Alternatives to Vectice
Compare Vectice alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Vectice in 2026. Compare features, ratings, user reviews, pricing, and more from Vectice competitors and alternatives in order to make an informed decision for your business.
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Teradata VantageCloud
Teradata
Teradata VantageCloud: The complete cloud analytics and data platform for AI. Teradata VantageCloud is an enterprise-grade, cloud-native data and analytics platform that unifies data management, advanced analytics, and AI/ML capabilities in a single environment. Designed for scalability and flexibility, VantageCloud supports multi-cloud and hybrid deployments, enabling organizations to manage structured and semi-structured data across AWS, Azure, Google Cloud, and on-premises systems. It offers full ANSI SQL support, integrates with open-source tools like Python and R, and provides built-in governance for secure, trusted AI. VantageCloud empowers users to run complex queries, build data pipelines, and operationalize machine learning models—all while maintaining interoperability with modern data ecosystems. -
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Posit
Posit
Posit builds tools that help data scientists work more efficiently, collaborate seamlessly, and share insights securely across their organizations. Its Positron code editor provides the speed of an interactive console combined with the power to build, debug, and deploy data-science workflows in Python and R. Posit’s platform enables teams to scale open-source data science, offering enterprise-ready capabilities for publishing, sharing, and operationalizing applications. Companies rely on Posit’s secure infrastructure to host Shiny apps, dashboards, APIs, and analytical reports with confidence. Whether using open-source packages or cloud-based solutions, Posit supports reproducible, high-quality work at every stage of the data lifecycle. Trusted by millions of users—and more than half of the Fortune 100—Posit empowers professionals across industries to innovate with data. -
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Domino Enterprise MLOps Platform
Domino Data Lab
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. -
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PurpleCube
PurpleCube
Enterprise-grade architecture and cloud data platform powered by Snowflake® to securely store and leverage your data in the cloud. Built-in ETL and drag-and-drop visual workflow designer to connect, clean & transform your data from 250+ data sources. Use the latest in Search and AI-driven technology to generate insights and actionable analytics from your data in seconds. Leverage our AI/ML environments to build, tune and deploy your models for predictive analytics and forecasting. Leverage our built-in AI/ML environments to take your data to the next level. Create, train, tune and deploy your AI models for predictive analysis and forecasting, using the PurpleCube Data Science module. Build BI visualizations with PurpleCube Analytics, search through your data using natural language, and leverage AI-driven insights and smart suggestions that deliver answers to questions you didn’t think to ask. -
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Deepnote
Deepnote
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 connectionStarting Price: Free -
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Oracle Machine Learning
Oracle
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. -
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Anaconda
Anaconda
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. -
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Cloudera Data Science Workbench
Cloudera
Accelerate machine learning from research to production with a consistent experience built for your traditional platform. With Python, R, and Scala directly in the web browser, Cloudera Data Science Workbench (CDSW) delivers a self-service experience data scientists will love. Download and experiment with the latest libraries and frameworks in customizable project environments that work just like your laptop. Cloudera Data Science Workbench provides connectivity not only to CDH and HDP but also to the systems your data science teams rely on for analysis. Cloudera Data Science Workbench lets data scientists manage their own analytics pipelines, including built-in scheduling, monitoring, and email alerting. Quickly develop and prototype new machine learning projects and easily deploy them to production. -
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Analance
Ducen
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. -
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Metaflow
Metaflow
Successful data science projects are delivered by data scientists who can build, improve, and operate end-to-end workflows independently, focusing more on data science, less on engineering. Use Metaflow with your favorite data science libraries, such as Tensorflow or SciKit Learn, and write your models in idiomatic Python code with not much new to learn. Metaflow also supports the R language. Metaflow helps you design your workflow, run it at scale, and deploy it to production. It versions and tracks all your experiments and data automatically. It allows you to inspect results easily in notebooks. Metaflow comes packaged with the tutorials, so getting started is easy. You can make copies of all the tutorials in your current directory using the metaflow command line interface. -
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JetBrains Datalore
JetBrains
Datalore is a collaborative data science and analytics platform aimed at boosting the whole analytics workflow and making work with data enjoyable for both data scientists and data savvy business teams across the enterprise. Keeping a major focus on data teams workflow, Datalore offers technical-savvy business users the ability to work together with data teams, using no-code or low-code together with the power of Jupyter notebooks. Datalore enables analytical self-service for business users, enabling them to work with data using SQL and no-code cells, build reports and deep dive into data. It offloads the core data team with simple tasks. Datalore enables analysts and data scientists to share results with ML Engineers. You can run your code on powerful CPUs or GPUs and collaborate with your colleagues in real-time.Starting Price: $19.90 per month -
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Saturn Cloud
Saturn Cloud
Saturn Cloud is an AI/ML platform available on every cloud. Data teams and engineers can build, scale, and deploy their AI/ML applications with any stack. Quickly spin up environments to test new ideas, then easily deploy them into production. Scale fast—from proof-of-concept to production-ready applications. Customers include NVIDIA, CFA Institute, Snowflake, Flatiron School, Nestle, and more. Get started for free at: saturncloud.ioStarting Price: $0.005 per GB per hour -
