Andreessen Horowitz is a venture capital firm specializing in investing in seed, start-ups, early, mid-stage, growth, and late-stage. It prefers to invest in the social media business and technology sector with a focus on software, back-end infrastructure, the infrastructure of the Internet, cloud computing, enterprise software and services, consumer, business Internet, mobile-Internet, consumer Internet, cloud computing, data storage, social network browsers data-storage, consumer electronics, networking functions, software related biology, biotech, and medicine companies at the intersection of computer science and life sciences with a focus on digital therapeutics, cloud technology in biology, and computational medicine.

Andreessen Horowitz

New Enterprise Associates is a prominent venture capital firm focusing on investments in technology and healthcare startups. They help entrepreneurs build transformational businesses across multiple stages, sectors, and geographies. With over $19 billion in cumulative committed capital since the firm’s founding in 1977, NEA invests in technology and healthcare companies at all stages in a company’s lifecycle, from the seed stage through the IPO. The firm's long track record of successful investing includes more than 210 portfolio company IPOs and more than 360 acquisitions.

New Enterprise Associates

Ant Group aims to create the infrastructure and platform to support the digital transformation of the service industry. They strive to enable all consumers and small businesses to have equal access to financial and other services that are inclusive, green, and sustainable.

Ant Group

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

Amplify Partners invests in technical founders solving technical problems for the enterprise. They invest in early-stage companies pioneering novel applications in machine intelligence and computer science.

Amplify Partners

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

11.2 Capital

The House Fund is a pre-seed and early stage venture capital fund focused on the boldest Berkeley startups.  UC Berkeley has some of the most brilliant minds and daring businesses in the world, like Tesla, Apple, and Intel. It has never had a place to unite its entrepreneurs, until now. Started in 2016, with 50+ investments, $2B in follow-on funding, and 10 exits later, The House Fund has become a thriving ecosystem for the boldest Berkeley startups to grow.

The House Fund

Foundation Capital is a venture capital firm dedicated to the proposition that one entrepreneur's idea, with the right support, can become a business that changes the world. The company is made up of former entrepreneurs who set out to create the firm they wanted as founders. This forward-thinking team of VCs has helped companies like Lending Club change the way money is lent and borrowed, Sunrun reinvent the residential clean energy market, and Netflix revolutionizes media distribution and consumption, among many others. Foundation Capital is currently invested in more than 60 high-growth ventures in the areas of consumer, information technology, software, digital energy, financial technology, and marketing technology. These investments include AdRoll, Beepi, Bolt Threads, DogVacay, Kik, ForgeRock, Lending Home, Localytics, and Visier. The firm's twenty-six IPOs include Lending Club, OnDeck, Chegg, Sunrun, MobileIron, Control4, TubeMogul, Envestnet, Financial Engines, Netflix, NetZero, Responsys and Silver Spring Networks.

Foundation Capital

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

Investing in the next generation of software infrastructure, powered by AI and Blockchain

Sancus Ventures

Anyscale

Anyscale, the company founded by the creators of Ray, is accelerating the development and productionization of AI applications, at any scale. Ray, the fastest growing open source project in distributed AI, lets developers instantly scale applications from a laptop to the cloud, without the cost or expertise of building complex infrastructure. By empowering developers of all skill levels to effortlessly develop and scale the end-to-end AI lifecycle on a single compute substrate and deploy the app into production, Anyscale is enabling organizations to bring AI products to market faster and at lower costs. Backed by Andreessen Horowitz, NEA, and Addition, Anyscale is based in San Francisco, CA. www.anyscale.com

Anyscale provides a platform supporting the development of apps for serverless infrastructure. It primarily caters to developing artificial intelligence (AI) and machine learning (ML) apps which are scalable and distributed. Anyscale’s “Ray 1.0” open source project offers a serverless compute API with an ecosystem of libraries, enabling user apps to scale up and down based on demand, serverlessly.

The innovative cost dynamics of serverless computing allow more customers onto the cloud without breaking the bank.

