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

SV Angel is 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

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

Our mission is to coach and invest in entrepreneurial leaders building world-class, purpose-driven organizations. Led by Jeff Weiner and Brian Rumao. Sector focus areas include B2B / enterprise software, financial tech, consumer apps, health and wellness and education. We are interested in productivity software and virtual work, direct-to-consumer / e-commerce, SaaS, and data and AI/ML-powered platforms.

Next Play Ventures

Meritech Capital provides late-stage venture capital to technology companies. It specializes in the fields of finance, venture capital, and late-stage investment management.  It was founded in 1999 and headquartered in Palo Alto, California.

Meritech Capital Partners

Ignition is a venture capital firm dedicated to helping the best entrepreneurs seize opportunity. With over $2B under management, Ignition invests in emerging and future leaders in enterprise software.  Ignition brings together an unparalleled combination of domain focus, technical expertise, and global operational experience. Ignition's partners are proven business leaders who have built some of the world's most successful businesses of the last two decades, including Microsoft Windows and Office, McCaw Cellular Communications, AT&T Wireless and Starbucks.  Ignition helps entrepreneurs by turning their early idea into a business, to hiring the right team, providing the right industry and functional insight and connections, to growing the business strategically, globally, financially, to realizing the best ultimate outcome, Ignition is ready to go the distance.

Ignition 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.

Corner Ventures, re-branded from DAG Ventures (c. 2004) in 2018, with offices in Silicon Valley, New York, Tel Aviv and Tokyo, focuses on building category leading companies in a variety of industries including information technology, cyber-security, financial services, healthcare, software among others.

Corner Ventures

T. Rowe Price is an investment management firm dedicated to funding technology startups. The firm serves individuals, financial intermediaries, and institutions and offers a full range of investment strategies across a broad spectrum: debt, equities, and private equities.

T. Rowe Price

Google Ventures invests in sectors including life sciences, consumer, enterprise, crypto, climate, and frontier technology. With Alphabet as its sole limited partner, Google Ventures focuses on long-term investments. Its operating partners assist startups in design, equity, diversity & inclusion, talent, and engineering and help them connect with Google for technology and expertise. Founded in 2009 as Google Ventures, Google Ventures manages over $8 billion in assets with 400 active portfolio companies in North America and Europe. Some notable investments include Uber, Nest, Slack, GitLab, and One Medical. Google Ventures is based in the San Francisco Bay Area with offices in Cambridge, New York, and London.

Google Ventures

DFO Management, LLC (“DFO”), is the family investment office of Dell Technologies Founder, Chairman, and CEO Michael Dell and his family. DFO engages in a broad range of investment activities with flexibility to invest in a wide variety of asset classes. The Dell family office was initially established in 1998 as MSD Capital, L.P., and was restructured as DFO at the end of 2022.

DFO Management

Intel Capital invests in innovative startups targeting cloud and AI infrastructure, edge, 5G, autonomy, cybersecurity, client & gaming, enterprise applications, silicon design and manufacturing, and a wide range of other disruptive technologies.

Intel Capital

Cloudera

Cloudera develops a data management and analytics platform. They specialize in delivering a hybrid data platform with secure data management and cloud-native data analytics. They provide software subscriptions and public cloud services. They also provide clients with professional services for the implementation and use of software subscriptions, machine learning expertise, consultation, training, and education services.

Cloudera is a data infrastructure and analytics company that operates a hybrid data platform for modern data architectures. It initially began as a distributor and developer of the Hadoop data processing platform but evolved to offer a range of proprietary data management products and services.

Data Infrastructure & Analytics

Cloudera offers a Machine Learning tool designed to empower enterprise data science teams. This cloud-native service provides data scientists with the flexibility they require while meeting IT needs. The Cloudera Machine Learning platform facilitates collaboration across various stages of the data lifecycle. It grants data science teams immediate access to enterprise data pipelines and scalable compute resources. The tool also allows users to work with their preferred tools, enhancing productivity and user experience. Cloudera Machine Learning aims to simplify the process of transitioning analytic workloads into production environments. Additionally, it offers capabilities for managing machine learning use cases across the business at scale, enabling organizations to leverage their data assets more effectively. In&nbsp;<a href="https://sp-edge.com/updates/33560">September 2024</a>, Cloudera launched several new accelerators for ML Projects (AMPs). These AMPs can be deployed with a single click from the Cloudera platform to reduce time-to-value.

The toolkit to build machine learning applications at scale

Machine Learning Infrastructure

Cloudera Achieves Agency-Level Authority to Operate at the FedRAMP Moderate Level from the Department of Veterans Affairs

CrewAI

To deliver technical capabilities, including agentic ETL elements, dynamic report generation, and cross-organizational capabilities.

Automation to improve business efficiency

Workflow Automation Platforms

Companies which utilize GenAI as a core part of their product offering for workflow automation

Snowflake

Cloudera partnered with Snowflake, a cloud-based data and AI infrastructure company, to access Cloudera's Data Lakehouse via Apache Iceberg REST Catalog, to ingest, prepare, and process their data across on-premise and cloud platforms.

