Alternatives to Solvuu

One source of truth for R packages and Python packages RStudio is the preferred professional data science solution for every group. A Python and R integrated development environment with syntax-highlighting editor, console, and code execution. It also includes tools for workspace management, history, plotting, and plotting. You can publish and distribute data products throughout your organization. One-button deployment of Shiny applications and R Markdown reports, Jupyter Notebooks, etc. To increase reproducibility and reduce the time spent installing and troubleshooting R packages, you can control, organize, and manage your use of them. RStudio is committed to sustainable investment in open-source and free software for data science. RStudio has been certified as a B Corporation. This means that our open-source mission has been codified in our charter. Our professional software products are enterprise-ready and provide a modular platform that allows teams to adopt open-source data sciences at scale.

IBM® SPSS® Statistics software is used by a variety of customers to solve industry-specific business issues to drive quality decision-making. The IBM® SPSS® software platform offers advanced statistical analysis, a vast library of machine learning algorithms, text analysis, open-source extensibility, integration with big data and seamless deployment into applications. Its ease of use, flexibility and scalability make SPSS accessible to users of all skill levels. What’s more, it’s suitable for projects of all sizes and levels of complexity, and can help you find new opportunities, improve efficiency and minimize risk.

SAS Visual Statistics allows multiple users to interactively explore data and then create and refine predictive models. Your statisticians and data scientists can use the most appropriate analytical modeling techniques to analyze your observations at a fine level. What will you get? The result? You can quickly build and refine models to target specific segments or groups, and run multiple scenarios simultaneously. To get better results, you can ask more "what-if" questions. You can also use an automatically generated score code to put your results into practice. Multiple users can interact with data visually. They can add, change, or remove outliers. You can instantly see how changes affect the predictive power of your model and make adjustments quickly. Data science teams have the freedom to work in the language they prefer, so they can make the most of their talents. SAS Visual Statistics combines all analytical assets.

Easy extract, transform, load (ETL), data for data science or analytics. Code-free data flows can be created into data lakes or data marts. Oracle's extensive portfolio of integration solutions. The intuitive user interface allows you to set up integration parameters and automate data mapping from sources and targets. To shape your data, you can use one of the many out-of-the box operators such as a join or aggregate. You can centrally manage your processes and use parameters to override certain configuration values at runtime. Users can view and interact with their data to validate their processes. You can increase productivity and fine-tune data flow on the fly without waiting for executions to complete. Reduce maintenance complexity and avoid broken integration flows as data schemas change.

NVIDIA Merlin enables data scientists, machine-learning engineers, and researchers, to build high-performance recommenders at scale. Merlin includes libraries, methods and tools to streamline the building and deployment of recommenders. These include addressing common challenges in preprocessing, feature engineering and training. Merlin components and capabilities have been optimized to support retrieval, scoring, filtering and ordering of hundreds terabytes data. All of this is accessible via easy-to-use interfaces. Merlin can help you make better predictions, increase click-through rates and deploy faster to production. NVIDIA Merlin is part of NVIDIA AI and advances our commitment to support innovative practitioners doing their best. NVIDIA Merlin is designed as an end-toend solution that can be integrated into existing recommender workflows utilizing data science and machine learning.

Machine learning can be accelerated from research to production using a consistent experience that is built for your traditional platform. Cloudera Data Science Workbench, (CDSW), offers a self-service experience that data scientists will love. It allows you to access Python, R, Scala, and more directly from your web browser. You can download and test the latest frameworks and libraries in project environments that look exactly like your laptop. Cloudera Data Science Workbench allows you to connect to CDH and HDP as well as to the systems that your data science teams depend on for analysis. Cloudera Data Science Workbench allows data scientists to manage their own analytics pipelines. It includes built-in monitoring, scheduling, email alerting, and monitoring. Rapidly create and prototype machine learning projects, and then easily deploy them to production.