Serverless Computing

Anyscale provides an open-source Python framework called “Ray” that allows developers to build multi-cloud AI applications and run models on very large data sets. The platform enables model training using approaches such as reinforcement learning, model tuning, and model serving.

The toolkit to build machine learning applications at scale

Machine Learning Infrastructure

<div>Anyscale, the company founded by the creators of Ray, is accelerating the development and productionization of AI applications, at any scale. Ray, the fastest growing open source project in distributed AI, lets developers instantly scale applications from a laptop to the cloud, without the cost or expertise of building complex infrastructure. By empowering developers of all skill levels to effortlessly develop and scale the end-to-end AI lifecycle on a single compute substrate and deploy the app into production, Anyscale is enabling organizations to bring AI products to market faster and at lower costs. Backed by Andreessen Horowitz, NEA, and Addition, Anyscale is based in San Francisco, CA.</div>

Empowering Tomorrow's Innovations with Generative AI Infrastructure

Generative AI Infrastructure

How Anyscale cofounder Robert Nishihara is smoothing AI’s complexities

NVIDIA

NVIDIA AI software integrated with Anyscale Ray unified computing framework accelerates and boosts efficiency of generative AI development with open-source and supported software.

Integrated solutions that handle the end-to-end processes of developing, training, deploying, and monitoring ML models.

Anyscale provides a platform supporting the development of apps for serverless infrastructure. It primarily caters to developing artificial intelligence (AI) and machine learning (ML) apps which are scalable and distributed. Anyscale’s “Ray 1.0” open source project offers a serverless compute API with an ecosystem of libraries, enabling user apps to scale up and down based on demand, serverlessly.In August 2022, the company launched the second iteration of its “Ray” platform which offers a serverless compute API with an ecosystem of libraries that enables users to scale their apps up and down based on demand serverlessly. The new offering includes features such as 1) Ray AI runtime, which adds a unified runtime layer for ML applications 2) KubeRay, a toolkit for managing the execution of apps on Kubernetes and 3) new integrations with ML tools such as Weights &amp; Biases and Hugging Face.Key customers and partnershipsAs of July 2024, Anyscale served more than 10,000 organizations globally. Notable customers include Uber, LinkedIn, Shopify, Amazon, and Visa.The company entered a partnership with NVIDIA in September 2023 to enhance the performance and efficiency of LLM development on Ray and the Anyscale Platform.

Triggermesh’s platform allows users to create serverless apps that integrate multiple cloud, data center, and on-premise software and environments, on top of Kubernetes. Through these integrations, the platform aims to break “silos” between enterprise customers and their software development and IT operations (DevOps) teams. The cloud and infrastructure integration development speed is reportedly enhanced by reusing connectors and customizable templates.In March 2022, the platform announced broad support for KNative (an open-source platform to build and deploy serverless workloads) which includes any conformant Knative deployment, along with the provision of Knative distribution. TriggerMesh also announced broad support for creating event-driven architecture that runs on Kubernetes in Google Cloud, to enable users to create integrations to sync data or drive event-driven workloads. Triggermesh went on to launch a service to enable enterprises using Kubeless migrate to Knative in May 2022.

Triggermesh

Iron.io offers multiple tools to assist development operations (DevOps) to focus on core tasks, without managing infrastructure. The company entered the serverless computing market in 2016, with the launch of IronFunctions, effectively an open-source platform that can be used by developers and uses containers as the base. It allows users to launch serverless applications and functions on private and public clouds, on-premise servers, and hybrid environments. IronFunctions can be written in a variety of programming languages including Ruby, PHP, Python, Java, Node.js, Go, and .NET. However, the company currently only provides helper libraries and integration with Amazon Web Services (AWS) Lambda.The company has expanded its operations since 2017 by adding an office in Tokyo, expanding its engineering and customer success teams, and continuing to improve the company’s products (bug fixes, improvements to internal tooling, and adding concurrency graphs, etc.). Iron.io looks to continue ramping up the development of its products by improving performance and reliability and developing a new user interface.Iron.io also continues to invest in new cutting-edge technologies such as “Computerless,” which eliminates the physical machine altogether and allows for it to be fully encapsulated in fiber optic cable.Key customers and partnershipsIts key customers include Google, Harry’s, Philips, Whole Foods, Veritone, and Counsyl.