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Co.dx
TheMathCompany
Co.dx is a platform that helps businesses across multiple industries solve key problems through low code, custom business applications. Co.dx is built with the sole purpose of ensuring every stakeholder has the needed intelligence to make quick and effective decisions that unlock real-world value. We have codified and blended the knowledge of data science and business experts to deliver features that change the way businesses solve problems. Simplify data science with advanced and comprehensive AI/ML widgets that automate tasks across data engineering, data science and visualization. Benefit from state-of-the-art solution blueprints, infused with the IP of industry and data science experts, that capture the nuance of your industry. Generate robust applications that convert data science jargon into an easy-to-use business application designed to provide actionable insights. -
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Oracle Data Science
Oracle
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. -
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Google Colab
Google
Google Colab is a free, hosted Jupyter Notebook service that provides cloud-based environments for machine learning, data science, and educational purposes. It offers no-setup, easy access to computational resources such as GPUs and TPUs, making it ideal for users working with data-intensive projects. Colab allows users to run Python code in an interactive, notebook-style environment, share and collaborate on projects, and access extensive pre-built resources for efficient experimentation and learning. Colab also now offers a Data Science Agent automating analysis, from understanding the data to delivering insights in a working Colab notebook (Sequences shortened. Results for illustrative purposes. Data Science Agent may make mistakes.) -
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Neysa Aegis
Neysa
From thwarting model poisoning to preserving data integrity, Aegis ensures that your AI models are shielded by default, empowering you to deploy your AI/ML projects in the cloud or on-premise, confident that your security posture is protecting you against an evolving threat landscape. Unsecured AI/ML tools broaden attack surfaces, amplifying enterprise vulnerability to security breaches without vigilant oversight by security teams. Suboptimal AI/ML security posture risks data breaches, downtime, profit losses, reputational damage, and credential theft. Vulnerable AI/ML frameworks jeopardize data science initiatives, risking breaches, intellectual property theft, supply chain attacks, and data manipulation. Aegis uses an ensemble of specialized tools and AI models to analyse data from your AI/ML landscape, as well as external data sources. -
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IBM SPSS Modeler
IBM
IBM SPSS Modeler is a leading visual data science and machine learning (ML) solution designed to help enterprises accelerate time to value by speeding up operational tasks for data scientists. Organizations worldwide use it for data preparation and discovery, predictive analytics, model management and deployment, and ML to monetize data assets. IBM SPSS Modeler automatically transforms data into the best format for the most accurate predictive modeling. It now only takes a few clicks for you to analyze data, identify fixes, screen out fields and derive new attributes. Leverage IBM SPSS Modeler’s powerful graphics engine to bring your insights to life. The smart chart recommender finds the perfect chart for your data from among dozens of options, so you can share your insights quickly and easily using compelling visualizations. -
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TetraScience
TetraScience
Accelerate scientific discovery and empower your R&D team with harmonized data in the cloud. The Tetra R&D Data Cloud combines the industry’s only cloud-native data platform built for global pharmaceutical companies, with the power of the largest and fastest growing network of Life Sciences integrations, and deep domain knowledge, to deliver a future-proof solution for harnessing the power of your most valuable asset: R&D data. Covers the full life-cycle of your R&D data, from acquisition to harmonization, engineering, and downstream analysis with native support for state-of-the-art data science tools. Vendor-agnostic with pre-built integrations to easily connect to instruments, analytics and informatics applications, ELN/LIMS, CRO/CDMOs. Data acquisition, management, harmonization, integration/engineering and data science enablement in one single platform. -
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Antuit.ai
Antuit.ai
Antuit.ai is the leader in AI-powered cloud solutions for Retail and Consumer Goods. Our solution portfolio will help you digitally transform Forecasting, Pricing, Assortment, and Personalization. Our clients use Antuit.ai artificial intelligence, in production and at scale, to drive business decisions that result in substantial, financial impact. At antuit.ai, we differentiate ourselves from our competition with solutions that leverage the correct AI/ML algorithms in unique ways to solve real business problems. Rather than use off-the-shelf algorithms that force fit data through pre-defined data models, our data science team are all experts in AI/ML and fully understand the nature of these algorithms – what works well and what doesn’t. Together with our engineering team, they apply critical thinking and precision engineering to the data and science, pushing the boundaries of these algorithms to produce results that are truly innovative and transformative. -
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RapidMiner
Altair
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.Starting Price: Free -
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Amazon SageMaker Unified Studio is a comprehensive, AI and data development environment designed to streamline workflows and simplify the process of building and deploying machine learning models. Built on Amazon DataZone, it integrates various AWS analytics and AI/ML services, such as Amazon EMR, AWS Glue, and Amazon Bedrock, into a single platform. Users can discover, access, and process data from various sources like Amazon S3 and Redshift, and develop generative AI applications. With tools for model development, governance, MLOps, and AI customization, SageMaker Unified Studio provides an efficient, secure, and collaborative environment for data teams.