An end-to-end solution gives you all the tools your data science team needs to scale your machine learning development, from research to production. cnvrg.io, the world's leading data science platform for MLOps (model management) is a leader in creating cutting-edge machine-learning development solutions that allow you to build high-impact models in half the time. In a collaborative and clear machine learning management environment, bridge science and engineering teams. Use interactive workspaces, dashboards and model repositories to communicate and reproduce results. You should be less concerned about technical complexity and more focused on creating high-impact ML models. The Cnvrg.io container based infrastructure simplifies engineering heavy tasks such as tracking, monitoring and configuration, compute resource management, server infrastructure, feature extraction, model deployment, and serving infrastructure.

Analytically driven decision flows can be created, embedded and managed at scale in batch or real-time. SAS Data Science Programming allows data scientists who prefer to work only in programmatic mode to access SAS analytical capabilities at every stage of the analytics lifecycle, including data discovery and deployment. Visualize and discover relationships in your data. You can create and share interactive dashboards and reports, and use self service analytics to quickly assess possible outcomes to make data-driven, smarter decisions. This solution runs in SAS®, Viya®. It allows you to explore data and create or adjust predictive analytical models. Analysts, statisticians, data scientists, and analysts can work together to refine and refine models for each group or segment, allowing them to make informed decisions. A comprehensive visual interface allows you to solve complex analytical problems. It handles all aspects of the analytics lifecycle.

Access, explore, and prepare data while discovering new patterns and trends. SAS Visual Data Science allows you to create and share interactive visualizations and reports using a single interface. It uses machine learning, text analysis, and econometrics to improve forecasting and optimization. Additionally, it registers SAS and open source models within projects and as standalone models. Visualize your data and find relevant relationships. You can create and share interactive dashboards and reports, and use self service analytics to quickly assess possible outcomes for better, data-driven decisions. This solution runs in SAS®, Viya®. It allows you to explore data and create or adjust predictive analytical models. Analysts, statisticians, data scientists, and analysts can work together to refine and refine models for each group or segment, allowing them to make informed decisions.

Spend less time prepping your data and more time analysing it. You can create better-looking and more accurate reports by centralizing all data gathering, analytics, and data science into one interface that is accessible to everyone within the organization. No matter where your data is located, import it all. Rational BI provides all the tools you need to create scheduled reports from Excel files, cross-reference data between Excel files and databases, or transform your data into SQL queryable database tables. Find the hidden signals in your data and make it accessible immediately to your competitors. Business intelligence can help you increase your analytics capabilities and make it easier to find the most up-to-date data. It also makes it easy for data scientists and casual users to analyze it.

SAS®, Viya®, data science offerings offer a comprehensive, scalable analytical environment that is quick and easy to use, allowing you to meet diverse business requirements. Automatically generated insights allow you to identify the most commonly used variables across all models, the most significant variables selected across models, and assess results for all models. Natural language generation capabilities allow you to create project summaries in plain language. This makes it easy to interpret reports. Analytics team members can add project notes and comments to the insights report to facilitate communication between team members. SAS allows you to embed open source code into an analysis and call open-source algorithms seamlessly within its environment. This allows for collaboration within your organization as users can program in the language they prefer. SAS Deep Learning with Python (DLPy) is also available on GitHub.

Integrate analytics into real time interactions and event-based capabilities. SAS Visual Data Science Decisioning offers robust data management, visualization, advanced analysis, and model management. It supports decision making by creating, embedding, and governing analytically driven decision flows at scale in batch or real-time. It also provides analytics and stream-based decisions to help you uncover insights. A comprehensive visual interface allows you to solve complex analytical problems. It handles all aspects of the analytics lifecycle. SAS Visual Data Mining and Machine Learning runs in SAS®, Viya®. It combines data wrangling and exploration with feature engineering and modern statistical, data mining and machine learning techniques in one, scalable, in-memory processing environment. This web application is a development tool that you can access via your browser.