Iron.io

Elotl offers the “Elotl Milpa” serverless platform to deploy Kubernetes (container orchestration system) apps on the cloud (mainly AWS, Google Cloud, Azure cloud, and Oracle cloud). It allows users to run their Kubernetes workloads in a cost effective manner (around 60%-80% cost savings relative to traditional offerings), avoiding vendor lock-in, Its offering also includes multi-tenancy security.Key customers and partnershipsAs of January 2022, its customers included Robinhood, Ronin, and Symphony, among others.In the year leading to November 2021, deployments through Elotl expanded 5x YoY, and the company became a founding member of the “Mobile Native Foundation” (a space for developers to collaborate on open source projects and discuss topics).

Elotl

ServerlessOps offers DevOps transformation advisory services, focusing on Amazon Web Services (AWS) serverless technology. The firm covers both technical training as well as implementation engineering. ServerlessOps claims it focuses on promoting AWS usage, as it believes AWS Lambda has the best combination of runtime and range of cloud services.

ServerlessOps

Sparta is an open-source framework for building and deploying Go microservices on AWS Lambda-powered microservices. It allows developers to define their application logic, AWS infrastructure, operational metrics, alert conditions, and security policies using Go types within a monorepo. Sparta transforms a Go application into a self-deploying AWS Lambda service, automatically provisioning the required infrastructure through CloudFormation.It integrates with various AWS services, including DynamoDB, S3, Kinesis, SNS, SES, CloudMap, CloudWatch Events, CloudWatch Logs, and Step Functions. It also allows provisioning custom AWS resources and defining IAM roles with limited privileges to minimize the service's attack surface. Sparta emphasizes security and operational best practices as first-class goals.One of Sparta's key features is its ability to discover dynamically created AWS resources at runtime, eliminating the need for hard-coded ARNs in the codebase. This promotes an immutable infrastructure approach. The framework aims to discourage the deployment of monolithic applications as Lambda functions, instead favoring a microservices architecture.

Sparta

This includes all serverless software which does not fall into the other categories but are related to the serverless market (e.g serverless based database providers).

Software and services that monitor, optimize, and enable integrations to improve performance.

Businesses and organizations helping programmers transition to serverless platforms by reducing client dependency on vendor-specific offerings.

Businesses that fill in knowledge gaps between clients and serverless vendors for developing and running complex apps and programs.

Vendor platforms such as AWS Lambda and Azure Functions used by clients to run their program. Effectively the infrastructure for serverless computing.

Serverless database providers offer infrastructure for running Gen AI models

Anyscale provides an open-source Python framework called “Ray” that allows developers to build multi-cloud AI applications and run models on very large data sets. The platform enables model training using approaches such as reinforcement learning, model tuning, and model serving.The company also offers the Anyscale platform, which is a managed version of Ray that runs on AWS and requires less expertise than Ray to operate. It allows developers to build, tune, and train machine learning (ML) workloads and deploy them into production. Anyscale ML Workspace enables developers to leverage the same set of tools throughout the process such as VS Code and Jupyter. The platform also supports integration with third-party orchestration tools such as Airflow and Prefect. The company claims that the Anyscale platform has the ability to start up clusters 5x faster than Ray. It also allows automation capabilities that support integration with Anyscale’s managed Grafana and Ray dashboard, which also delivers a monitoring and observability stack.In addition, the company provides <a href="https://sp-edge.com/updates/19041">Aviary </a>, an open-source, free, cloud-based infrastructure designed to assist developers to choose and integrate large language models (LLMs) into their application. Aviary offers a unified framework designed to deploy multiple LLMs, and allows developers to A/B test models to improve functionality while maximizing GPU utilization and reducing cloud costs. The product also offers libraries, tools, documentation, and sample code to aid developers to deploy LLMs into production. It also provides <a href="https://sp-edge.com/updates/21932">Anyscale Endpoints</a>, which enables developers to integrate LLMs into their applications using APIs.Key customers and partnershipsAs of August 2022, Anyscale served more than 1,000 organizations globally. Notable customers include Amazon, Ant Group, Ricardo, Dow, Uber, and Visa. The company entered into a partnership with <a href="https://sp-edge.com/companies/4353">NVIDIA</a> in September 2023, to enhance the performance and efficiency of LLM development on Ray and the Anyscale Platform.Funding and financialsIn August 2022, the company raised USD 99 million in a Series C funding round co-led by Addition and Intel Capital at a more than USD 1 billion valuation. The funds were utilized to build out its distributed AI-computing platform.

