Zetta Venture Partners is the first focused fund committed to delivering exceptional returns from the high-growth analytics market.  The firm, founded by industry veteran Mark Gorenberg, launched in 2013.  With offices in San Francisco and Utah, and a worldwide network of partners, entrepreneurs and investors, Zetta Venture Partners is at the forefront of the next huge and long-lasting investment opportunity.  Focused funds deliver exceptional returns. In fact, over the past 10 years, focused funds have outperformed all funds by 72 basis points, according to the National Venture Capital Association. As an analytics-only fund, Zetta delivers the expertise, network and portfolio to create ongoing, exceptional deal flow.

Zetta Venture Partners

IQT identifies and partners with companies developing advanced technologies. It evaluates emerging technologies and collaborates with entities that show potential for practical applications. IQT serves industries such as defense, cybersecurity, and telecommunications.

Slow Ventures is a venture capital firm that focuses on investing in companies central to the technology industry as well as those operating at the intersection of science, society, and culture. The firm seeks to support innovative ideas and solutions that shape the future across various sectors.

Slow Ventures

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

Sequoia is a venture capital focused on energy, financial, enterprise, healthcare, internet, and mobile startups. The firm helps a small number of daring founders build legendary companies. It spurs them to push the boundaries of what’s possible. The firm seeks to invest in all sectors with a focus on energy, financials and financial services, healthcare and healthcare services, Internet, mobile, outsourcing, and technology.

Sequoia Capital

Coatue is a privately owned hedge fund sponsor. The firm invests in the public equity markets globally focusing on investments in technology, media, and telecommunications in addition to other sectors. It employs a long or short strategy to make its investments.

Coatue

Founded in 1988, Highland Capital Partners is a global venture capital firm focused on putting the entrepreneur first.  With offices in Silicon Valley, Boston and Shanghai, Highland has raised over $3 billion in committed capital and invested in more than 225 companies, resulting in category-defining businesses across consumer and enterprise technology.  Investments include 2U, Ask Jeeves, Bromium, Gigamon, Leap Motion, LevelUp, Lycos, MapQuest, Nebula, QD Vision, Qihoo 360, Quattro Wireless, RentJuice, Rent the Runway, Starent Networks, Sybase, Violin Memory, VistaPrint and WePay.  Highland also serves as a mentor for future entrepreneurs through Summer@Highland, a program that provides students and university-affiliated startups with the environment and resources to take their initiative to the next level.

Highland Capital Partners

Highland Europe invests in rapidly growing European internet, mobile, and software companies that address large market opportunities and have over €10 million in annualized revenues. They can provide acquisition finance or lead secondary transactions as well as making primary investments. Their capital enables management teams to accelerate growth and build a lasting, valuable business. Highland Europe was launched in 2012 and closely collaborates with Highland Capital Partners, an independent global venture capital firm with a twenty-seven year investment experience and offices in Boston and Palo Alto.

Highland Europe

Dell Technologies Capital is the investment arm for Dell Technologies.  We’ve invested in over 100 companies that push the envelope on digital technology for enterprises and consumers.  We are a team of world-class investors who help our companies succeed.  We focus on early-stage investments with passionate founders. Our companies gain unique access to the go-to-market capabilities of Dell Technologies. For more information visit www.delltechcapital.com

Dell Technologies Capital

Great Hill Partners is a private equity firm with $2.7 billion under management. Great Hill Partners seeks to partner with middle-market companies operating in high growth sectors in the media/communications, Internet, business services, consumer services, financial technology, healthcare technology, software, and transaction processing sectors.

Great Hill Partners

NVIDIA is a computing platform company, innovating at the intersection of graphics, HPC, and AI. The company specializes in the manufacture of graphics-processor technologies for workstations, desktop computers, and mobile devices. The company is a major supplier of integrated circuits used for personal computer motherboard chipsets, graphics processing units (GPUs), and game consoles.

NVIDIA

Empede Capital is a Venture Capital investor with a clear focus on innovation & industry disruption

Empede Capital

Snowflake Ventures invests in growth-stage companies that demonstrate a commitment to mobilizing data, providing value to its customers, and expanding opportunities for the data cloud.

Snowflake Ventures

Domino Data Lab

Domino Data Lab empowers data science teams with the leading, open data science platform that enables enterprises to manage and scale data science with discipline and maturity. Model-driven companies including Allstate, Dell Technologies, and Bayer use Domino as a data science system of record to accelerate breakthrough research, increase collaboration, and rapidly deliver high-impact models.

Domino Data Lab provides an enterprise MLOps platform that allows users to collaboratively build, train, deploy, and manage models. The platform delivers automated experiment tracking through its Reproducibility Engine along with delivery, deployment, and monitoring features on any infrastructure through self-service web forms, scheduled reports, and APIs. The platform also offers an integrated model factory that allows model development, deployment, and monitoring with a system of record that documents reusable code, artifacts, and learnings from previous experiments in a central repository.