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Create, embed and govern analytically driven decision flows at scale in real-time or batch. SAS Data Science Programming enables data scientists who prefer a programmatic-only approach to access SAS analytical capabilities at all stages of the analytics life cycle, including data, discovery and deployment. 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. Solve complex analytical problems with a comprehensive visual interface that handles all tasks in the analytics life cycle.
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Solvuu
Solvuu
A data science platform for life scientists. Translate your microbiome research into practical applications. Bring novel, safe and effective products to market faster. Integrate the right set of data science and collaboration tools, and achieve rapid advances in cancer therapeutics. Accelerate research, enable innovation and create value by adopting effective digital technology solutions to improve crop productivity. Import your small and big data. Organize according to our templates, or define your own schema. Our format inference algorithm synthesizes parsing functions and lets you override if needed, without coding. Use our interactive import screens or CLI for bulk imports. Your data is not just bytes. Solvuu automatically computes relevant summary statistics and generates rich interactive visualizations. Explore and gain insights into your data immediately; slice and dice as needed. -
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Zepl
Zepl
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. -
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Dataiku
Dataiku
Dataiku is an advanced data science and machine learning platform designed to enable teams to build, deploy, and manage AI and analytics projects at scale. It empowers users, from data scientists to business analysts, to collaboratively create data pipelines, develop machine learning models, and prepare data using both visual and coding interfaces. Dataiku supports the entire AI lifecycle, offering tools for data preparation, model training, deployment, and monitoring. The platform also includes integrations for advanced capabilities like generative AI, helping organizations innovate and deploy AI solutions across industries. -
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KitOps
KitOps
KitOps is a packaging, versioning, and sharing system for AI/ML projects that uses open standards so it works with the AI/ML, development, and DevOps tools you are already using, and can be stored in your enterprise container registry. It's AI/ML platform engineering teams' preferred solution for securely packaging and versioning assets. KitOps creates a ModelKit for your AI/ML project which includes everything you need to reproduce it locally or deploy it into production. You can even selectively unpack a ModelKit so different team members can save time and storage space by only grabbing what they need for a task. Because ModelKits are immutable, signable, and live in your existing container registry they're easy for organizations to track, control, and audit. -
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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.
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Positron
Posit PBC
Positron is a next-generation, free, open source available integrated development environment for data science, built to support both Python and R in one unified workflow. It enables data professionals to move from exploration to production by offering interactive consoles, notebook support, variables and plot panes, and built-in previews of apps alongside code, all without needing extensive configuration. The IDE includes AI-assisted tools like the Positron Assistant and Databot agent to help write or refine code, perform exploratory analysis, and accelerate development. It offers features like a dedicated Data Explorer for viewing dataframes, a connections pane for databases, a variables pane, a plot pane, and seamless switch between R and Python with full support for notebooks, scripts, and visual dashboards. With version control, extensions support, and deep integration with other tools in the Posit Software ecosystem.Starting Price: Free -
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Outerbounds
Outerbounds
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. -
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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.Starting Price: $699 per month
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KNIME Analytics Platform
KNIME
One enterprise-grade software platform, two complementary tools. Open source KNIME Analytics Platform for creating data science and commercial KNIME Server for productionizing data science. KNIME Analytics Platform is the open source software for creating data science. Intuitive, open, and continuously integrating new developments, KNIME makes understanding data and designing data science workflows and reusable components accessible to everyone. KNIME Server is the enterprise software for team-based collaboration, automation, management, and deployment of data science workflows as analytical applications and services. Non experts are given access to data science via KNIME WebPortal or can use REST APIs. Do even more with your data using extensions for KNIME Analytics Platform. Some are developed and maintained by us at KNIME, others by the community and our trusted partners. We also have integrations with many open source projects. -
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Zerve AI
Zerve AI
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. -
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Kedro
Kedro
