RunLve Alternatives

Build, deploy, and scale machine learning (ML) models faster, with fully managed ML tools for any use case. Through Vertex AI Workbench, Vertex AI is natively integrated with BigQuery, Dataproc, and Spark. You can use BigQuery ML to create and execute machine learning models in BigQuery using standard SQL queries on existing business intelligence tools and spreadsheets, or you can export datasets from BigQuery directly into Vertex AI Workbench and run your models from there. Use Vertex Data Labeling to generate highly accurate labels for your data collection.

Qloo is the “Cultural AI”, decoding and predicting consumer taste across the globe. A privacy-first API that predicts global consumer preferences and catalogs hundreds of millions of cultural entities. Through our API, we provide contextualized personalization and insights based on a deep understanding of consumer behavior and more than 575 million people, places, and things. Our technology empowers you to look beyond trends and uncover the connections behind people’s tastes in the world around them. Look up entities in our vast library spanning categories like brands, music, film, fashion, travel destinations, and notable people. Results are delivered within milliseconds and can be weighted by factors such as regionalization and real-time popularity. Used by companies who want to incorporate best-in-class data in their consumer experiences. Our flagship recommendation API delivers results based on demographics, preferences, cultural entities, metadata, and geolocational factors.

Amazon SageMaker is a fully managed service that provides every developer and data scientist with the ability to build, train, and deploy machine learning (ML) models quickly. SageMaker removes the heavy lifting from each step of the machine learning process to make it easier to develop high quality models. Traditional ML development is a complex, expensive, iterative process made even harder because there are no integrated tools for the entire machine learning workflow. You need to stitch together tools and workflows, which is time-consuming and error-prone. SageMaker solves this challenge by providing all of the components used for machine learning in a single toolset so models get to production faster with much less effort and at lower cost. Amazon SageMaker Studio provides a single, web-based visual interface where you can perform all ML development steps. SageMaker Studio gives you complete access, control, and visibility into each step required.

Composable is an enterprise-grade DataOps platform built for business users that want to architect data intelligence solutions and deliver operational data-driven products leveraging disparate data sources, live feeds, and event data regardless of the format or structure of the data. With a modern, intuitive dataflow visual designer, built-in services to facilitate data engineering, and a composable architecture that enables abstraction and integration of any software or analytical approach, Composable is the leading integrated development environment to discover, manage, transform and analyze enterprise data.

Scale your machine learning development from research to production with an end-to-end solution that gives your data science team all the tools they need in one place. As the leading data science platform for MLOps and model management, cnvrg.io is a pioneer in building cutting-edge machine learning development solutions so you can build high-impact machine learning models in half the time. Bridge science and engineering teams in a clear and collaborative machine learning management environment. Communicate and reproduce results with interactive workspaces, dashboards, dataset organization, experiment tracking and visualization, a model repository and more. Focus less on technical complexity and more on building high impact ML models. Cnvrg.io container-based infrastructure helps simplify engineering heavy tasks like tracking, monitoring, configuration, compute resource management, serving infrastructure, feature extraction, and model deployment.

Build, run and manage AI models, and optimize decisions at scale across any cloud. IBM Watson Studio empowers you to operationalize AI anywhere as part of IBM Cloud Pak® for Data, the IBM data and AI platform. Unite teams, simplify AI lifecycle management and accelerate time to value with an open, flexible multicloud architecture. Automate AI lifecycles with ModelOps pipelines. Speed data science development with AutoAI. Prepare and build models visually and programmatically. Deploy and run models through one-click integration. Promote AI governance with fair, explainable AI. Drive better business outcomes by optimizing decisions. Use open source frameworks like PyTorch, TensorFlow and scikit-learn. Bring together the development tools including popular IDEs, Jupyter notebooks, JupterLab and CLIs — or languages such as Python, R and Scala. IBM Watson Studio helps you build and scale AI with trust and transparency by automating AI lifecycle management.

