Point Nine Capital is a Berlin-based venture capital firm focused exclusively on early-stage Internet investments in areas like Software-as-a-Service (SaaS), online marketplaces, and mobile. The fund and its managers, Pawel Chudzinski and Christoph Janz have backed a number of highly successful Internet companies such as Delivery Hero, Clio, Shiftplanning, Vend, Typeform, and Zendesk from their earliest stages.

Point Nine

Runa Capital is a technology-focused venture capital firm managing two funds – Runa I was launched with $135M in 2010 and has made 33 investments,  Runa II of $135M was launched in 2014 and has made 30 investmerns and Runa III was started in 2019 and is in active investment stage right now.  The fund was established to seek early stage opportunities in the rapidly growing tech sector, with the specific focus on deeptech (AI, ML, open-source), future of computing, fintech infrastructure and enterprise software. Runa brings a team with extensive operational experience and is focused on finding growth businesses that generate revenues, supporting them in the global marketplace and turning them into international champions. Founded by Ilya Zubarev, Serg Bell (founders of Parallels and Acronis) and Dmitry Chikhachev (Ericsson, Ritzio, Uvenco) Runa Capital is run by a team of successful entrepreneurs, most of whom have worked together for over 15 years. It is a united team with broad geographical and cross-industry experience, as well as an extensive professional network. Runa Capital investment team members possess an excellent track record in tech investments.

Runa Capital

Granatus Ventures is the first Armenia-based Venture Capital firm with offices in Yerevan, London and Singapore providing investment, networks and expertise to startups worldwide that leverage Armenia's potential as an emerging technology hub.

Granatus Ventures

SmartGateVC is a SoCal and Armenia based VC with a focus on pre-seed investments in AI. Krisp (the world’s best noise cancellation technology), SuperAnnotate (the fastest annotation platform and services for training AI) are among our investments (31 portfolio companies since 2018). Sierra Ventures, Upfront Ventures, AI Fund, YC, and others are among our follow-on investors. We invest out of 2 funds and our investors include Tim Draper, One Way Ventures, and other high-profile GPs, entrepreneurs, and professionals.

SmartGateVC

Fathom Capital is an early-stage VC firm focusing on enterprise applications and IT infrastructure.

Fathom Capital

Berkeley SkyDeck Fund is an investment Arm Behind UC Berkeley's SkyDeck Accelerator.

Berkeley SkyDeck Fund

Base10 is an early-stage venture capital firm investing in the automation of the real economy. They bring automation to traditional sectors of the economy.  Today, the company has backed nearly 30 companies. Base10 creates industry teams that consider what is going to happen in the next five years, and then call the companies they see playing a role. It either turns into an investment, or Base10 will follow the company for 18 months. It is based in San Francisco, California, and was founded in 2017.

Base10 Partners

Plug and Play is a seed and early-stage investor focused on great teams leading emerging growth companies.  Plug and Play runs 12 industry-specific accelerator programs twice a year, that acts as a platform for major corporations and high quality startups to connect and collaborate.  Located in the heart of Silicon Valley, Plug and Play participates in Seed, Angel and Series A funding where they often co-invest with their strategic partners. Through years of experience and as part of their network, Plug and Play has put together a world-class network of serial entrepreneurs, strategic investors, and industry leaders who actively assist the firm with its successful and growing investment portfolio.  SEED ROUND. Plug and Play participates in seed round investing through a program called Startup Camp. Startup Camp is a 10-week program based in Silicon Valley for top-notch entrepreneurs to work intensively on building out their business model. Select startups will refine their business models and prototypes with help from a combination of structured workshops, speaker series and mentorship sessions, as well as active coaching from their investment team. At the culmination of Startup Camp, founders will have crystalized their business plans and pitched their company to the venture capital community at EXPO Demo Day.''  ANGEL ROUND Plug and Play makes angel round investments throughout the year, sourced from their monthly Plug and Play Angels (PAPA) sessions. They are partnered with local angel investors in Silicon Valley who participate in PAPA to find the most promising startups and best new technologies.  SERIES A. Series A typical Series A round is in the range of $2 million to $10 million, and is intended to provide operating capital for the company for six months to two years. This round capitalizes the company as it develops its products, performs initial marketing and branding, acquires talent, and conducts other early-stage business operations. It is in this stage that Plug and Play will co-invest with over 180 venture capital partners.  Plug and Play has helped grow market leaders such as PayPal, Danger, Google, DropBox, LendingClub, Zoosk, SoundHound, CreditSesame, Skytree, and has over 400 more early-stage startups in its portfolio.

Plug and Play

Socium Ventures

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

Databricks Ventures invests in innovative companies that share the view of the future for data, analytics, and AI. Databricks' inaugural initiative, the Lakehouse Fund, is focused on early and growth-stage companies that are extending the lakehouse ecosystem or using the lakehouse architecture to create the next generation of data and AI-powered companies.

