dollar invested. We invest pre-seed / seed companies in the Enterprise space. We do 2 zoom meetings. Founders get our decision the day after the second zoom. At noon.

2 | Twelve

Darkmode Ventures is an early stage venture fund with a “builders for builders” ethos.

Darkmode Ventures

K20 Fund offers flexible capital to various sectors through their diversified deployment strategy including debt, growth equity, PIPE.

K20 Fund

Irregular Expressions, IrregEx for short, is a group of seasoned software engineering and product leaders investing in and advising early stage technology startups. We’ve spent many cumulative decades bringing high-growth consumer and enterprise products to market, and are driven to help founders scale their own teams, products and businesses faster, by leveraging both our know-how and our network. Having co-founded, built and scaled hundreds of companies, primarily in the San Francisco, New York, and now remote-first ecosystems, we love working closely with the founders and teams we back, and think through thorny challenges on the product, engineering, and business fronts alike.

Irregular Expressions

Notation Capital is a pre-seed venture capital firm that work with technical founding teams. Notation Capital focus on early-stage technical teams, often pre-market or even pre-product, primarily in New York, and provide capital and support to help go-to-market and scale the company.

Notation Capital

Compound is a venture capital firm that invests in bleeding-edge technology built by outliers. They have partnered with elite operators that understand the intricacies of many different industries and various components of businesses, that help them navigate the complex systems in which each startup lives by removing roadblocks and compounding growth. Compound is based in New York City.

Compound

Alectio

The Alectio platform is the first full-stack, end-to-end, ML-driven self-serve DataPrepOps platform® enabling ML teams to prepare, curate, annotate, manage, version and visualize their training data in a few clicks, in near-real-time and quasi-automated manner. Alectio's proprietary technology is based on the fundamental belief that ML models can be trained with the same (sometimes better) performance with just a fraction of the data (which means lower labeling, storage and compute costs, and eventually the possibility of training on the edge). Data Scientists wrap their regular model and raw data with the Alectio's SDK and the Alectio curation engine guides the training process strategically so that the model gets trained on the most informative data; they'll never have to spend a minute on data preparation again! We're neither a labeling company nor an MLOps company: we're building a new category providing the entire workflow to prepare data during training which allows ML experts to build models and datasets simultaneously, reducing time to market, and a new training paradigm that will lead orgs to actual AI profitability. Alectio uncovers the smart data inside your big data, unlocking model performance and saving machine learning experts both time and money.

Alectio is a data curation and labeling platform. It uses active learning techniques to curate data that is optimal for training AI/ML models. This enables models to be trained with minimal data, saving businesses time and money.&nbsp;

The toolkit to build machine learning applications at scale

Machine Learning Infrastructure

Exclusive Talk With Dr. Jennifer Prendki, CEO of Alectio (An AI Startup Focused on DataPrepOps)

Alectio is a data curation and labeling platform. It uses active learning techniques to curate data that is optimal for training AI/ML models. This enables models to be trained with minimal data, saving businesses time and money.&nbsp;The platform also assists developers examine the subset of data that was most useful in training the model, allowing them to improve their data gathering and synthetic data generation processes. In addition, its smart labeling feature connects businesses with labeling partners and automatically incorporates modifications and requests for revisions in labeled data into the system to enhance the overall process.Key customers and partnershipsIn July 2022, the company partnered with InGen Dynamics to enable the latter to develop robot-based ML applications on the edge.&nbsp;Alectio’s key customers include Aecho, Veamly, Baylor University, Embark, and Voyage.Funding and financialsThe company’s most recent round of funding was in April 2021 for USD 1.5 million from an undisclosed round.&nbsp;

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

Alectio

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