Empowering the enterprise to do real data science at speed and scale with a full-featured machine learning platform. Spend less time managing tools and infrastructure, so you can focus on building machine learning applications that move your business forward. Anaconda Enterprise takes the headache out of ML operations, puts open-source innovation at your fingertips, and provides the foundation for serious data science and machine learning production without locking you into specific models, templates, or workflows. Software developers and data scientists can work together with AE to build, test, debug, and deploy models using their preferred languages and tools. AE provides access to both notebooks and IDEs so developers and data scientists can work together more efficiently. They can also choose from example projects and preconfigured projects. AE projects are automatically containerized so they can be moved between environments with ease.

Merging the best of a notebook and an IDE into one integrated coding environment, experts can explore their data and write stable code at the same time with fully automated cloud infrastructure. Zerve’s data science development environment gives data science and ML teams a unified space to explore, collaborate, build, and deploy data science & AI projects like never before. Zerve offers true language interoperability, meaning that as well as being able to use Python, R, SQL, or Markdown all in the same canvas, users can connect these code blocks to each other. No more long-running code blocks or containers, with Zerve enjoying unlimited parallelization at any stage of the development journey. Analysis artifacts are automatically serialized, versioned, stored, and preserved for later use, meaning easily changing a step in the data flow without needing to rerun any preceding steps. Fine-grained selection of compute resources and extra memory for complex data transformation.

The Databricks Data Intelligence Platform allows your entire organization to use data and AI. It’s built on a lakehouse to provide an open, unified foundation for all data and governance, and is powered by a Data Intelligence Engine that understands the uniqueness of your data. The winners in every industry will be data and AI companies. From ETL to data warehousing to generative AI, Databricks helps you simplify and accelerate your data and AI goals. Databricks combines generative AI with the unification benefits of a lakehouse to power a Data Intelligence Engine that understands the unique semantics of your data. This allows the Databricks Platform to automatically optimize performance and manage infrastructure in ways unique to your business. The Data Intelligence Engine understands your organization’s language, so search and discovery of new data is as easy as asking a question like you would to a coworker.

ClearML is the leading open source MLOps and AI platform that helps data science, ML engineering, and DevOps teams easily develop, orchestrate, and automate ML workflows at scale. Our frictionless, unified, end-to-end MLOps suite enables users and customers to focus on developing their ML code and automation. ClearML is used by more than 1,300 enterprise customers to develop a highly repeatable process for their end-to-end AI model lifecycle, from product feature exploration to model deployment and monitoring in production. Use all of our modules for a complete ecosystem or plug in and play with the tools you have. ClearML is trusted by more than 150,000 forward-thinking Data Scientists, Data Engineers, ML Engineers, DevOps, Product Managers and business unit decision makers at leading Fortune 500 companies, enterprises, academia, and innovative start-ups worldwide within industries such as gaming, biotech , defense, healthcare, CPG, retail, financial services, among others.

RapidMiner is reinventing enterprise AI so that anyone has the power to positively shape the future. We’re doing this by enabling ‘data loving’ people of all skill levels, across the enterprise, to rapidly create and operate AI solutions to drive immediate business impact. We offer an end-to-end platform that unifies data prep, machine learning, and model operations with a user experience that provides depth for data scientists and simplifies complex tasks for everyone else. Our Center of Excellence methodology and the RapidMiner Academy ensures customers are successful, no matter their experience or resource levels. Simplify operations, no matter how complex models are, or how they were created. Deploy, evaluate, compare, monitor, manage and swap any model. Solve your business issues faster with sharper insights and predictive models, no one understands the business problem like you do.

The entire process of building machine learning algorithms and predicting outcomes, packed in one single click. Not all data is built to be ready for ML, use the Data Dialog to seamlessly shape your dataset without wrangling your files. Share your prediction reports with your team or make them public. Allow anyone to start making predictions on your model. Bring dynamic ML predictions into your own app using our low-code API. Predict willingness to pay, score leads and much more in real-time. Obviously AI puts the world’s most cutting-edge algorithms in your hands, without compromising on performance. Forecast revenue, optimize supply chain, personalize marketing. You can now know what happens next. Add a CSV file OR integrate with your favorite data sources in minutes. Pick your prediction column from a dropdown, we'll auto build the AI. Beautifully visualize predicted results, top drivers and simulate "what-if" scenarios.