Data scientists are able to build, improve, or operate end-to–end workflows independently. This allows them to deliver data science projects that are successful. Metaflow can be used with your favorite data science libraries such as SciKit Learn or Tensorflow. You can write your models in idiomatic Python codes with little to no learning. Metaflow also supports R language. Metaflow allows you to design your workflow, scale it, and then deploy it to production. It automatically tracks and versions all your data and experiments. It allows you to easily inspect the results in notebooks. Metaflow comes pre-installed with the tutorials so it's easy to get started. Metaflow allows you to make duplicates of all tutorials in your current directory by using the command line interface.

Wolfram Data Science Platform allows you to use structured and unstructured data sources, as well as real-time or static data. Alpha to convert unstructured data to structured form, with automated or guided destructuring and disambiguation. Wolfram Data Science Platform uses industry-specific database connection technology to transform database content into its highly flexible internal symbol representation. Wolfram Data Science Platform is capable of reading hundreds of data formats and converting them. Wolfram Data Science Platform can work with images, text and networks as well as sounds, GIS data, and many other formats. Wolfram Data Science Platform seamlessly handles both SQL-style data and NoSQL data thanks to the Wolfram Language's breakthrough symbolic data representation. Wolfram Data Science Platform automatically creates an interactive report using algorithms that identify interesting features in your data to highlight and visualize.

Datalore is a platform for collaborative data science and analytics that aims to improve the entire analytics workflow and make working with data more enjoyable for both data scientists as well as data-savvy business teams. Datalore is a collaborative platform that focuses on data teams workflow. It offers technical-savvy business users the opportunity to work with data teams using no-code and low-code, as well as the power of Jupyter Notebooks. Datalore allows business users to perform analytic self-service. They can work with data using SQL or no-code cells, create reports, and dive deep into data. It allows core data teams to focus on simpler tasks. Datalore allows data scientists and analysts to share their results with ML Engineers. You can share your code with ML Engineers on powerful CPUs and GPUs, and you can collaborate with your colleagues in real time.

A fully-featured machine learning platform empowers enterprises to conduct real data science at scale and speed. You can spend less time managing infrastructure and tools so that you can concentrate on building machine learning applications to propel your business forward. Anaconda Enterprise removes the hassle from ML operations and puts open-source innovation at the fingertips. It provides the foundation for serious machine learning and data science production without locking you into any specific models, templates, workflows, or models. AE allows data scientists and software developers to work together to create, test, debug and deploy models using their preferred languages. AE gives developers and data scientists access to both notebooks as well as IDEs, allowing them to work more efficiently together. They can also choose between preconfigured projects and example projects. AE projects can be easily moved from one environment to the next by being automatically packaged.

Deepnote is building the best data science notebook for teams. Connect your data, explore and analyze it within the notebook with real-time collaboration and versioning. Share links to your projects with other analysts and data scientists on your team, or present your polished, published notebooks to end users and stakeholders. All of this is done through a powerful, browser-based UI that runs in the cloud.

With open-source Metaflow, you can design and develop data-intensive projects. You can scale them up and deploy them on the fully managed Outerbounds platform. All your data science and ML projects can be managed from one platform. Access data securely from existing data warehouses. A cluster that is optimized for cost and scale can be used to compute. 24/7 managed orchestration of production workflows. Results can be used to power any application. Your engineers will give your data scientists superpowers. Outerbounds Platform enables data scientists to quickly develop, experiment at scale, then deploy to production with confidence. All within the boundaries of your engineers' policies and processes, all running on your cloud account, fully supported by us. Security is part of our DNA, not at its perimeter. Through multiple layers of security, the platform adapts to your policies. Centralized authentication, a strict permission limit, and granular task execution role.

HyperCube is the platform that data scientists use to quickly discover hidden insights, no matter what your business needs. Use your business data to make an impact. Unlock understanding, uncover untapped opportunities, make predictions, and avoid risk before they happen. HyperCube turns huge amounts of data into actionable insights. HyperCube is for you, whether you are a beginner or an expert in machine learning. It is the data science Swiss Army knife. It combines proprietary and open-source code to deliver a wide variety of data analysis features right out of the box. Or, it can be customized for your business. We are constantly improving our technology to deliver the best possible results. Choose from apps, DaaS (data-as-a service) or vertical market solutions.