Datagen provides a self-service synthetic data platform that generates visual synthetic data of humans for computer vision applications. The platform allows users to write their own code to generate labeled synthetic data for faces, full body, and humans in motion in the form of images and videos to test and train AI models while retaining complete control over the data. The data covers a range of computer vision tasks including face landmark detection, face and hair segmentation, facial recognition and identification, full body pose estimation, full body segmentation, and behavior detection.Key customers and partnershipsThe company serves three of the top five global technology companies and Fortune 500 companies across the automotive, smart fitness, AR/VR/metaverse, smart office, and home security industries. Its notable customers include Google, Toyota, NVIDIA, IBM, and Intel.Funding and financialsIn March 2022, the company raised USD 50 million in a Series B funding round led by Scale Venture Partners. The funds were utilized to bolster its position in the market.Datagen reported to have recorded 8x growth in revenue in 2022.

Datagen

Weights &amp; Biases offers a platform that allows users to build models with experiment tracking, data set and model versioning, data visualization, hyperparameter optimization, and model management. The platform enables users to automatically retrain and re-evaluate models and centrally manage all model versions through every lifecycle stage—from development to staging to production. It also helps to visualize comparisons between model versions to evaluate performance and identify regressions before model deployment. It also offers toolkits such as <a href="https://sp-edge.com/updates/19172">W&amp;B Weave and W&amp;B Production Monitoring </a>to build and monitor data- and ML-powered applications, respectively, through interactive visualizations.The company also offers a <a href="https://sp-edge.com/updates/17880">suite of tools (W&amp;B Prompts) </a>to support large language model operations (LLMOps). W&amp;B Prompts includes tools and features for experiment tracking, debugging, and collaboration, as well as a one-click method to evaluate and score prompts through the OpenAI Eval’s framework.The company provides the platform through a free tier and under a subscription model for up to USD 50 per user per month.Key customers and partnershipsWeights &amp; Biases served more than 700,000 ML practitioners as of August 2023. Its notable include NVIDIA, Toyota, BMW Group, Samsung, Fujifilm, Truebill, and Clear Capital.The company has <a href="https://sp-edge.com/updates/18663">partnered with Lambda </a>, a GPU cloud computing provider, to offer its MLOps platform integrated with the infrastructure services of the latter, catering to enterprises dealing with AI and deep-learning workloads.Funding and financialsIn August 2023, the company raised <a href="https://sp-edge.com/updates/20874">USD 50 million in a strategic investment </a>round at a valuation of USD 1.25 billion, led by Daniel Gross and Nat Friedman. The round also saw participation from Sapphire Ventures, Coatue, Insight Partners, and other investors. The company aimed to utilize the fresh funds to further develop its ML tools, including the launch of W&amp;B Prompts.