AI Cloud is a new approach built for the demands, challenges and opportunities of AI today. A single system of record, accelerating the delivery of AI to production for every organization. All users collaborate in a unified environment built for continuous optimization across the entire AI lifecycle. The AI Catalog enables seamlessly finding, sharing, tagging, and reusing data, helping to speed time to production and increase collaboration. The catalog provides easy access to the data needed to answer a business problem while ensuring security, compliance, and consistency. If your database is protected by a network policy that only allows connections from specific IP addresses, contact Support for a list of addresses that an administrator must add to your network policy (whitelist).

The Domino platform helps data science teams improve the speed, quality, and impact of data science at scale. Domino is open and flexible, empowering professional data scientists to use their preferred tools and infrastructure. Data science models get into production fast and are kept operating at peak performance with integrated workflows. Domino also delivers the security, governance and compliance that enterprises expect. The Self-Service Infrastructure Portal makes data science teams become more productive with easy access to their preferred tools, scalable compute, and diverse data sets. The Integrated Model Factory includes a workbench, model and app deployment, and integrated monitoring to rapidly experiment, deploy the best models in production, ensure optimal performance, and collaborate across the end-to-end data science lifecycle. The System of Record allows teams to easily find, reuse, reproduce, and build on any data science work to amplify innovation.

Combining Data Science, Business Intelligence, and Data Management Capabilities in One Integrated, Self-Serve Platform. Analance is a robust, salable end-to-end platform that combines Data Science, Advanced Analytics, Business Intelligence, and Data Management into one integrated self-serve platform. It is built to deliver core analytical processing power to ensure data insights are accessible to everyone, performance remains consistent as the system grows, and business objectives are continuously met within a single platform. Analance is focused on turning quality data into accurate predictions allowing both data scientists and citizen data scientists with point and click pre-built algorithms and an environment for custom coding. Company – Overview Ducen IT helps Business and IT users of Fortune 1000 companies with advanced analytics, business intelligence and data management through its unique end-to-end data science platform called Analance.

Saturn Cloud is an award-winning ML platform for any cloud with 100,000+ users, including NVIDIA, CFA Institute, Snowflake, Flatiron School, Nestle, and more. It is an all-in-one solution for data science & ML development, deployment, and data pipelines in the cloud. Users can spin up a notebook with 4TB of RAM, add a GPU, connect to a distributed cluster of workers, build large language models, and more in a completely hosted environment. Data professionals can use your preferred languages, IDEs, and machine-learning libraries in Saturn Cloud. We offer full Git integration, shared custom images, and secure credential storage, making scaling and building your team in the cloud easy. We support the entire machine learning lifecycle from experimentation to production with features like jobs and deployments. These features and built-in tools are easily shareable within teams, so time is saved and work is reproducible.

Sync, search and manage all the work across your data science team. Zepl’s powerful search lets you discover and reuse models and code. Use Zepl’s enterprise collaboration platform to query data from Snowflake, Athena or Redshift and build your models in Python. Use pivoting and dynamic forms for enhanced interactions with your data using heatmap, radar, and Sankey charts. Zepl creates a new container every time you run your notebook, providing you with the same image each time you run your models. Invite team members to join a shared space and work together in real time or simply leave their comments on a notebook. Use fine-grained access controls to share your work. Allow others have read, edit, and run access as well as enable collaboration and distribution. All notebooks are auto-saved and versioned. You can name, manage and roll back all versions through an easy-to-use interface, and export seamlessly into Github.

Machine Learning and Predictive Analytics Platform. Augment data-driven decision making and accelerate business with advanced artificial intelligence in a pre-built machine learning and big data analytics platform. OpenText Magellan uses AI technologies to provide predictive analytics in easy to consume and flexible data visualizations that maximize the value of business intelligence. Artificial intelligence software eliminates the need for manual big data processing by presenting valuable business insights in a way that is accessible and related to the most critical objectives of the organization. By augmenting business processes through a curated mix of capabilities, including predictive modeling, data discovery tools, data mining techniques, IoT data analytics and more, organizations can use their data to improve decision making based on real business intelligence and analytics.