IBM SPSS Modeler, a leading visual data-science and machine-learning (ML) solution, is designed to help enterprises accelerate their time to value through the automation of operational tasks by data scientists. It is used by organizations around the world for data preparation, discovery, predictive analytics and model management and deployment. ML is also used to monetize data assets. IBM SPSS Modeler transforms data in the best possible format for accurate predictive modeling. You can now analyze data in just a few clicks, identify fixes, screen fields out and derive new characteristics. IBM SPSS Modeler uses its powerful graphics engine to help you bring your insights to life. The smart chart recommender will select the best chart from dozens of options to share your insights.

Installed with one click, it's a desktop application that includes Jupyter Notebook. It has interactive code snippets, an AI assistant and a coding speed-up tool. Over 100 interactive code recipes have been handcrafted by us and can be used in Data Science projects. Code recipes detect the packages that are available in the current environment. Install modules with a single click. You can create variables and interact with them in your Python session. Interactive recipes speed-up your work. AI Assistant can access your current Python session and variables. It is smarter because it has a broad context. Our AI Assistant is designed to solve data issues using Python programming language. It can assist you with plots and data loading, data wrangling and Machine Learning. Click the Fix button to use AI to quickly fix code issues. The AI assistant will analyze and suggest a solution to the error.

Einblick is the fastest and most collaborative method to analyze data, make predictions, and then deploy data apps. Our canvases dramatically change the data science workflows. They make it easier to clean, manipulate, and explore data in a new interface. Our platform is the only one that allows you to collaborate with your entire team in real-time. Let's make decision-making a team activity. Don't waste your time tuning models manually. AutoML's goal is to help you make clear predictions and identify key drivers quickly. Einblick combines common analytics functionality into simple-to-use operators that allow you to abstract repetitive tasks and get answers faster. Connect your data source to Snowflake, S3 buckets, or CSV files and you'll be able to get answers in minutes. You can create a list of customers that have been churned or are currently churned, and share everything you know about them. Find out the key factors that caused churn and how at-risk each customer is.

Accelerate and simplify IoT data extraction, create AI for the shop floor, and visualize KPIs. Manage decentralized, compact data pods. Each data pod is completely autonomous and includes infrastructure for powerful analytics. Flexible storage capacity allows you to create multiple pods with different sizes. In a seamless data journey, you can collect, analyze, visualize, and visualize data. You can collect raw data from multiple sources, such as IoT routers or the web. Instantly generate reports and create custom infographics from your browser. Combine the power of VS Code, Observable and TablePlus to create interactive data science workbooks. You can see the current and past processes in real time and automate package loads up to reporting.

Easily extract, transform, manage & process CAD data, FE data, CFD and test results. Create automatic data pipelines to support machine learning, deep learning, and ROM. Data science barriers can be removed without coding. Key Ward's platform, the first engineering no-code end-to-end solution, redefines how engineers work with their data. Our software allows engineers to handle multi-source data with ease, extract direct value using our built-in advanced analytical tools, and build custom machine and deep learning model with just a few clicks. Automatically centralize, update and extract your multi-source data, then sort, clean and prepare it for analysis, machine and/or deep learning. Use our advanced analytics tools to correlate, identify patterns, and find dependencies in your experimental & simulator data.

Vizly is a data scientist powered by AI that lets you chat, visualize insights and perform analysis. Create interactive data visualizations for better understanding of your data. Chat with your data to uncover actionable insights. Perform complex analyses and generate predictive insights. Vizly, an AI-powered data scientist, lets you chat with data, visualize insights and perform analysis. Our users can upload their data to get insights instantly. Sign up for Vizly to immediately begin asking questions and creating visualizations using your data. Vizly was built for companies and can be used right away. Register your interest in our Enterprise offering for additional hosting, data source, and security options. Vizly currently supports CSV and Excel file formats. All users are entitled to send 10 messages per month at no cost. You can upgrade your plan after reaching the limit on your profile page.