Weights & Biases

BentoML offers an open-source platform called Bento Cloud, for the deployment and scaling of AI applications. It is a fully managed platform that handles the complexities of AI infrastructure, providing serverless autoscaling as required during the development and production stages. The platform helps to ship models to production with advanced deployment options including online and shadow A/B testing, while also providing visibility through model performance monitoring. The platform integrates with an organization’s existing data stack and enables users to continuously deploy and improve models in production. The company offers its platform through a combination of subscription and usage-based model.In addition, BentoML also provides the following open-source platforms: 1) Yatai, for model deployment on Kubernetes and 2) bentoctl, for model deployment on any cloud platform.Key customers and partnershipsAs of January 2024, BentoML reported that over 1,000 organizations, comprising more than 3,000 members, use its platform. Its notable customers include Koo, Open Layer, Line, and Naver.The company entered into a strategic partnership with TomTom, a developer of location technology, to help integrate with various models as well as in LLM deployments.Funding and financialsThe company raised <a href="https://sp-edge.com/updates/19684">USD 9 million in seed funding </a>in June 2023 led by DCM Ventures, with participation from Bow Capital. It aimed to channel the newly acquired funds to enhance its platform and offer developers a range of tools for building, deploying, and scaling AI applications efficiently.

BentoML

Iguazio provides a serverless platform based on its open-source Nuclio framework that helps users to develop, deploy, and manage real-time AI applications without requiring them to manually manage underlying infrastructures such as servers and storage. The platform creates real-time intelligence for applications located at the edge, public cloud, and on-premise data centers and reduces bandwidth constraints by consolidating data into a repository and making it available for applications as required. The platform can ingest and transform data from any source, which is then used to train, evaluate, deploy, and monitor models in production.The company leverages Big Data and ML software such as Apache Spark, TensorFlow, and Kubernetes to manage software containers that enable applications to run across different computing environments.Key customers and partnershipsIguazio serves customers in the financial services, telecommunications, smart mobility, manufacturing, retail, AdTech, gaming, healthcare, energy, and utilities sectors. Notable customers include Samsung, Microsoft, NVIDIA, AWS, Google, and Intel.Funding and financialsIn January 2020, the company raised USD 24 million in a funding round led by INCapital Ventures. The funds were utilized to accelerate its growth, expand its reach into new global markets, grow sales, and facilitate new sales channels that include companies such as Dell Technologies

Iguazio

Cogito Tech provides image and video annotation to generate computer vision training data sets for ML &amp; deep learning (DL). The video annotation solution leverages AI-powered tools to convert video into a sequence of images and generates training data sets for ML-based AI models, including self-driving cars and drones. The AI model understands and derives insights from visual data to detect, identify, classify, and track objects in an image or video. Cogito also provides virtual assistants and chatbots to help users in the process of training ML algorithms. Cogito Tech also provides high-quality, ethically sourced datasets that are compliant and reliable to train ML models.In addition, the company provides services to fine-tune LLMs and GenAI applications through reinforcement learning techniques as well as stress test models through red teaming.Key customers and partnershipsAs of December 2022, the company served more than 150 customers across 25 countries in the retail, medical, automotive, agriculture, robotics, smart cities, security, and manufacturing industries. Notable customers includes Verizon Media, The University of Sydney, National Geographic, Tumblr, and Vimeo.

Cogito Tech

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

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

Platforms that generate artificial data that mimics the characteristics of real data, which is then used to train ML models at scale.

Platforms that help monitor and manage ML models in training and deployment to track performance, conduct variance analysis, and optimize performance.

Makers of hardware such as CPUs, GPUs, and other application-specific hardware required to train and run ML workloads.

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>
 
 Anyscale, the company founded by the creators of Ray, is accelerating the development and productionization of AI applications, at any scale. Ray, the fastest growing open source project in distributed AI, lets developers instantly scale applications from a laptop to the cloud, without the cost or expertise of building complex infrastructure. By empowering developers of all skill levels to effortlessly develop and scale the end-to-end AI lifecycle on a single compute substrate and deploy the app into production, Anyscale is enabling organizations to bring AI products to market faster and at lower costs. Backed by Andreessen Horowitz, NEA, and Addition, Anyscale is based in San Francisco, CA. 
 
</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’ 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 capabilities2. NR1-M™ 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 architectureThe 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 partnershipsIn 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.