Data is crucial when it comes to building, streamlining and growing your business. However, getting the full value out of data can be a challenge, many organizations are faced with poor access to data, incompatible tools, spiraling costs and slow results. Simply put, leaders who can turn raw data into real results will thrive in today’s landscape. The key to this is empowering everyone across your business to be able to analyze, build and collaborate on end-to-end AI and machine learning solutions in one place, fast. Streamflux is a one-stop shop to meet your data analytics and AI challenges. Our self-serve platform allows you the freedom to build end-to-end data solutions, uses models to answer complex questions and assesses user behaviors. Whether you’re predicting customer churn and future revenue, or generating recommendations, you can go from raw data to genuine business impact in days, not months.

Metacoder makes processing data faster and easier. Metacoder gives analysts needed flexibility and tools to facilitate data analysis. Data preparation steps such as cleaning are managed reducing the manual inspection time required before you are up and running. Compared to alternatives, is in good company. Metacoder beats similar companies on price and our management is proactively developing based on our customers' valuable feedback. Metacoder is used primarily to assist predictive analytics professionals in their job. We offer interfaces for database integrations, data cleaning, preprocessing, modeling, and display/interpretation of results. We help organizations distribute their work transparently by enabling model sharing, and we make management of the machine learning pipeline easy to make tweaks. Soon we will be including code free solutions for image, audio, video, and biomedical data.

A data science platform that improves productivity with unparalleled abilities. Build and evaluate higher-quality machine learning (ML) models. Increase business flexibility by putting enterprise-trusted data to work quickly and support data-driven business objectives with easier deployment of ML models. Using cloud-based platforms to discover new business insights. Building a machine learning model is an iterative process. In this ebook, we break down the process and describe how machine learning models are built. Explore notebooks and build or test machine learning algorithms. Try AutoML and see data science results. Build high-quality models faster and easier. Automated machine learning capabilities rapidly examine the data and recommend the optimal data features and best algorithms. Additionally, automated machine learning tunes the model and explains the model’s results.

Design and develop data-intensive projects with human-friendly, open-source Metaflow. Run, scale, and deploy them reliably on the fully managed Outerbounds platform. One platform for all your ML and data science projects. Access data securely from your existing data warehouses. Compute with a cluster optimized for scale and cost. 24/7 managed orchestration for production workflows. Use results to power any application. Give your data scientists superpowers, approved by your engineers. Outerbounds Platform allows data scientists to develop rapidly, experiment at scale, and deploy to production confidently. All within the outer bounds of policies and processes defined by your engineers, running on your cloud account, fully managed by us. Security is in our DNA, not at the perimeter. The platform adapts to your policies and compliance requirements through multiple layers of security. Centralized auth, a strict permission boundary, and granular task execution roles.

Deepnote is building the best data science notebook for teams. In the notebook, users can connect their data, explore, and analyze it with real-time collaboration and version control. Users can easily share project links with team collaborators, or with end-users to present polished assets. All of this is done through a powerful, browser-based UI that runs in the cloud. We built Deepnote because data scientists don't work alone. Features: - Sharing notebooks and projects via URL - Inviting others to view, comment and collaborate, with version control - Publishing notebooks with visualizations for presentations - Sharing datasets between projects - Set team permissions to decide who can edit vs view code - Full linux terminal access - Code completion - Automatic python package management - Importing from github - PostgreSQL DB connection

Neural Designer is a powerful software tool for developing and deploying machine learning models. It provides a user-friendly interface that allows users to build, train, and evaluate neural networks without requiring extensive programming knowledge. With a wide range of features and algorithms, Neural Designer simplifies the entire machine learning workflow, from data preprocessing to model optimization. In addition, it supports various data types, including numerical, categorical, and text, making it versatile for domains. Additionally, Neural Designer offers automatic model selection and hyperparameter optimization, enabling users to find the best model for their data with minimal effort. Finally, its intuitive visualizations and comprehensive reports facilitate interpreting and understanding the model's performance.

The biggest challenge to scaling AI-powered decision-making is unused data. IBM Cloud Pak® for Data is a unified platform that delivers a data fabric to connect and access siloed data on-premises or across multiple clouds without moving it. Simplify access to data by automatically discovering and curating it to deliver actionable knowledge assets to your users, while automating policy enforcement to safeguard use. Further accelerate insights with an integrated modern cloud data warehouse. Universally safeguard data usage with privacy and usage policy enforcement across all data. Use a modern, high-performance cloud data warehouse to achieve faster insights. Empower data scientists, developers and analysts with an integrated experience to build, deploy and manage trustworthy AI models on any cloud. Supercharge analytics with Netezza, a high-performance data warehouse.