The toolkit to build machine learning applications at scale

Machine Learning Infrastructure

Domino Data Lab provides an Enterprise MLOps platform that enables organizations to develop, deploy and manage machine learning models at scale. The platform acts as a system of record for data science, offering tools and infrastructure for the complete AI lifecycle - from data access and model development to deployment and monitoring. The Domino Enterprise AI Platform enables data scientists to use their preferred tools, languages, and infrastructure while providing enterprise-level governance and collaboration capabilities. As of March 2023, the platform includes support for open-source ML tools like Ray 2.0, MLflow, and Feast's feature store, enabling advanced AI applications including generative AI development. The company also offers Domino Code Assist (DCA), launched in February 2023, which helps organizations democratize data science by enabling business analysts to generate and work with Python and R code. The platform reduces the time to begin building and launching data models from weeks to minutes. A case study showed that Lockheed Martin achieved USD 20 million in annual cost savings and a tenfold increase in productivity after implementing Domino's platform. In June 2024, Gartner named Domino Data Lab a Visionary in its Magic Quadrant for Data Science and Machine Learning Platforms, recognizing the company's strong market position and continued innovation.

Data Infrastructure & Analytics

Domino Data Lab Transforms AI Governance from Innovation Tax into Value Driver

Domino Data Lab provides an Enterprise MLOps platform that enables organizations to develop, deploy and manage machine learning models at scale. The platform acts as a system of record for data science, offering tools and infrastructure for the complete AI lifecycle - from data access and model development to deployment and monitoring. The Domino Enterprise AI Platform enables data scientists to use their preferred tools, languages, and infrastructure while providing enterprise-level governance and collaboration capabilities. As of March 2023, the platform includes support for open-source ML tools like Ray 2.0, MLflow, and Feast's feature store, enabling advanced AI applications including generative AI development. The company also offers Domino Code Assist (DCA), launched in February 2023, which helps organizations democratize data science by enabling business analysts to generate and work with Python and R code. The platform reduces the time to begin building and launching data models from weeks to minutes. A case study showed that Lockheed Martin achieved USD 20 million in annual cost savings and a tenfold increase in productivity after implementing Domino's platform. In June 2024, Gartner named Domino Data Lab a Visionary in its Magic Quadrant for Data Science and Machine Learning Platforms, recognizing the company's strong market position and continued innovation.
Key customers and partnerships
Over 20% of Fortune 100 companies use Domino's platform across industries including life sciences, financial services, public sector, and insurance. The company maintains partnerships with technology providers like NVIDIA for accelerated computing capabilities and Snowflake for data cloud integration. Lockheed Martin uses the platform across 300+ data scientists for building ML models in aeronautics design and factory operations. Direct Line Group leverages the platform's Ray integration capabilities for distributed training jobs. Evidation utilizes the platform to work with person-generated health data.

Domino Data Lab Announces Domino Code Assist to Help Close Data Science Talent Gap and Democratize Advanced Analytics

Domino Data Lab harnesses data science in AI platform

Domino Data Lab Named a Visionary in the 2024 Gartner Magic Quadrant for Data Science and Machine Learning Platforms

Snowflake invests in Domino Data Lab to facilitate deeper integrations

Domino Data Lab Makes Cutting-Edge AI Accessible to All Enterprises

Lockheed Martin accelerates data science with Domino Data Lab

Domino Data Lab Named a Visionary in the 2024 Gartner Magic Quadrant for Data Science and ML Platforms

Domino Data Lab provides an enterprise MLOps platform that allows users to collaboratively build, train, deploy, and manage models. The platform delivers automated experiment tracking through its Reproducibility Engine along with delivery, deployment, and monitoring features on any infrastructure through self-service web forms, scheduled reports, and APIs. The platform also offers an integrated model factory that allows model development, deployment, and monitoring with a system of record that documents reusable code, artifacts, and learnings from previous experiments in a central repository.The platform’s standard license includes unlimited consumer licenses, user and admin training sessions, technical support and advice, and new platform releases.Key customers and partnershipsDomino Data Lab counted more than 20% of the Fortune 100 and served customers in the financial services, health and life sciences, insurance, and other sectors. Notable customers include GSK, Bayer, Cox Automotive, Johnson &amp; Johnson, and Topdanmark.Funding and financialsIn October 2021, the company raised USD 100 million in a Series F funding round led by Great Hill Partners. The funds were utilized to accelerate its product innovation and growth. In June 2022, the company raised an undisclosed amount in an extended Series F funding round from Snowflake Ventures.