Kedro is the foundation for clean data science code. It borrows concepts from software engineering and applies them to machine-learning projects. A Kedro project provides scaffolding for complex data and machine-learning pipelines. You spend less time on tedious "plumbing" and focus instead on solving new problems. Kedro standardizes how data science code is created and ensures teams collaborate to solve problems easily. Make a seamless transition from development to production with exploratory code that you can transition to reproducible, maintainable, and modular experiments. A series of lightweight data connectors is used to save and load data across many different file formats and file systems.Starting Price: Free -
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Darwin
SparkCognition
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.Starting Price: $4000 -
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With SAS Visual Statistics, multiple users can explore data, then interactively create and refine predictive models. Your data scientists and statisticians can act on observations at a granular level using the most appropriate analytical modeling techniques. The result? You'll unearth insights at unprecedented speeds, and find new ways to grow revenue. Easily build and refine models to target specific groups or segments, and run numerous scenarios simultaneously. You can ask more what-if questions to get better results. And put results into action with an automatically generated score code. Empower multiple users to interact with data visually – to add or change variables, remove outliers, etc. Instantly see how changes affect your model's predictive power, and make refinements quickly. Data science teams have the ultimate flexibility of working in their language of choice, so they can use their skills to the fullest. SAS Visual Statistics unites all analytical assets.
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Incedo Lighthouse
Incedo
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. -
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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.
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Albert
Albert Invent
Meet Albert, the end-to-end platform that’s digitalizing materials science for the age of AI. From molecular design to industrial production, we've lived the challenges of chemical innovation. Albert is built and implemented by industry veterans to meet the real-world needs of chemists, for today's challenges and tomorrow's innovations. Break down the silos in your R&D processes with Albert’s end-to-end platform. By combining ELN, LIMS, AI/ML, automated SDS generation, and other capabilities, Albert creates a unified flow of knowledge throughout R&D that enables innovation. Equip every scientist in your organization with the power of AI. Albert's specialized AI is trained like a chemist to optimize formulations and accelerate experiments, so you can get new products to market more than 50% faster. Our intuitive design and collaborative implementation, rooted in our own lab experience, ensure seamless integration into your workflows. -
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FeatureByte
FeatureByte
FeatureByte is your AI data scientist streamlining the entire lifecycle so that what once took months now happens in hours. Deployed natively on Databricks, Snowflake, BigQuery, or Spark, it automates feature engineering, ideation, cataloging, custom UDFs (including transformer support), evaluation, selection, historical backfill, deployment, and serving (online or batch), all within a unified platform. FeatureByte’s GenAI‑inspired agents, data, domain, MLOps, and data science agents interactively guide teams through data acquisition, quality, feature generation, model creation, deployment orchestration, and continued monitoring. FeatureByte’s SDK and intuitive UI enable automated and semi‑automated feature ideation, customizable pipelines, cataloging, lineage tracking, approval flows, RBAC, alerts, and version control, empowering teams to build, refine, document, and serve features rapidly and reliably. -
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dotData
dotData
dotData frees your business to focus on the results of your AI and machine learning applications, not the headaches of the data science process by automating the full data science life-cycle. Deploy full-cycle AI & ML pipeline in minutes, update in real-time with continuous deployment. Accelerate data science projects from months to days with feature engineering automation. Discover the unknown unknowns of your business automatically with data science automation. The process of using data science to develop and deploy accurate machine learning and AI models is cumbersome, time-consuming, labor-intensive, and interdisciplinary. Automate the most time-consuming and repetitive tasks that are the bane of data science work and shorten AI development times from months to days. -
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NVIDIA Merlin
NVIDIA
NVIDIA Merlin empowers data scientists, machine learning engineers, and researchers to build high-performing recommenders at scale. Merlin includes libraries, methods, and tools that streamline the building of recommenders by addressing common preprocessing, feature engineering, training, inference, and deploying to production challenges. Merlin components and capabilities are optimized to support the retrieval, filtering, scoring, and ordering of hundreds of terabytes of data, all accessible through easy-to-use APIs. With Merlin, better predictions, increased click-through rates, and faster deployment to production are within reach. NVIDIA Merlin, as part of NVIDIA AI, advances our commitment to supporting innovative practitioners doing their best work. As an end-to-end solution, NVIDIA Merlin components are designed to be interoperable within existing recommender workflows that utilize data science, and machine learning (ML). -
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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.