Next generation cloud native AI powered Decision Automation platform to develop use case specific solutions. Incedo LighthouseTM harnesses the power of AI in a low code environment to deliver insights and action recommendations, every day, by leveraging the capabilities of Big Data at superfast speed. Incedo LighthouseTM enables you to increase revenue potential by optimizing customer experiences and delivering hyper-personalized recommendations. Our AI and ML driven models allow personalization across the customer lifecycle. Incedo LighthouseTM allows you to achieve lower costs by accelerating the loop of problem discovery, generation of insights and execution of targeted actions. The platform is powered by our ML driven metric monitoring and root cause analyses models. Incedo LighthouseTM monitors the quality of the high volumes of frequent data loads and leverages AI/ML to fix some of the quality issues, thereby improving trust in data.

Manage and secure the data lifecycle from the Edge to AI in any cloud or data center. Operates across all major public clouds and the private cloud with a public cloud experience everywhere. Integrates data management and analytic experiences across the data lifecycle for data anywhere. Delivers security, compliance, migration, and metadata management across all environments. Open source, open integrations, extensible, & open to multiple data stores and compute architectures. Deliver easier, faster, and safer self-service analytics experiences. Provide self-service access to integrated, multi-function analytics on centrally managed and secured business data while deploying a consistent experience anywhere—on premises or in hybrid and multi-cloud. Enjoy consistent data security, governance, lineage, and control, while deploying the powerful, easy-to-use cloud analytics experiences business users require and eliminating their need for shadow IT solutions.

PredictSense is an end-to-end Machine Learning platform powered by AutoML to create AI-powered analytical solutions. Fuel the new technological revolution of tomorrow by accelerating machine intelligence. AI is key to unlocking value from enterprise data investments. PredictSense enables businesses to monetize critical data infrastructure and technology investments by creating AI driven advanced analytical solutions rapidly. Empower data science and business teams with advanced capabilities to quickly build and deploy robust technology solutions at scale. Easily integrate AI into the current product ecosystem and fast track GTM for new AI solutions. Incur huge savings in cost, time and effort by building complex ML models in AutoML. PredictSense democratizes AI for every individual in the organization and creates a simple, user-friendly collaboration platform to seamlessly manage critical ML deployments.

Ours is the world’s first & only end-to-end platform for all your AI-powered innovation needs — right from data cleansing & structuring, to creating & deploying advanced data-science models, to infusing advanced analytics algorithms with built-in Recommendation AI, to deducing the outcomes with easy-to-deduce visualization dashboards, as well as Explainable AI to backtrack how the outcomes were derived, our no-code AI platform can do it all! Our platform offers a holistic, seamless data science experience. With key features like a robust Data Lakehouse, a unique AI Studio, a comprehensive AI Marketplace, and a world-class data-science support team (on a need basis), FutureAnalytica is geared to reduce your time, efforts & costs across your data-science & AI journey. Initiate discussions with the leadership, followed by a quick technology assessment in 1–3 days. Build ready-to-integrate AI solutions using FA's fully automated data science & AI platform in 10–18 days.

Accelerate the end-to-end machine learning lifecycle. Empower developers and data scientists with a wide range of productive experiences for building, training, and deploying machine learning models faster. Accelerate time to market and foster team collaboration with industry-leading MLOps—DevOps for machine learning. Innovate on a secure, trusted platform, designed for responsible ML. Productivity for all skill levels, with code-first and drag-and-drop designer, and automated machine learning. Robust MLOps capabilities that integrate with existing DevOps processes and help manage the complete ML lifecycle. Responsible ML capabilities – understand models with interpretability and fairness, protect data with differential privacy and confidential computing, and control the ML lifecycle with audit trials and datasheets. Best-in-class support for open-source frameworks and languages including MLflow, Kubeflow, ONNX, PyTorch, TensorFlow, Python, and R.

