GV supports innovative founders moving the world forward. We invest across the life sciences, consumer, enterprise, crypto, climate, and frontier technology sectors. With Alphabet as a sole limited partner, GV operates on long time horizons and deals in decades, not rounds. Our operating partners support startups at the earliest stages of company-building across design, equity, diversity & inclusion, talent, and engineering. We also help startups interface with Google, providing unique access to the world's best technology and talent. Launched as Google Ventures in 2009, GV has over $8 billion in assets under management and 400 active portfolio companies across North America and Europe. Notable investment outcomes include Uber, Nest, Slack, GitLab, Duo Security, Flatiron Health, Verve Therapeutics, and One Medical. GV is headquartered in the San Francisco Bay Area, with offices in Cambridge, New York, and London.

Google Ventures

Greylock Partners invests in entrepreneurs that focus on consumer and enterprise software companies. The firm invests in companies that define new markets, including Airbnb, AppDynamics, Apptio, Arista Networks (NYSE: ANET), Cloudera, Docker, Dropbox, Facebook (Nasdaq: FB), LinkedIn (NYSE: LNKD), Medium, Nextdoor, Palo Alto Networks (NYSE: PANW), Pandora (NYSE: P), Pure Storage, and Workday (NYSE: WDAY). It was founded in 1965 and headquartered in Menlo Park, California.

Greylock

Accel is an early and growth-stage venture capital firm that powers a global community of entrepreneurs. Accel backs entrepreneurs who have what it takes to build a business.  Accel’s vision for entrepreneurship and business enables it to identify and invest in the companies that will be responsible for the growth of next-generation industries. Accel-backed companies include Atlassian, Braintree, Cloudera, DJI, Dropbox, Dropcam, Etsy, Facebook, Flipkart, Lookout Security, MoPub, Qualtrics, Slack, Spotify, Supercell, Vox Media, and others.

Accel

In-Q-Tel identifies and partners with companies developing cutting-edge technologies to help deliver these solutions to the Central Intelligence Agency and the broader U.S. Intelligence Community (IC) to further their missions.

In-Q-Tel

SV Angel is a San Francisco-based venture fund. Their experience spans helping companies like Airbnb, Coinbase, Databricks, DoorDash, Faire, Flexport, GitHub, Notion, Pinterest, Snap, Square, and Stripe Scale. Over the last 30 years of investing, their core values of trust, loyalty, and integrity along with a founder-first approach have driven our strategy. They are a service organization, investing in founders who share these values. They support entrepreneurs in building lasting companies by assisting at key inflection points and leveraging networks to help them propel their businesses forward.

SV Angel

Lightspeed Venture Partners is a venture capital firm that engages in consumer, enterprise, technology, and cleantech markets. It focuses on seed, early-stage, later-stage, expansion-stage, start-ups, growth companies, and incubation, and specializes in debt financing for start-ups and growth companies. Lightspeed Venture Partners invests in various sectors that include enterprise, consumer, big data, bitcoin, enterprise technology, cleantech, mobile, internet, financial technology, cloud solutions, e-commerce, storage, media, networking, energy, and software, software-as-a-service, information technology, biotechnology, and social. It mainly invests in countries such as the United States, Europe, Israel, China, and India.

Lightspeed Venture Partners

BlackRock is an investment management company that provides its services to a diverse range of clients, including institutions, intermediaries, foundations, and individual investors. The firm operates as a global asset manager, overseeing and advising on a wide array of investment portfolios. In addition to its role as an investment manager, BlackRock is also known for its technological innovations and solutions that support various aspects of the financial industry. The company's multifaceted approach encompasses investment management, financial technology, and serving a broad spectrum of clients in the financial ecosystem.

BlackRock

Nepenthe Capital

Boston Trust Walden Company is an independent, employee-owned firm providing investment management services to institutional investors and private wealth clients.

Boston Trust Walden Company

Addition is a venture capital firm that invests in early and growth-stage tech companies. The firm was founded in 2020 by Lee Fixel with a mission to support visionary entrepreneurs on their journey to build impactful and enduring businesses.