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

Fivetran is a cloud-based automated data integration platform that enables businesses to move data from various sources, including SaaS applications, databases, and files, into data warehouses, data lakes, and other destinations. The company's platform offers multiple deployment models to meet diverse business needs, ranging from stringent security requirements to maintaining on-premises databases even after partial cloud migration.The company's data movement platform is designed to automate and streamline the process of extracting, loading, and transforming (ELT) data, empowering organizations to focus on data-driven insights and decision-making. With real-time analytics, database replication, AI workflows, and cloud migrations facilitated by Fivetran, thousands of customers worldwide can leverage the platform to drive business growth.Fivetran's core offering revolves around its connector library, which supports over 500 data sources, including SaaS applications, databases, ERPs, and files. These connectors enable automatic, reliable, and secure data movement, regardless of whether the data resides on-premises, in the cloud, or in a hybrid environment. The platform's scalable architecture allows businesses to seamlessly add or remove data sources as their needs evolve.To enhance the usability and accessibility of the ingested data, Fivetran employs a normalized schema approach. By delivering data in a normalized format, the platform enables customers to remix and reshape the data according to their specific requirements, facilitating efficient data analysis and reporting. Additionally, Fivetran offers pre-built data models and dbt Core integration, empowering customers to create analytics-ready tables tailored to their business use cases, such as analyzing deal opportunities from Salesforce, generating general ledger reports from QuickBooks data, or evaluating return on ad spend across advertising platforms.In <a href="https://sp-edge.com/updates/30203">June 2024</a>, the company launched Managed Data Lake Service to simplify the process of managing data lakes for businesses of any size. Key benefits include the ability to centralize data for insights and convenience. Furthermore, it reduces costs by discontinuing support for legacy data warehouses.In September 2024,&nbsp;<a href="https://sp-edge.com/updates/33748">Fivetran introduced "Hybrid Deployment",</a> allowing customers to run data pipelines within their environment while managing them through Fivetran's platform. This solution enables enterprises to securely centralize data from various sources, including cloud-based SaaS apps and legacy databases. Fivetran claims Hybrid Deployment offers full visibility of all pipelines from a single interface, enhanced data security, and simplified setup and maintenance.Key customers and partnershipsOver the years, Fivetran has attracted a diverse range of customers across various industries, including ecommerce, finance, technology, and media. Notable clients include Autodesk, Conagra Brands, JetBlue, Lionsgate, Morgan Stanley, and Ziff Davis, among others. These companies leverage Fivetran's platform to streamline their data integration workflows, optimize their analytics capabilities, and gain a competitive edge through data-driven decision-making.To further enhance its offerings and enable seamless integrations, Fivetran has established strategic partnerships with various technology providers, including data warehousing solutions, cloud platforms, and business intelligence tools. For instance, Fivetran collaborates with Databricks, enabling customers to build an open lakehouse with Delta Lake powered by the Databricks Data Intelligence Platform. Additionally, Fivetran's integration with Unity Catalog provides out-of-the-box governance and security for Fivetran-generated tables.

Fivetran

<div>
 
 Domo is a cloud-based analytics platform that enables businesses to connect, transform, and visualize data from various sources. It provides a comprehensive solution for data management, analysis, and visualization, empowering organizations to make data-driven decisions. Domo's platform is designed to foster collaboration, efficient decision-making, and improved business outcomes through its user-friendly interface and powerful data manipulation capabilities.
 
 
 Domo's key offerings include data integration, data warehousing, business intelligence (BI), and intelligent applications. The platform leverages its Adrenaline engine and offers over 1,000 pre-built connectors to extract data from cloud applications, databases, spreadsheets, and other sources. This data is then stored in Domo's internal data warehouse or accessed through federated queries, enabling users to analyze and visualize it using Domo's extensive collection of visualization tools and dashboards.
 
 
 Domo&rsquo;s user experience is designed to be intuitive and accessible, fostering high adoption rates across organizations. Its user-friendly interface, seamless collaboration features, and mobile-first approach contribute to its widespread adoption and ease of use. Domo's platform is built for speed and scalability, allowing organizations to quickly access and analyze even large datasets without experiencing performance issues.
 
 
 Key customers and partnerships
 
 
 Domo serves over 2,300 customers across various industries, including major enterprises such as eBay, Walmart, Cisco, Citibank, HP, The National Geographic Society, Verizon, US Army, Vanguard, Microsoft, IBM, Thomson Reuters, Airbus, Orange, AT&amp;T, Caterpillar, Volvo Cars, and Comcast.
 
 
 The platform has been widely adopted by organizations seeking to leverage data for better decision-making, improved customer insights, and enhanced marketing analytics. Domo has formed strategic partnerships with companies like Regional One Health and Torchy's Tacos, enabling them to leverage Domo's capabilities for healthcare metrics and finance applications, respectively.
 