Stata is a comprehensive, integrated software package that can handle all aspects of data science: data manipulation, visualization and statistics, as well as automated reporting. Stata is quick and accurate. The extensive graphical interface makes it easy to use, but is also fully programable. Stata's menus, dialogs and buttons give you the best of both worlds. All Stata's data management, statistical, and graphical features are easy to access by dragging and dropping or point-and-click. To quickly execute commands, you can use Stata's intuitive command syntax. You can log all actions and results, regardless of whether you use the menus or dialogs. This will ensure reproducibility and integrity in your analysis. Stata also offers complete command-line programming and programming capabilities, including a full matrix language. All the commands that Stata ships with are available to you, whether you want to create new Stata commands or script your analysis.

All work can be synced, searched and managed across your data science team. Zepl's powerful search allows you to discover and reuse models, code, and other data. Zepl's enterprise collaboration platform allows you to query data from Snowflake or Athena and then build your models in Python. For enhanced interactions with your data, use dynamic forms and pivoting. Zepl creates new containers every time you open your notebook. This ensures that you have the same image each time your models are run. You can invite your team members to join you in a shared space, and they will be able to work together in real-time. Or they can simply leave comments on a notebook. You can share your work with fine-grained access controls. You can allow others to read, edit, run, and share your work. This will facilitate collaboration and distribution. All notebooks can be saved and versioned automatically. An easy-to-use interface allows you to name, manage, roll back, and roll back all versions. You can also export seamlessly into Github.

Powerful computing at your fingertips. Parallel computing and innovative algorithms are available. What are you waiting for?! This tool is designed to empower data scientists in the business. You can get the fastest computing through an all-inclusive platform that covers time-series. Shapelets offers analytical features such as forecasting, clustering and motif discovery, discords, and causality. To make Big Data analysis more efficient, you can run, extend, and integrate your own algorithms in the Shapelets platform. Shapelets can be integrated seamlessly with any data storage and collection solution. It can also be integrated with MS Office and any other visualization software to simplify and share your insights without needing any technical knowledge. Interactive visualizations are possible because our UI integrates with the server. Our modern interface allows you to make the most out of your metadata and present it in the various visual graphs available. Shapelets allows users in the oil, gas, or energy industry to analyze operational data in real-time.

To quickly develop models, streamline the data mining process. Learn the key relationships. Find the most important patterns. Your data miners and statisticians will be able to significantly reduce the time it takes to create models. A self-documenting interactive process flow diagram environment maps the entire data mining process for the best results. It also has more predictive modeling techniques that any commercial data mining program. Why not choose the best? SAS Rapid Predictive Modeller is available for business users and subject-matter specialists with limited statistical skills. A simple-to-use GUI guides them through the data mining process. Analytics results are presented in simple-to-understand charts that provide insights necessary for better decision-making. Use industry-specific methods and innovative algorithms to create models that are more efficient. Visual assessment and validation metrics are used to verify results.

Streamlit. The fastest way to create and share data apps. In minutes, turn data scripts into sharable Web apps All in Python. All this for free. No need for front-end experience. Streamlit combines three simple concepts. Use Python scripting. Our API is simple and allows you to create an app in just a few lines of code. You can then see the app update automatically as you save your source file. You can also use interaction. Declaring a variable is the same thing as adding a widget. You don't need to create a backend, define routes or handle HTTP requests. You can deploy your app instantly. Streamlit's platform for sharing allows you to easily share, manage and collaborate on your apps. A framework that allows you to create powerful apps. Face-GAN explorer. App that generates faces matching selected attributes using Shaobo Guan’s TL-GAN project, TensorFlow and NVIDIA’s PG-GAN. Real time object detection. A browser that displays images from the Udacity self driving-car dataset.