Addition

Walden International is unique among US venture firms through its focus on cross-border investments that leverage global markets and talent to grow industry-leading companies. For more than 30 years, their integrated team has brought extensive added value to help companies through capital, relationships and expertise. They look to partner with the best of the best – entrepreneurs with a strong appreciation for the benefits of leveraging talent and markets independent of geography to gain unfair advantage. Their team brings both extensive venture expertise together with in-depth operating experience to help you grow your company. They invest in early and expansion stage companies across sectors such as Semiconductors, Clean Tech, Internet & Digital Media and Software.

Walden International

Stonebridge Ventures

Snorkel AI

Snorkel AI tackles a critical blocker to scaling AI: labeled training data. At Stanford AI lab, our founding team developed an automated way to build AI, replacing slow & costly hand-labeling. Today, Chubb, BNY Mellon, & other Fortune 500 companies accelerate AI development by 10-100x using Snorkel.

Snorkel AI provides a data-centric AI platform called Snorkel Flow for automated data labeling, along with integrated model training, analysis, and guided iteration within a single workflow. Developers can choose between different training data sets, model architectures from its library, or use the Python SDK to train custom models. The platform also has an AutoML feature that selects the best algorithm and hyper-parameters for the problem automatically and includes guided iteration tools to provide insights on how to improve both data and models to reach model performance targets.

The toolkit to build machine learning applications at scale

Machine Learning Infrastructure

<div>Snorkel AI offers a suite of solutions for the development of foundational model data and AI applications consisting of three main products: Snorkel Flow, Snorkel GenFlow, and Snorkel Foundry.</div>

Empowering Tomorrow's Innovations with Generative AI Infrastructure

Generative AI Infrastructure

Snorkel AI Signs Agreement with BNY to Accelerate the Development of Predictive AI Models

Google Cloud

To make the Snorkel Flow platform available on Google Cloud Marketplace and to integrate it with Google's Vertex Generative AI Studio to allow Google Cloud customers develop and fine-tune ML models and generative AI applications using its own proprietary data.

Platforms and frameworks that help developers build and train ML models.

Azure

To complement Azure AI services and the Azure Machine Learning platform with Snorkel AI's data labeling capability to generate high-quality data training sets, and automatically train and deploy custom ML models into production.

Platforms that deploy and host the trained and tested models in production and integrate them into applications through APIs.

Snorkel AI provides a data-centric AI platform called Snorkel Flow for automated data labeling, along with integrated model training, analysis, and guided iteration within a single workflow. Developers can choose between different training data sets, model architectures from its library, or use the Python SDK to train custom models. The platform also has an AutoML feature that selects the best algorithm and hyper-parameters for the problem automatically and includes guided iteration tools to provide insights on how to improve both data and models to reach model performance targets.Snorkel AI also supports collaboration between developers and domain experts as well as integration with foundation models (FM) to build tailored ML models. Companies can use their proprietary data to build their custom FM or large language models (LLMs), or improve the accuracy of commercially available or open-source models for domain-specific generative AI and predictive AI applications. Moreover, Snorkel AI has integrations with a variety of ML infrastructure platforms that allows users to choose between a private cloud and a public cloud deployment architecture.Key customers and partnershipsIts key customers include five of the top 10 US banks, a number of government agencies, and Fortune 500 companies such as Apple, Intel, Chubb, and Google.The company <a href="https://sp-edge.com/updates/17515">partnered with Microsoft </a>to integrate Snorkel Flow with Azure AI services to aid data science and ML teams in developing AI/ML models tailored to their proprietary data. It also <a href="https://sp-edge.com/updates/20931">collaborated with Google Cloud </a>to make available the Snorkel Flow platform on Google Cloud Marketplace and to integrate it with Google's Vertex Generative AI Studio to develop and fine-tune ML models.Funding and financialsIn August 2021, Snorkel AI raised USD 85 million in Series C funding at a valuation of USD 1 billion. The round was co-led by Addition and funds and accounts managed by BlackRock. It planned to use the funds to scale its engineering and go-to-market teams to improve product development and adoption of 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 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

<div>
 
 Snorkel AI offers a suite of solutions for the development of foundational model data and AI applications consisting of three main products: Snorkel Flow, Snorkel GenFlow, and Snorkel Foundry.
 