</div>

Domo

Founded in 2014, Confluent, Inc. is a technology company headquartered in Mountain View, California. The company specializes in data streaming platforms, primarily based on Apache Kafka, an open-source project created by Confluent's founders while working at LinkedIn. Confluent offers two main products: Confluent Platform, an on-premise solution, and Confluent Cloud, a fully managed SaaS. These products help organizations harness real-time data streams for various applications, including microservices, Internet of Things (IoT), financial services, fraud detection, and customer analytics.Confluent's primary offering in data infrastructure services is its integration solution, which enables organizations to unify data from disparate sources. The Confluent Platform and Confluent Cloud act as clients' central nervous systems, allowing them to connect various IT systems and applications to capture and process real-time data streams. This capability enables businesses to make decisions based on continuously flowing data.In September 2024,&nbsp;<a href="https://sp-edge.com/updates/33818">Confluent announced upgrades to its Confluent Cloud</a> product, enhancing support for Apache Flink. The updates include support for the Table API, simplifying development for Java and Python users, and private networking support to improve data security. These upgrades aimed to simplify Flink deployments, enhance security, and make it easier for organizations in regulated industries to stream data and integrate it into applications.Key customers and partnershipIn December 2023, Confluent expanded partnerships with MongoDB, Pinecone, Rockset, Weaviate, and Zilliz as part of its "Data Streaming for AI" initiative. These partnerships aimed to provide real-time contextual data from Confluent's platform to partners' vector databases, facilitating the development of AI-powered applications.

Confluent

<div>
 
 dbt Labs provides an open source data transformation tool that uses analytics engineering. It is aimed at programmers with knowledge of SQL to develop models with SELECT statements, test and document each model, and install safely with Git-enabled version control. The software enables the user to develop faster, work from the same assumptions, deploy with confidence, and&nbsp; ensure low risk with governance and safety. The company also offers dbt Core, which is an open source software for analytics engineers, and dbt Cloud Enterprise for secure, reliable access to data. JetBlue and Domain are some of its clients.
 
 
 
</div>

dbt Labs

Starburst provides an analytics engine that enables organizations to access and analyze distributed data without moving it from its source location. The company's platform is built on Trino (formerly known as Presto), a distributed SQL query engine designed for running interactive analytics queries across various data sources. The platform allows users to query data across multiple databases, data lakes, and data warehouses simultaneously, eliminating the need for costly and time-consuming data centralization. In February 2023, Starburst introduced Warp Speed, a smart indexing and caching solution that accelerates queries up to 7x faster by autonomously identifying and caching frequently used data. The company's software includes two main offerings: Starburst Enterprise for self-managed deployments and Starburst Galaxy, a Software-as-a-Service (SaaS) solution launched in 2021 that enables data lake and cross-cloud analytics. In February 2022, Starburst reported tripling its customer base and annual recurring revenue in the previous 12 months.
Key customers and partnerships
Starburst's platform is used by organizations including Zillow, Standard Chartered, Carrefour Brazil, Comcast, DoorDash, VMware, and Condé Nast. The platform helped Priceline reduce data storage costs by 5-10x while AssuranceIQ achieved a 10% increase in conversion rates. Starburst had established partnerships with major cloud platforms including AWS, Azure, Google Cloud Platform, Alibaba Cloud, Red Hat, and HPE. The company also partnered with Red Hat as one of the inaugural members of the Red Hat OpenShift Data Science ecosystem.

Starburst

Solutions to unify data from disparate sources by extracting, transforming, loading, and storing data in a usable form (such as in data warehouses) for further analysis.

Tools to monitor data for quality issues in real-time, as it moves throughout the data pipeline.

Providers of storage solutions that help accelerate data analytics. These include primary storage solutions, such as data warehouses and data lakes, and secondary storage solutions for non-mission-critical data.

Solutions that enable businesses to carry out data processing and create ML models on the underlying data for predictive analysis.

Tools for enterprises to visualize data in a graphical form and obtain insights on the same using AI and natural language processing.

Companies that use GenAI as a core part of their product offering for data infrastructure & analytics.

Leverages GenAI to help organizations extract insights and supports GenAI application development through data preparation

Offers data analytics and storage platforms for business under a B2B SaaS model

These are tools that help prepare data for AI/ML applications

PROMINENT_CATEGORY

<div>
 Domino, a data lab organization, has introduced Domino AI Gateway and integrations with vector databases as part of its GenAI applications. These enhancements are developed to uplift the scalability of GenAI projects within enterprise-level organizations.
 Domino AI Gateway, designed for arranging controlled access to large language models (LLMs) including those from OpenAI and Anthropic, aims at managing potential risks. The gateway extends security solutions such as handling LLM API keys and monitoring their usage to backup cost management.&nbsp;
 The feature associated with vector databases, particularly the Domino Pinecone Vector Database connection, ensures rapid and safe access to vectorized data. This becomes crucial for applications that employ the Retrieval Augmented Generation (RAG) methodology.
 
</div>

Domino Data Lab

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