Combine Data Science, Business Intelligence and Data Management Capabilities into One Integrated, Self-Serve Platform. Analance is an end-to-end platform with robust and salable features that combines Data Science and Advanced Analytics, Business Intelligence and Data Management into a single integrated platform. It provides core analytical processing power to ensure that data insights are easily accessible to all, performance remains consistent over time, and business objectives can be met within a single platform. Analance focuses on making quality data into accurate predictions. It provides both citizen data scientists and data scientists with pre-built algorithms as well as an environment for custom programming. Company - Overview Ducen IT provides advanced analytics, business intelligence, and data management to Fortune 1000 companies through its unique data science platform Analance.

The Domino Enterprise MLOps 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. By automating time-consuming and tedious DevOps tasks, data scientists can focus on the tasks at hand. 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 has a powerful reproducibility engine, search and knowledge management, and integrated project management. Teams can easily find, reuse, reproduce, and build on any data science work to amplify innovation.

ZinkML is an open-source data science platform that does not require any coding. It was designed to help organizations leverage data more effectively. Its visual and intuitive interface eliminates the need for extensive programming expertise, making data sciences accessible to a wider range of users. ZinkML streamlines data science from data ingestion, model building, deployment and monitoring. Users can drag and drop components to create complex pipelines, explore the data visually, or build predictive models, all without writing a line of code. The platform offers automated model selection, feature engineering and hyperparameter optimization, which accelerates the model development process. ZinkML also offers robust collaboration features that allow teams to work seamlessly together on data science projects. By democratizing the data science, we empower businesses to get maximum value out of their data and make better decisions.

All enterprise's AI/ML efforts can have a consistent and positive impact. Data scientists deserve a solution that makes their experiments reproducible, each asset discoverable, and simplifies knowledge transfer. Managers deserve a dedicated data science solution. To automate reporting, secure knowledge, and simplify reviews and other processes. Vectice's mission is to revolutionize how data science teams collaborate and work together. All organizations should see consistent and positive AI/ML impacts. Vectice is the first automated knowledge system that is data science-aware, actionable, and compatible with the tools used by data scientists. Vectice automatically captures all assets created by AI/ML teams, such as data, code, notebooks and models, or runs. It then automatically generates documentation, from business requirements to production deployments.

DotData allows your business to concentrate on the results of your AI/ML applications and not the hassles of the data science process. Automate full-cycle AI & ML pipeline deployment in minutes. Continuous deployment allows you to update your data in real-time. Feature engineering automation reduces the time it takes to complete data science projects. Data science automation automates the discovery of unknowns in your business. Data science automation is a labor-intensive and cumbersome process that uses data science to create and deploy machine learning and AI models. Automate repetitive and time-consuming tasks that are the banes of data science work. This will reduce the development times for AI from months to days.

Two complementary tools, one enterprise-grade platform. Open source KNIME Analytics Platform to create data science. Commercial KNIME Server to produce data science. KNIME Analytics Platform is an open-source software that creates data science. KNIME is intuitive, open, and constantly integrating new developments. It makes data science and designing data science workflows as easy as possible. KNIME Server Enterprise Software is used to facilitate team-based collaboration, automation, and management of data science workflows, as well as the deployment and management of analytical applications and services. Non-experts have access to KNIME WebPortal and REST APIs. Extensions for KNIME Analytics Platform allow you to do more with your data. Some are created and maintained by KNIME, while others are contributed by the community or our trusted partners. Integrations are also available with many open-source projects.

Google Colab is a cloud-based Jupyter Notebook environment that allows users to write and execute Python code without any setup required. It provides access to powerful computing resources, including GPUs and TPUs, making it an excellent tool for machine learning, data analysis, and academic research. Colab is designed for collaborative work, enabling users to share notebooks with others, track changes, and easily integrate with Google Drive for file storage. It is particularly beneficial for both beginners and professionals seeking a free, interactive platform for experimenting with code and data. With Colab notebooks, you can integrate executable code with rich text, images, LaTeX, HTML, and other elements in a single document. All notebooks you create are saved to your Google Drive. Sharing with colleagues or friends is easy, allowing them to comment or edit your work. Additionally, Colab now provides a Data Science Agent that automates the entire analysis process, from data understanding to delivering insights in a functional notebook. (Note: Sequences are shortened, and results are for illustration. The Data Science Agent may occasionally make errors.)