 
 Snorkel Flow enables the rapid construction, management, and deployment of predictive AI applications, such as classification and information extraction, utilizing techniques like programmatic labeling, fine-tuning, and distillation. This empowers enterprises to achieve high accuracy in production-grade applications, including tasks like financial document analysis, clinical trial analytics, and KYC compliance.&nbsp;
 
 
 Snorkel GenFlow facilitates the swift creation, management, and deployment of GenAI applications, such as summarization, question-answering, and chatbots. It achieves this by programmatically curating, scoring, filtering, and sampling instructions and responses for instruction tuning, incorporating methods like reinforcement learning with human feedback (RLHF). Enterprises can enhance task-specific performance and reliability by leveraging their proprietary data with this tool.
 
 
 Lastly, Snorkel Foundry provides a solution for creating custom foundational models or LLMs by programmatically processing and enhancing proprietary data. This enables enterprises to leverage their unique data for specialized domain-specific models that serve as the basis for all internal AI applications.
 
 
 The company claims its solutions help users accelerate AI development by 10x&ndash;100x and save up to 90% of labeling costs.
 
 
 Key customers and partnerships
 
 
 Snorkel AI&rsquo;s customer base includes Apple, five of the top ten US banks, Memorial Sloan Kettering, BNY Mellon, Wayfair, US government agencies, and Pixability.
 
 
 Snorkel AI has a notable 
 <a href="https://sp-edge.com/updates/17515">
 partnership with Microsoft
 </a>
 to empower Azure AI customers to customize and refine machine-learning models with their proprietary data. It also collaborated with
 <a href="https://sp-edge.com/updates/20931">
 Google Cloud
 </a>
 to make the Snorkel Flow platform available on the Google Cloud Marketplace and integrate with Google's Vertex Generative AI Studio.
 
 
 Funding and financials
 
 
 In January
 <a href="https://sp-edge.com/updates/25880">
 2024
 </a>
 , Snorkel AI received an undisclosed amount of strategic investment from QBE Ventures to develop AI solutions for the insurance industry. In August 2021, the firm raised USD 85 million in a Series C funding round led by BlackRock and Addition. The company planned to utilize the funding for business development and workforce expansion.&nbsp;
 
 
 
</div>

<div>
 
 Founded in Israel, NeuReality specializes in providing hardware infrastructure to streamline computation processes to accelerate the development of AI applications. Its technology assists AI inferencing deployment by offering a comprehensive system solution that seamlessly supports a vast array of deep learning models.
 
 
 NeuRealitys&rsquo; infrastructure includes an architecture called the Network Addressable Processing Unit (NAPU) to maximize the capabilities of Deep Learning Accelerators (DLAs). This design facilitates inference through purpose-built NAPUs that are specifically crafted for AI inference tasks, enhancing performance and efficiency.
 
 
 The NR1 AI Inference Solution by NeuReality is a comprehensive system comprising architecture, hardware, and software platforms. Launched in November 2023, it intends to simplify the installation, utilization, and management of AI, making it accessible and manageable for users.
 
 
 The hardware offerings of the solution include,
 
 
 1. 
 NR1 Network Addressable Processing Unit
 : A network addressable inference Server-on-a-Chip with an embedded Neural Network Engine, which is a workflow-optimized hardware device with specialized processing units, native network capabilities, and virtualization capabilities
 
 
 2. 
 NR1-M&trade; AI Inference Module
 : A full-height, double-wide PCIe card containing one NR1 Network Addressable Processing Unit (NAPU) system-on-chip and a network addressable Inference Server that can connect to an external Deep Learning Accelerator (DLA)
 
 
 3. 
 NR1-S AI Inference Appliance
 : An optimized design for an inference server that contains NR1-M modules with the NR1 NAPU, which enables disaggregated AI service in a scalable and efficient architecture
 
 
 The software component of the solution is designed to be compatible with any trained model from any development environment. It includes tools that handle the entire AI pipeline and enable seamless connection of AI workflows to any environment.
 
 
 NeuReality differs from traditional AI chip connectivity in replacing CPU-centric support with an AI-centric platform. This allows components to communicate directly with AI accelerators, eliminating the need for commands to pass through a central processing unit. Additionally, the technology enables AI accelerators to connect with each other, enhancing efficiency and performance in AI applications. It also claims its AI-centric approach reduces complexity, cost, and power usage. The firm claims it can reduce inference costs by 90%.
 