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.

Red Hat

To address the growing demand for AI workloads by bolstering cloud infrastructure security and robustness.

Building future-ready applications in the cloud

Cloud-native Tech

Vendors that bundle different tools from different layers together into a platform, solving a larger problem. These can include an orchestration tool, a container runtime, service discovery, networking, an API gateway, etc.

Rewe Group

Amazon Web Services

Cloudera, a provider of a hybrid data platform, is leveraging Amazon S3 Express One Zone to enhance data access speed, enabling up to 40% faster read and write performance for its customers.

Cloudera has entered into a Strategic Collaboration Agreement (SCA) with Amazon Web Services (AWS) to enhance their partnership and advance cloud-native data management and analytics on AWS.

NVIDIA

Collaboration with NVIDIA, which will enable the Cloudera Data Platform (CDP) to integrate the RAPIDS Accelerator for Apache Spark 3.0, deployed on NVIDIA’s computing platforms.

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

To develop joint go-to-market programs designed to bring advanced data and AI solutions to more organizations across the expansive Apache Hadoop ecosystem.

Using data and automation to achieve 24/7 production.

Smart Factory

Companies that provide an industrial IoT platform across factories as the primary offering.

Cloudera selects Red Hat OpenShift as the preferred container solution for Cloudera data platform private cloud

To develop joint go-to-market programs designed to bring advanced data and AI solutions to organizations across the expansive Apache Hadoop ecosystem. The partnership builds on a long-standing relationship between IBM and Hortonworks, which merged with Cloudera in January 2019, and created integrated solutions for data science and data management.

Hitachi

Through the use of Cloudera Enterprise in Hitachi's IoT Platform 'Lumada', both companies will collaborate and contribute to the creation of digital solutions to address challenges across a wide range of industries.

Alphabet

It partnered with Hadoop specialists at Cloudera to bring its Cloud Dataflow programming model to Apache’s Spark data processing engine.

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.

Cloudera is a data infrastructure and analytics company that operates a hybrid data platform for modern data architectures. It initially began as a distributor and developer of the Hadoop data processing platform but evolved to offer a range of proprietary data management products and services.The Cloudera Data Platform (CDP) provides a variety of capabilities related to and including data flows, stream processing, data engineering, data warehousing, operational databases, machine learning, and data hubs, and aims to provide a single platform for data management and analysis across multi-cloud and on-premise environments. The Cloudera Shared Data Experience (SDX) enables unified security and governance across open and cloud-native storage formats​​​​​​​​​​. The company also offers <a href="https://sp-edge.com/updates/31391">data observability solutions</a>.&nbsp;In <a href="https://sp-edge.com/updates/30050">June 2024</a>, the company acquired Verta, a machine-learning infrastructure company. Cloudera planned on enhancing its AI capabilities by integrating Verta's Operational AI platform, as well as retain its workforce, which could help the company further expand its AI capabilities.&nbsp;Key customers and partnershipsCloudera’s customer list spans multiple segments across financial services, telecommunications, the public sector, retail and consumer goods, insurance, manufacturing, and healthcare and life sciences, and as of November 2023, includes names such as Regions Bank, Zain, The New Yorker, Transamerica, Vodafone, and Rush University Medical Center.The company has partnered with numerous notable global companies to provide integrated data solutions and enhanced capabilities, including AWS, IBM, and Kyndryl, as of November 2023.In October 2024, Cloudera<a href="https://sp-edge.com/updates/34701"> partnered with Snowflake</a> to allow its joint customers to access Cloudera's Data Lakehouse via Apache Iceberg REST Catalog, to ingest, prepare, and process their data across on-premise and cloud platforms.&nbsp;

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

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

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

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

ANALYST_QUICK_TAKE

PROMINENT_CATEGORY

<div>
 
 CrewAI has formed a partnership with Cloudera to improve workflows driven by multiple AI agents. Through this collaboration, they'll introduce abilities such as agentic ETL components, dynamic report creation, and cross-organizational features. This integration finds application in various domains like healthcare, finance, industrial, and telecommunication, offering organizations the chance to automate intricate workflows and utilize real-time insights.
 
</div> Analyst QuickTake : 
 Agentic AI is gaining traction within the business sector, with several key partnerships driving innovation in this space. Notable examples include <a href="https: 
//neontri.com/blog/agentic-ai/"> Accenture and NVIDIA </a> , which have expanded their partnership to accelerate AI adoption in businesses by forming a dedicated NVIDIA Business Group; 2) <a href="https: 
//sp-edge.com/updates/36391"> Google Cloud's launch </a> of its AI Agent Ecosystem Program, which empowers partners to develop and deploy AI agents; <a href="https: 
//sp-edge.com/updates/35208"> NVIDIA </a> , which combined its AI infrastructure with the ServiceNow platform to develop more capable native AI agents; and <a href="https: 
//sp-edge.com/updates/33646"> Salesforce and IBM </a> , which expanded their partnership to offer pre-built AI agents and tools.

Cloudera

About EDGE

Contact Us

Resources

Area of Focus

Technology Research Made Effortless