Darwin is an automated machine-learning product that allows your data science and business analysis teams to quickly move from data to meaningful results. Darwin assists organizations in scaling the adoption of data science across their teams and the implementation machine learning applications across operations to become data-driven enterprises.

Our platform is the only one that offers an end-to–end platform for AI-powered innovation. It can handle everything from data cleansing and structuring to creating and deploying advanced data-science models to infusing advanced analytics algorithms, to infusing Recommendation AI, to deducing outcomes with simple-to-deduce visualization dashboards as well as Explainable AI to track how the outcomes were calculated. Our platform provides a seamless, holistic data science experience. FutureAnalytica offers key features such as a robust Data Lakehouse and an AI Studio. There is also a comprehensive AI Marketplace. You can also get support from a world-class team of data-science experts (on a case-by-case basis). FutureAnalytica will help you save time, effort, and money on your data-science and AI journey. Start discussions with the leadership and then a quick technology assessment within 1-3 days. In 10-18 days, you can create ready-to-integrate AI solutions with FA's fully-automated data science & AI platform.

Dataiku provides a powerful AI platform that helps organizations harness the potential of data science and machine learning by enabling teams to collaborate on AI-driven projects. With a flexible user interface that supports both no-code and code-based workflows, Dataiku allows users to streamline data preparation, build models using AutoML, and deploy solutions across diverse environments. The platform supports advanced capabilities like generative AI and AI governance, making it suitable for enterprises seeking scalable and secure AI solutions across various business functions.

Predictive modeling with Machine Learning and Explainable Ai. FICO®, Analytics Workbench™, is a comprehensive suite of state-of the-art analytic authoring software that empowers companies to make better business decisions throughout the customer lifecycle. Data scientists can use it to build superior decisioning abilities using a variety of predictive data modeling tools, including the most recent machine learning (ML), and explainable AI (xAI) methods. FICO's innovative intellectual property enables us to combine the best of open-source data science and machine learning to provide world-class analytical capabilities to find, combine, and operationalize data predictive signals. Analytics Workbench is built upon the FICO®, leading platform that allows for new predictive models and strategies to easily be put into production.

Accelerate scientific discovery, empower your R&D team and use harmonized data in cloud to accelerate your R&D. The Tetra R&D Data Cloud is the only cloud-native data platform for global pharmaceutical companies. It combines the power of the largest Life Sciences integrations network and deep domain knowledge to provide a future-proof solution to harness the power of your most important asset, R&D data. The cloud covers the entire life-cycle of your R&D data: from acquisition, harmonization, engineering, downstream analysis, and native support for state–of-the–art data science tools. Pre-built integrations allow for easy connection to instruments, informatics and analytics applications, ELN/LIMSs, CRO/CDMOs, and other vendors. Data acquisition, management, harmonization, integration/engineering and data science enablement in one single platform.

We create, manage, and operate predictive software services that are based on machine learning and data science. Software service for large ecommerce businesses and retail chains that uses machine learning to optimize stock distribution between warehouses and retail stores. A personalized product recommendation tool for ecommerce websites that uses real-time Bayes nets in order to show relevant products to e-shop customers. Software service that automatically predicts product price movements in order to increase profit. It uses statistical price and demand elastic models. API to calculate optimal paths for batch picking optimization in a retailer’s warehouse. This API is built using shortest path graph algorithms.

The RAPIDS software library, which is built on CUDAX AI, allows you to run end-to-end data science pipelines and analytics entirely on GPUs. It uses NVIDIA®, CUDA®, primitives for low level compute optimization. However, it exposes GPU parallelism through Python interfaces and high-bandwidth memories speed through user-friendly Python interfaces. RAPIDS also focuses its attention on data preparation tasks that are common for data science and analytics. This includes a familiar DataFrame API, which integrates with a variety machine learning algorithms for pipeline accelerations without having to pay serialization fees. RAPIDS supports multi-node, multiple-GPU deployments. This allows for greatly accelerated processing and training with larger datasets. You can accelerate your Python data science toolchain by making minimal code changes and learning no new tools. Machine learning models can be improved by being more accurate and deploying them faster.