 
 Key customers and partnerships
 
 
 In November 2021, NeuReality teamed up with IBM to develop advanced AI inference technology by enhancing its NR1 chip and system for use in IBM's Hybrid Cloud.
 
 
 In September 2021, the company partnered with Xilinx to develop AI-centric platforms that improve real-world AI applications. This collaboration was intended to focus on NeuReality's AI-centric inference platform NR1-P and address existing issues with AI deployment including cost and complexity.
 
 
 Funding and financials
 
 
 In 
 <a href="https://sp-edge.com/updates/27745">
 March 2024
 </a>
 , NeuReality secured USD 20 million in funding led by The European Innovation Council (EIC) Fund. The funds were intended to accelerate the deployment of NeuReality&rsquo;s NR1AI Inference Solution.
 
 
 In December 2022, it secured USD 35 million in a Series A funding round led by Samsung Ventures, with Cardumen Capital, Varana Capital, OurCrowd, XT Hi-Tech, and others as participants. The funding was used to launch its flagship AI inferencing solution.
 
</div>

NeuReality

<div>
 
 Accubits is an AI and BLOCKCHAIN focused development and solutions company based in Washington DC with its development offices in India and Dubai. Pioneering as a custom Blockchain solutions provider delivering solutions ever since 2012, Accubits is one of the oldest and experienced Blockchain dev house in the market and is featured as one among the top 13 Blockchain companies in India by INC42. We are a big family of engineers, innovators, inventors and many others continually working to help our customers in leveraging their business and adding value to their lives. Over the past 6 years, We have delivered more than 600 projects, for over 200 clients worldwide. Several of Fortune 500 companies in sectors from Retail to Health are being powered by our solutions to streamline and leverage their growth.Our portfolio for AI solutions includes intelligent conversational tools, RPAs, CRMs, SIPs, real-time video and image analytics systems, state of the art ALPR systems and many more being used enterprises, startups across North America, Canada, Middle East, Hong Kong, Singapore, Indonesia, India &amp; Sweden. Our portfolio of Blockchain development includes custom DApps and smart contracts, crypto token and exchange development, integrated blockchain services and ICO platforms.
 
</div>

Accubits

<div>
 
 LeewayHertz is a leading software development company delivering tailor-made digital solutions to businesses worldwide. Our team of 250+ full-stack developers, designers and innovators has designed and developed 100+ digital solutions across industry verticals. As a close-knit team of AI and web3 experts, designers and full-stack developers, we undertake collaborative research and development to create next-gen applications and solutions perfectly suited to the evolving tech space. As a technology pioneer with deep knowledge and expertise in AI, blockchain and other advanced technologies like IoT, LeewayHertz believes in helping companies overcome their most complex tech challenges and drive business growth. Our motto, &lsquo;You Dream It: We Build It,&rsquo; reflects our business philosophy. From putting flesh on your idea to delivering the expected end product, we do whatever it takes to make your project successful. Having worked with 30+ top fortune 500 companies and created various on-demand solutions, we boast an impressive work portfolio demonstrating our expertise.
 
</div>

LeewayHertz

<div>
 
 AI21 Labs is a creator of generative artificial intelligence and massive language models, as well as tools for creating artificial intelligence systems with extraordinary understanding and generation of natural language. The company's tool captures real intelligence and rewrites writing to say exactly what is meant; it transforms the way people read and write, empowering them in the process; it is an artificial intelligence-based writing companion that understands context and meaning; and it helps people read more efficiently by providing summaries, allowing customers to understand, analyze, and visualize abstract knowledge structures.
 
</div>

AI21 Labs

<div>
 
 Databricks, a data and AI company established by the original developers behind prominent Big Data solutions such as Delta Lake, Apache Spark, and MLflow, and provides organizations with AI and data analytics tools for efficient management of their data.&nbsp;
 
 
 Databricks' primary product is the Databricks Lakehouse platform, a unified data intelligence platform that merges a data warehouse and data lake to provide developers with efficient access to data and enables enterprise customers to create their AI models&mdash;similar to a ChatGPT-style AI system&mdash;using only their internal data.&nbsp;
 
 
 Databricks Unity Catalog, part of the Databricks Lakehouse Platform, provides unified governance for structured and unstructured data, machine-learning models, notebooks, dashboards, and files across various environments, offering automated monitoring, proactive alerts, and seamless data sharing through Delta Sharing integration. Furthermore, Databricks offers an open architecture that streamlines the AI development process, allowing the integration of various LLMs such as Llama 2, Azure OpenAI, and Anthropic, enabling customization with enterprise data for tailored model creation.
 