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Tovana
Verix
Tovana is a science-driven methodical approach to connecting data-Science with deep pharma domain knowledge, using advanced Machine Learning (ML) technology to solve the challenges of building and executing a winning HCP engagement strategy, in a continuous, optimal manner. Experience a noticeable boost in growth through streamlining your Go-to-Market strategy, by combining human knowledge with easy-to-use AI/ML technology to bridge the infamous gap between strategy and execution. Tovana promotes self-reliance, removing the dependency on third parties to manage your own strategy execution and giving you full control to quickly calibrate and course correct. Tovana provides you full control over your business, free from the nagging dependency on 3rd parties to generate, scrutinize, and adjust strategic processes such as targeting & segmentation, sales forecasting, and campaign management. -
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HyperCube
BearingPoint
Whatever your business need, discover hidden insights quickly and easily using HyperCube, the platform designed for the way data scientists work. Put your business data to work. Unlock understanding, discover unrealized opportunities, generate predictions and avoid risks before they happen. HyperCube takes huge volumes of data and turns it into actionable insights. Whether a beginner in analytics or a machine learning expert, HyperCube is designed with you in mind. It is the Swiss Army knife of data science, combining proprietary and open source code to deliver a wide range of data analysis features straight out of the box or as business apps, customized just for you. We are constantly updating and perfecting our technology so we can deliver the most innovative, intuitive and adaptable results Choose from apps, data-as-a-services (DaaS) and vertical market solutions. -
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Rational BI
Rational BI
Spend less time preparing your data and more time analyzing it. Not only can you build better looking and more accurate reports, you can centralize all your data gathering, analytics and data science in a single interface, accessible to everyone in the organization. Import all your data no matter where it lives. Whether you’re looking to build scheduled reports from your Excel files, cross-reference data between files and databases or turn your data into SQL queryable databases, Rational BI gives you all the tools you need. Discover the signals hidden in your data, make it available without delay and move ahead of your competition. Magnify the analytics capabilities of your organization through business intelligence that makes it easy to find the latest up-to-date data and analyze it through an interface that delights both data scientists and casual data consumers.Starting Price: $129 per month -
46
MLJAR Studio
MLJAR
It's a desktop app with Jupyter Notebook and Python built in, installed with just one click. It includes interactive code snippets and an AI assistant to make coding faster and easier, perfect for data science projects. We manually hand crafted over 100 interactive code recipes that you can use in your Data Science projects. Code recipes detect packages available in the current environment. Install needed modules with 1-click, literally. You can create and interact with all variables available in your Python session. Interactive recipes speed-up your work. AI Assistant has access to your current Python session, variables and modules. Broad context makes it smart. Our AI Assistant was designed to solve data problems with Python programming language. It can help you with plots, data loading, data wrangling, Machine Learning and more. Use AI to quickly solve issues with code, just click Fix button. The AI assistant will analyze the error and propose the solution.Starting Price: $20 per month -
47
Wolfram Data Science Platform
Wolfram
Wolfram Data Science Platform lets you use data sources that are structured or unstructured, and static or real-time. Use the power of WDF and the same linguistics as in Wolfram|Alpha to convert unstructured data to structured form, with automated or guided destructuring and disambiguation. Wolfram Data Science Platform uses industry database connection technology to bring database content into its highly flexible internal symbolic representation. Wolfram Data Science Platform can natively read hundreds of data formats, converting them. Wolfram Data Science Platform works with images, text, networks, geometry, sounds, GIS data and much more. Using the breakthrough symbolic data representation in the Wolfram Language, Wolfram Data Science Platform can seamlessly handle both SQL-style and NoSQL data. Wolfram Data Science Platform automatically constructs a sophisticated interactive report, using algorithms to identify interesting features of your data to visualize and highlight. -
48
FutureAnalytica
FutureAnalytica
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. -
49
Azure Data Science Virtual Machines
Microsoft
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.Starting Price: $0.005 -
50
ZinkML
ZinkML Technologies
ZinkML is a zero-code data science platform designed to address the challenges faced by organizations in leveraging data effectively. By providing a visual and intuitive interface, it eliminates the need for extensive coding expertise, making data science accessible to a broader range of users. ZinkML streamlines the entire data science lifecycle, from data ingestion and preparation to model building, deployment, and monitoring. Users can drag-and-drop components to create complex data pipelines, explore data visually, and build predictive models without writing a single line of code. The platform also offers automated feature engineering, model selection, and hyperparameter tuning, accelerating the model development process. Moreover, ZinkML provides robust collaboration features, enabling teams to work together seamlessly on data science projects. By democratizing data science, we empower companies to extract maximum value from their data and drive better decision-making.