Alteryx is the launchpad for automation breakthroughs. Be it your personal growth, achieving transformative digital outcomes, or rapid innovation, the results are unparalleled. The unique innovation that converges analytics, data science and process automation into one easy-to-use platform, empowers everyone and every organization ​to make business-altering breakthroughs the new status quo.​

Bring data analysts, engineers, and scientists together. Enable self-service analytics and operationalize machine learning. Get results today and build for tomorrow. Dataiku DSS is the collaborative data science software platform for teams of data scientists, data analysts, and engineers to explore, prototype, build, and deliver their own data products more efficiently. Use notebooks (Python, R, Spark, Scala, Hive, etc.) or a customizable drag-and-drop visual interface at any step of the predictive dataflow prototyping process – from wrangling to analysis to modeling. Profile the data visually at every step of the analysis. Interactively explore and chart your data using 25+ built-in charts. Prepare, enrich, blend, and clean data using 80+ built-in functions. Leverage Machine Learning technologies (Scikit-Learn, MLlib, TensorFlow, Keras, etc.) in a visual UI. Build & optimize models in Python or R and integrate any external ML library through code APIs.

The only all-in-one data pipeline platform. Built ground-up for a cloud-first world, Gathr is the only platform to handle all your data integration and engineering needs - ingestion, ETL, ELT, CDC, streaming analytics, data preparation, machine learning, advanced analytics and more. With Gathr, anyone can build and deploy pipelines in minutes, irrespective of skill levels. Create Ingestion pipelines in minutes, not weeks. Ingest data from any source, deliver to any destination. Build applications quickly with a wizard-based approach. Replicate data in real-time using a templatized CDC app. Native integration for all sources and targets. Best-in-class capabilities with everything you need to succeed today and tomorrow. Choose between free, pay-per-use or customize as per your requirements.

Emly Labs is an AI framework designed to make AI accessible for users at all technical levels through a user-friendly platform. It offers AI project management with tools for guided workflows and automation for faster execution. The platform encourages team collaboration and innovation, provides no-code data preparation, and integrates external data for robust AI models. Emly AutoML automates data processing and model evaluation, reducing human input. It prioritizes transparency, with explainable AI features and robust auditing for compliance. Security measures include data isolation, role-based access, and secure integrations. Additionally, Emly's cost-effective infrastructure allows on-demand resource provisioning and policy management, enhancing experimentation and innovation while reducing costs and risks.

Unstructured data is the future of AI. Unlock this future now and build an ML/AI pipeline that scales all of your unstructured data in one place. Use better data to deliver better models, only with Graviti. Get to know the data platform that enables AI developers with management, query, and version control features that are designed for unstructured data. Quality data is no longer a pricey dream. Manage your metadata, annotation, and predictions in one place. Customize filters and visualize filtering results to get you straight to the data that best match your needs. Utilize a Git-like structure to manage data versions and collaborate with your teammates. Role-based access control and visualization of version differences allows your team to work together safely and flexibly. Automate your data pipeline with Graviti’s built-in marketplace and workflow builder. Level-up to fast model iterations with no more grinding.

Access, explore and prepare data while discovering new trends and patterns. SAS Visual Data Science helps you create and share smart visualizations and interactive reports through a single, self-service interface. It uses machine learning, text analytics and econometrics capabilities for better forecasting and optimization, plus it manages and registers SAS and open-source models within projects or as standalone models. Visualize and discover relevant relationships in your data. Create and share interactive reports and dashboards, and use self-service analytics to quickly assess probable outcomes for smarter, more data-driven decisions. Explore data and build or adjust predictive analytical models with this solution running in SAS® Viya®. Data scientists, statisticians, and analysts can collaborate and iteratively refine models for each segment or group to make decisions based on accurate insights.

DSVMs are Azure Virtual Machine images, pre-installed, configured and tested with several popular tools that are commonly used for data analytics, machine learning and AI training. Consistent setup across team, promote sharing and collaboration, Azure scale and management, Near-Zero Setup, full cloud-based desktop for data science. Quick, Low friction startup for one to many classroom scenarios and online courses. Ability to run analytics on all Azure hardware configurations with vertical and horizontal scaling. Pay only for what you use, when you use it. Readily available GPU clusters with Deep Learning tools already pre-configured. Examples, templates and sample notebooks built or tested by Microsoft are provided on the VMs to enable easy onboarding to the various tools and capabilities such as Neural Networks (PYTorch, Tensorflow, etc.), Data Wrangling, R, Python, Julia, and SQL Server.