 
 Notably, Lakehouse leverages NVIDIA technology for accelerated data processing and AI model generation. Databricks also offers industry-specific solutions like Databricks Lakehouse for Healthcare, Financial Services, Retail, and Manufacturing.
 
 
 Databricks has expanded its offerings through multiple acquisitions, including MosaicML (
 <a href="https://sp-edge.com/updates/19683">
 July 2023
 </a>
 ), Arcion (
 <a href="https://sp-edge.com/updates/23041">
 October 2023
 </a>
 ), Okera (
 <a href="https://sp-edge.com/updates/18197">
 May 2023
 </a>
 ), and Datajoy (October 2022).&nbsp;
 
 
 
 
 Key customers and partnerships
 
 
 As of July 2023, Databricks served a global customer base of approximately 10,000, including notable customers such as Comcast, DuPont, Honeywell, Rolls-Royce, Shell, and Tata Steel.
 
 
 Notable partnerships include collaboration with NVIDIA to incorporate NVIDIA TensorRT-LLM into its inference service and a partnership with Hevo-Data to automate data integration into the lakehouse for mutual customers (October 2022).
 
 
 Databricks also provides an LLM Mesh partner program; it has partnered with firms such as 
 <a href="https://sp-edge.com/updates/24218">
 Dataiku
 </a>
 where an emphasis is placed on comprehensive data access, enabling tight integration of GenAI applications with enterprise data.&nbsp;
 
 
 
 
 
 Funding and financials
 
 
 As of 
 <a href="https://sp-edge.com/updates/23839">
 September 2023
 </a>
 , Databricks completed a Series I funding round which saw participation from strategic partners like NVIDIA and Capital One Ventures and raised more than USD 500 million, with the company valued at USD 43 billion. Databricks planned to use the funding to develop its platform further and expand its reach in the AI and data analytics market​​​​​​.
 
</div>

Databricks

Integrated solutions that handle various processes such as model training, fine-tuning, model deployment, monitoring, and maintenance in working with and deploying LLMs

Platforms that provide hardware such as high-performance CPUs, GPUs, or TPUs, including cloud-based solutions that are commonly used to train and run GenAI models efficiently

Platforms that assist with fine-tuning pre-trained GenAI models or custom models tailored to specific use cases. Includes services that train models from scratch or use existing models

Platforms that store and retrieve training data in vector databases for access during the model training phase

Services to deploy GenAI models (on-premises or cloud-based) into production environments and integration tools to support existing systems and workflows

Ongoing monitoring of GenAI models to ensure performance. Includes regular model retraining, performance optimization, and troubleshooting

Platforms that assist in designing and refining prompts or instructions to GenAI models to get the desired responses or outcomes

Platforms that develop and implement strategies, policies, and practices to ensure the responsible, secure, ethical, and safe use of Generative AI technologies within an organization.

All services offered by these companies provide support to AI/ML

NLP is a key component of generative AI which is the core focus of this hub.

All companies within this space are offering infrastructure for generative AI

Generative AI infrastructure hub covers companies that deploy and run these foundation models.

PROMINENT_CATEGORY

<div>
 
 AI development platform Snorkel AI has launched an upgrade for Snorkel Flow. This new update aims to simplify the process of coupling enterprise data with machine learning models for businesses.
 The latest improvement optimizes the integration of enterprise data. It provides connectivity to Vertex AI, Databricks Unity Catalog, and Microsoft Azure Machine Learning. These platforms allow for simplified data labeling, even facilitating coding-based labeling of multimodal data.
 Furthermore, the platform can be seamlessly linked with Language Learning Models (LLMs) such as Google’s Gemini 3 and Meta’s Llama 3. Such an integration offers businesses the flexibility to choose appropriate LLMs.
 Snorkel AI has also introduced a feature for role-based access controls (RBAC) specifically for Snorkel Flow account administrators. These controls allow administrators to manage the accessibility of enterprise data.
 
</div>

Snorkel AI

About EDGE

Contact Us

Resources

Area of Focus

Technology Research Made Effortless