Databricks Ventures

Play Time is a venture capital firm that intends to invest in the sports, technology, and media industries.

Play Time Ventures

SuperAnnotate

SuperAnnotate is the world's leading platform for building the highest-quality training datasets for Generative AI, LLMs, Computer vision, and NLP. With advanced tooling and QA, ML and automation features, data curation, Orchestration, and integrated workforce marketplace, we enable machine learning teams to build and manage incredibly accurate datasets and successful ML pipelines 10x faster.

SupperAnnotate offers a data annotation platform for labeling text, audio, images, videos, and LiDAR data using AI-assisted tools. The platform caters to a wide range of industries and use cases, including agriculture, healthcare, sports, robotics, aerial imagery, natural language processing, and document processing. The platform’s key features also include the ability to manage, query, and debug data; visualize data trends; fine-tune data; and automate data annotation workflows required to train ML models. Additionally, the company provides a data annotation service marketplace that comprises over 400 vetted professionally managed and multilingual annotation service teams, which help companies manually label the data. The platform also includes a project management tool that allows customers to monitor and track a project’s current progress as well as conduct comprehensive quality reviews.

The toolkit to build machine learning applications at scale

Machine Learning Infrastructure

SuperAnnotate provides a data annotation platform that enables users to create, manage, and track GenAI-training datasets, facilitating fine-tuning, iteration, and evaluation within a single integrated enterprise solution. The platform simplifies dataset creation and curation, allowing users to build, fine-tune, and deploy models more efficiently by connecting data from local and cloud storage with robust security measures in place. Customizable interfaces support a range of GenAI tasks, including supervised fine-tuning, retrieval-augmented generation, and fine-grained reinforcement learning from human feedback.&nbsp;

Empowering Tomorrow's Innovations with Generative AI Infrastructure

Generative AI Infrastructure

SuperAnnotate raises USD 36 million in Series B funding for R&D and headcount expansion.. SuperAnnotate.. product 

SupperAnnotate offers a data annotation platform for labeling text, audio, images, videos, and LiDAR data using AI-assisted tools. The platform caters to a wide range of industries and use cases, including agriculture, healthcare, sports, robotics, aerial imagery, natural language processing, and document processing. The platform’s key features also include the ability to manage, query, and debug data; visualize data trends; fine-tune data; and automate data annotation workflows required to train ML models. Additionally, the company provides a data annotation service marketplace that comprises over 400 vetted professionally managed and multilingual annotation service teams, which help companies manually label the data. The platform also includes a project management tool that allows customers to monitor and track a project’s current progress as well as conduct comprehensive quality reviews.The company also provides a platform called ML Studio, which allows developers and engineers to visualize, manage, and query training data as well as automate data annotation workflows required to train ML models. Key customers and partnershipsIts notable customers include Samsung, Motorolla, IBM, and Hinge Health.In June 2020, the company partnered with OpenCV, an open-source computer vision platform, to improve the annotation process and toolsets for computer vision 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

SuperAnnotate provides a data annotation platform that enables users to create, manage, and track GenAI-training datasets, facilitating fine-tuning, iteration, and evaluation within a single integrated enterprise solution. The platform simplifies dataset creation and curation, allowing users to build, fine-tune, and deploy models more efficiently by connecting data from local and cloud storage with robust security measures in place. Customizable interfaces support a range of GenAI tasks, including supervised fine-tuning, retrieval-augmented generation, and fine-grained reinforcement learning from human feedback.&nbsp;SuperAnnotate also offers tools for model evaluation and comparison against benchmark tasks using predefined metrics, as well as features like "Explore" for curating relevant data subsets and "Orchestrate" for automating manual tasks and managing pipelines. Supporting various annotation types, such as object detection, pose estimation, segmentation, classification, OCR annotation, and handling of tiled and multi-layer imagery, the platform helps users create high-quality datasets to build top-performing models more quickly and easily.Key customers and partnershipsNotable enterprises that used SuperAnnotate included Canva, Databricks, IBM, and Qualcomm (November 2024).

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.
 
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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.
 
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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.

<div>
 SuperAnnotate, a GenAI dataset management platform, has secured USD 36 million in Series B funding. The round was led by Socium Ventures and saw participation from NVIDIA, Databricks Ventures, Play Time Ventures, Glynn Capital, among others. So far, the company's total funding has reached USD 53 million.
 The raised capital is intended to be used to increase the number of employees, which is currently 100, to invest in product research and development, and to expand its customer base. Currently, they serve over 100 companies.
 The platform provided by SuperAnnotate assists users in creating and monitoring GenAI training datasets. It offers tools for fine-tuning, iterating, and evaluating these datasets. Among their prestigious clients are companies like Databricks and Canva. Additionally, the company also provides access to a marketplace of crowd-sourced workers for data annotation tasks.
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SuperAnnotate

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