The single development environment for the entire data science workflow. Natively analyze your data with a reduction in context switching between services. Data to training at scale. Build and train models 5X faster, compared to traditional notebooks. Scale-up model development with simple connectivity to Vertex AI services. Simplified access to data and in-notebook access to machine learning with BigQuery, Dataproc, Spark, and Vertex AI integration. Take advantage of the power of infinite computing with Vertex AI training for experimentation and prototyping, to go from data to training at scale. Using Vertex AI Workbench you can implement your training, and deployment workflows on Vertex AI from one place. A Jupyter-based fully managed, scalable, enterprise-ready compute infrastructure with security controls and user management capabilities. Explore data and train ML models with easy connections to Google Cloud's big data solutions.

Darwin is an automated machine learning product that enables your data science and business analytics teams to move more quickly from data to meaningful results. Darwin helps organizations scale the adoption of data science across teams, and the implementation of machine learning applications across operations, becoming data-driven enterprises.

The Xilinx’s AI development platform for AI inference on Xilinx hardware platforms consists of optimized IP, tools, libraries, models, and example designs. It is designed with high efficiency and ease-of-use in mind, unleashing the full potential of AI acceleration on Xilinx FPGA and ACAP. Supports mainstream frameworks and the latest models capable of diverse deep learning tasks. Provides a comprehensive set of pre-optimized models that are ready to deploy on Xilinx devices. You can find the closest model and start re-training for your applications! Provides a powerful open source quantizer that supports pruned and unpruned model quantization, calibration, and fine tuning. The AI profiler provides layer by layer analysis to help with bottlenecks. The AI library offers open source high-level C++ and Python APIs for maximum portability from edge to cloud. Efficient and scalable IP cores can be customized to meet your needs of many different applications.

Developing AI solutions requires an engineering approach that is resilient, open and repeatable to ensure necessary quality and agility is achieved. Until today these efforts are missing the foundation to address these challenges amid a sea of point tools and fast changing models and data. Collaborative developer platform for automating development and control of AI applications across multiple personas. Derive hyper-detailed customer profiles from enterprise data to predict behaviors in real-time and at scale. Generate AI-powered models designed to continuously learn and achieve clearly defined business outcomes. Enables organizations to explain and prove compliance with applicable rules and regulations. CognitiveScale's Cortex AI Platform addresses enterprise AI use cases through modular platform offerings. Our customers consume and leverage its capabilities as microservices within their enterprise AI initiatives.

Build, deploy, and operate Enterprise AI applications. The C3 AI® Suite uses a unique model-driven architecture to accelerate delivery and reduce the complexities of developing enterprise AI applications. The C3 AI model-driven architecture provides an “abstraction layer,” that allows developers to build enterprise AI applications by using conceptual models of all the elements an application requires, instead of writing lengthy code. This provides significant benefits: Use AI applications and models that optimize processes for every product, asset, customer, or transaction across all regions and businesses. Deploy AI applications and see results in 1-2 quarters – rapidly roll out additional applications and new capabilities. Unlock sustained value – hundreds of millions to billions of dollars per year – from reduced costs, increased revenue, and higher margins. Ensure systematic, enterprise-wide governance of AI with C3.ai’s unified platform that offers data lineage and governance.

TrueFoundry is a Cloud-native Machine Learning Training and Deployment PaaS on top of Kubernetes that enables Machine learning teams to train and Deploy models at the speed of Big Tech with 100% reliability and scalability - allowing them to save cost and release Models to production faster. We abstract out the Kubernetes for Data Scientists and enable them to operate in a way they are comfortable. It also allows teams to deploy and fine-tune large language models seamlessly with full security and cost optimization. TrueFoundry is open-ended, API Driven and integrates with the internal systems, deploys on a company's internal infrastructure and ensures complete Data Privacy and DevSecOps practices.