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

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—similar to a ChatGPT-style AI system—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. In&nbsp;<a href="https://sp-edge.com/updates/28436">April 2024</a>, Databricks introduced its Data Intelligence platform for energy to use AI technology to process large data for energy companies. Following this, the company added synthetic data capabilities for AI agent evaluation in&nbsp;<a href="https://sp-edge.com/updates/37008">December 2024</a>.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 partnershipsAs of November 2024, Databricks served a global customer base of more than 10,000 organisations, including Comcast, Conde, DuPont, Honeywell, Rolls-Royce, Shell, and Tata Steel.Databricks collaborates with over 1,200 global cloud, ISV, and consulting partners to deliver data, analytics, and AI solutions, supporting customers in scaling their projects.Notable partnerships include collaboration with AWS in&nbsp;<a href="https://sp-edge.com/updates/34884">October 2024</a> to leverage AWS Trainium chips as the preferred AI chip to power Databricks' Mosaic AI model training and serving capabilities.&nbsp;Databricks also partnered with Karini AI in&nbsp;<a href="https://sp-edge.com/updates/33687">September 2024</a> to accelerate GenAI deployment for enterprises.&nbsp;

Databricks

Labelbox offers a data-centric AI platform for enterprises, enabling them to develop, optimize, and use AI to solve complex problems and power new products and services.&nbsp;&nbsp;Labelbox’s platform offers capabilities for building, optimizing, training, fine-tuning LLMs, and AI-enabled data labeling automation.&nbsp;Its products include&nbsp;1) Catalog: A platform for building AI applications with features such as advanced search capabilities and optimizing data for labeling budgets2) Annotate: A data labeling solution designed to streamline and accelerate labeling operations using automation tools and pre-labeling techniques(3) Model: Offers tools for data enrichment, model-assisted labeling, and custom Foundry Apps to automate data management tasks and improve AI model performance&nbsp;&nbsp;(4) Boost: Offers fully managed tailored solutions such as on-demand data labeling services to enhance AI development speed and efficiency.&nbsp;As such, Labelbox enables companies to streamline the fine-tuning and alignment of LLMs and enables the validation of outputs through techniques such as reinforcement learning with human feedback (RLHF), reinforcement learning from AI feedback (RELIEF), and evaluation. This incorporation of human expertise ensures more accurate, contextually relevant, trustworthy, and secure results from LLM systems.The platform is offered through a SaaS subscription model with packages ranging from free subscriptions with limited usage and custom pricing for enterprises.Key customers and partnershipsThe firm's solutions have use cases across diverse industries, including retail, consumer internet, healthcare, manufacturing, and financial services. Labelbox has a large portfolio of customers, including NASA's Jet Propulsion Laboratory and Blue River Technology, a smart AgriTech company that used Labelbox's model-assisted labeling suite to enhance its See &amp; Spray technology in smart agriculture, resulting in herbicide cost savings of 70%–80. Labelbox's customers also include several Fortune 500 companies, such as Walmart, P&amp;G, Audi Adobe, Airbnb, Bayer, and Bosch.Key partnerships include a long-term collaboration with <a href="https://sp-edge.com/updates/21770">Google Cloud </a>to facilitate digital transformations in retail, consumer internet, financial services, and manufacturing and logistics.&nbsp;

Labelbox

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 enable safe, responsible, and ethical GenAI deployment, ensuring compliance with regulations and/or protection against GenAI-based cybersecurity threats.

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.

Anyscale, the integrated MLOps platform, has launched Anyscale Endpoints, a service that allows developers to integrate large language models into their applications using APIs. The service is available for $1 per million tokens. Anyscale Endpoints aims to simplify the development process and reduce costs associated with AI applications. It also integrates with popular ML libraries and frameworks. In addition, Anyscale previously introduced Aviary, a cloud-based infrastructure that assists developers in seamlessly integrating language models into their applications. The demand for products that support the incorporation of AI capabilities continues to increase among ML infrastructure providers.

Anyscale

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