Bitfount provides a platform for distributed data sciences. We enable deep data collaborations that do not require data sharing. Distributed data science connects algorithms to data and not the other way around. In minutes, you can set up a federated privacy protecting analytics and machine learning network. This will allow your team to focus on innovation and insights instead of bureaucracy. Although your data team is equipped with the skills to solve your most difficult problems and innovating, they are hindered by data access barriers. Are you having trouble accessing your data? Are compliance processes taking too much time? Bitfount offers a better way for data experts to be unleashed. Connect siloed or multi-cloud data sources while protecting privacy and commercial sensitivity. No expensive, time-consuming data lift-and-shift. Useage-based access control to ensure that teams only do the analysis you need, with the data you want. Transfer access control management to the teams that have the data.

The traditional system of bespoke review of data is not keeping pace with the increasing volume and speed of data. Cornerstone AI has created a self-learning AI platform that automatically creates smarter data rules to organize and clean up your data. This will allow you to access better analytical datasets quicker. Your team is spending too much time and effort cleaning and preparing clinical data. Our platform supports clinical trial, EHR, registry and digital health. Our platform scans every table and data point to determine structure and validity. This allows us to organize your tables and correct any errors. A quick data quality report that highlights the most problematic features in your data. Automated or UI based correction of these errors, API access for connecting directly to your data pipeline, as well as an audit trail for all. We don't keep, aggregate, nor resell your data. Your data is yours, and it is used only for you.

A new decision intelligence system that puts AI in the hands commercial leaders to drive great decisions. Peak has designed CODI, our Connected Intelligence system to be a layer of intelligence between your systems. This allows you to unleash the power of your data, allowing you to make better decisions. CODI allows you to deploy AI solutions quickly and harness the full potential of your data with its unique full-stack capabilities. It gives data science and engineering teams full control over every aspect of building and deploying AI systems, quickly and efficiently. CODI allows AI projects to move beyond being experiments and become fully-deployed solutions with real world value and results. CODI, which is built on enterprise-grade infrastructure allows for data to be handled at scale and seamlessly integrates with existing tech stacks. Combine data from different departments to get more insight.

Brilent is a data-science tech company that develops a SaaS solution for talent seekers to quickly and effectively find the right talent to hire. This intelligent technology is simple, which is the best part. There are no tricks. It uses the components that recruiters find most relevant. The core elements of the Brilent engine include three simple elements: job requirements, candidate profile, and our unique repository market data. The fun part is next. Our system collects all relevant data from job requirements and candidate profiles. We use hundreds of variables from the market data and familiar elements in recruiting to make predictions about whether a candidate will be a good match for a job. This is a lot of data crunching done in seconds. Recruiters can then rank candidates according to their specifications.

To identify the best actions, you need to build and solve complex optimization models. IBM®, ILOG®, CPLEX®, Optimization Studio uses decision optimization technology. It optimizes your business decisions, creates and deploys optimization models quickly, and creates real-world applications that can significantly increase business outcomes. How does it work? How? It combines a fully-featured integrated development environment that supports Optimization Programming Language, (OPL), and the high-performance CPLEX/CP Optimizer solvers. It's data science for your decisions. IBM Decision Optimization is also available in Cloud Pak for Data. This allows you to combine optimization and machine-learning within a unified environment, IBM Watson® Studio that enables AI infused optimization modeling capabilities.

Unutilized data is the biggest obstacle to scaling AI-powered decision making. IBM Cloud Pak®, for Data is a unified platform that provides a data fabric to connect, access and move siloed data across multiple clouds or on premises. Automate policy enforcement and discovery to simplify access to data. A modern cloud data warehouse integrates to accelerate insights. All data can be protected with privacy and usage policy enforcement. To gain faster insights, use a modern, high-performance cloud storage data warehouse. Data scientists, analysts, and developers can use a single platform to create, deploy, and manage trusted AI models in any cloud.