Machine learning uncovers hidden patterns and insights in enterprise data, generating new value for the business. Oracle Machine Learning accelerates the creation and deployment of machine learning models for data scientists using reduced data movement, AutoML technology, and simplified deployment. Increase data scientist and developer productivity and reduce their learning curve with familiar open source-based Apache Zeppelin notebook technology. Notebooks support SQL, PL/SQL, Python, and markdown interpreters for Oracle Autonomous Database so users can work with their language of choice when developing models. A no-code user interface supporting AutoML on Autonomous Database to improve both data scientist productivity and non-expert user access to powerful in-database algorithms for classification and regression. Data scientists gain integrated model deployment from the Oracle Machine Learning AutoML User Interface.

Manage and optimize models across the entire ML lifecycle, from experiment tracking to monitoring models in production. Achieve your goals faster with the platform built to meet the intense demands of enterprise teams deploying ML at scale. Supports your deployment strategy whether it’s private cloud, on-premise servers, or hybrid. Add two lines of code to your notebook or script and start tracking your experiments. Works wherever you run your code, with any machine learning library, and for any machine learning task. Easily compare experiments—code, hyperparameters, metrics, predictions, dependencies, system metrics, and more—to understand differences in model performance. Monitor your models during every step from training to production. Get alerts when something is amiss, and debug your models to address the issue. Increase productivity, collaboration, and visibility across all teams and stakeholders.

H2O.ai is the open source leader in AI and machine learning with a mission to democratize AI for everyone. Our industry-leading enterprise-ready platforms are used by hundreds of thousands of data scientists in over 20,000 organizations globally. We empower every company to be an AI company in financial services, insurance, healthcare, telco, retail, pharmaceutical, and marketing and delivering real value and transforming businesses today.

The open-source ML observability platform. Evaluate, test, and monitor ML models from validation to production. From tabular data to NLP and LLM. Built for data scientists and ML engineers. All you need to reliably run ML systems in production. Start with simple ad hoc checks. Scale to the complete monitoring platform. All within one tool, with consistent API and metrics. Useful, beautiful, and shareable. Get a comprehensive view of data and ML model quality to explore and debug. Takes a minute to start. Test before you ship, validate in production and run checks at every model update. Skip the manual setup by generating test conditions from a reference dataset. Monitor every aspect of your data, models, and test results. Proactively catch and resolve production model issues, ensure optimal performance, and continuously improve it.

Democratize, collaborate, and operationalize, machine learning across your organization. Data science is a team sport. Data scientists, citizen data scientists, data engineers, business users, and developers need flexible and extensible tools that promote collaboration, automation, and reuse of analytic workflows. But algorithms are only one piece of the advanced analytic puzzle. To deliver predictive insights, companies need to increase focus on the deployment, management, and monitoring of analytic models. Smart businesses rely on platforms that support the end-to-end analytics lifecycle while providing enterprise security and governance. TIBCO® Data Science software helps organizations innovate and solve complex problems faster to ensure predictive findings quickly turn into optimal outcomes. TIBCO Data Science allows organizations to expand data science deployments across the organization by providing flexible authoring and deployment capabilities.

Predictive Modeling with Machine Learning and Explainable AI. FICO® Analytics Workbench™ is an integrated suite of state-of-the-art analytic authoring tools that empowers companies to improve business decisions across the customer lifecycle. With it, data scientists can build superior decisioning capabilities using a wide range of predictive data modeling tools and algorithms, including the latest machine learning (ML) and explainable artificial intelligence (xAI) approaches. We enhance the best of open source data science and machine learning with innovative intellectual property from FICO to deliver world-class analytic capabilities to discover, combine, and operationalize predictive signals in data. Analytics Workbench is built on the leading FICO® Platform to allow new predictive models and strategies to be deployed into production with ease.

SAS® Viya® data science offerings provide a comprehensive, scalable analytics environment that's quick and easy to deploy, enabling you to meet diverse business needs. Automatically generated insights enable you to identify the most common variables across all models, the most important variables selected across models and assessment results for all models. Natural language generation capabilities are used to create project summaries written in plain language, enabling you to easily interpret reports. Analytics team members can add project notes to the insights report to facilitate communication and collaboration among team members. SAS lets you embed open source code within an analysis and call open source algorithms seamlessly within its environment. This facilitates collaboration across your organization because users can program in their language of choice. You can also take advantage of SAS Deep Learning with Python (DLPy), our open-source package on GitHub.