Alternatives to Incedo Lighthouse

Fully managed ML tools allow you to build, deploy and scale machine-learning (ML) models quickly, for any use case. Vertex AI Workbench is natively integrated with BigQuery Dataproc and Spark. You can use BigQuery to create and execute machine-learning models in BigQuery by using standard SQL queries and spreadsheets or you can export datasets directly from BigQuery into Vertex AI Workbench to run your models there. Vertex Data Labeling can be used to create highly accurate labels for data collection. Vertex AI Agent Builder empowers developers to design and deploy advanced generative AI applications for enterprise use. It supports both no-code and code-driven development, enabling users to create AI agents through natural language prompts or by integrating with frameworks like LangChain and LlamaIndex.

BigQuery is a serverless, multicloud data warehouse that makes working with all types of data effortless, allowing you to focus on extracting valuable business insights quickly. As a central component of Google’s data cloud, it streamlines data integration, enables cost-effective and secure scaling of analytics, and offers built-in business intelligence for sharing detailed data insights. With a simple SQL interface, it also supports training and deploying machine learning models, helping to foster data-driven decision-making across your organization. Its robust performance ensures that businesses can handle increasing data volumes with minimal effort, scaling to meet the needs of growing enterprises. Gemini within BigQuery brings AI-powered tools that enhance collaboration and productivity, such as code recommendations, visual data preparation, and intelligent suggestions aimed at improving efficiency and lowering costs. The platform offers an all-in-one environment with SQL, a notebook, and a natural language-based canvas interface, catering to data professionals of all skill levels. This cohesive workspace simplifies the entire analytics journey, enabling teams to work faster and more efficiently.

Qloo, the "Cultural AI", is capable of decoding and forecasting consumer tastes around the world. Privacy-first API that predicts global consumer preferences, catalogs hundreds of million of cultural entities, and is privacy-first. Our API provides contextualized personalization and insight based on deep understanding of consumer behavior. We have access to more than 575,000,000 people, places, and things. Our technology allows you to see beyond trends and discover the connections that underlie people's tastes in their world. Our vast library includes entities such as brands, music, film and fashion. We also have information about notable people. Results are delivered in milliseconds. They can be weighted with factors like regionalization and real time popularity. Companies who want to use best-in-class data to enhance their customer experiences. Our flagship recommendation API provides results based on demographics and preferences, cultural entities, metadata, geolocational factors, and metadata.

Domo puts data to work for everyone so they can multiply their impact on the business. Underpinned by a secure data foundation, our cloud-native data experience platform makes data visible and actionable with user-friendly dashboards and apps. Domo helps companies optimize critical business processes at scale and in record time to spark bold curiosity that powers exponential business results.

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.

Snowflake offers a unified AI Data Cloud platform that transforms how businesses store, analyze, and leverage data by eliminating silos and simplifying architectures. It features interoperable storage that enables seamless access to diverse datasets at massive scale, along with an elastic compute engine that delivers leading performance for a wide range of workloads. Snowflake Cortex AI integrates secure access to cutting-edge large language models and AI services, empowering enterprises to accelerate AI-driven insights. The platform’s cloud services automate and streamline resource management, reducing complexity and cost. Snowflake also offers Snowgrid, which securely connects data and applications across multiple regions and cloud providers for a consistent experience. Their Horizon Catalog provides built-in governance to manage security, privacy, compliance, and access control. Snowflake Marketplace connects users to critical business data and apps to foster collaboration within the AI Data Cloud network. Serving over 11,000 customers worldwide, Snowflake supports industries from healthcare and finance to retail and telecom.

Immuta's Data Access Platform is built to give data teams secure yet streamlined access to data. Every organization is grappling with complex data policies as rules and regulations around that data are ever-changing and increasing in number. Immuta empowers data teams by automating the discovery and classification of new and existing data to speed time to value; orchestrating the enforcement of data policies through Policy-as-code (PaC), data masking, and Privacy Enhancing Technologies (PETs) so that any technical or business owner can manage and keep it secure; and monitoring/auditing user and policy activity/history and how data is accessed through automation to ensure provable compliance. Immuta integrates with all of the leading cloud data platforms, including Snowflake, Databricks, Starburst, Trino, Amazon Redshift, Google BigQuery, and Azure Synapse. Our platform is able to transparently secure data access without impacting performance. With Immuta, data teams are able to speed up data access by 100x, decrease the number of policies required by 75x, and achieve provable compliance goals.

The primary obstacle in expanding AI-driven decision-making lies in the underutilization of data. IBM Cloud Pak® for Data provides a cohesive platform that integrates a data fabric, enabling seamless connection and access to isolated data, whether it resides on-premises or in various cloud environments, without necessitating data relocation. It streamlines data accessibility by automatically identifying and organizing data to present actionable knowledge assets to users, while simultaneously implementing automated policy enforcement to ensure secure usage. To further enhance the speed of insights, this platform incorporates a modern cloud data warehouse that works in harmony with existing systems. It universally enforces data privacy and usage policies across all datasets, ensuring compliance is maintained. By leveraging a high-performance cloud data warehouse, organizations can obtain insights more rapidly. Additionally, the platform empowers data scientists, developers, and analysts with a comprehensive interface to construct, deploy, and manage reliable AI models across any cloud infrastructure. Moreover, enhance your analytics capabilities with Netezza, a robust data warehouse designed for high performance and efficiency. This comprehensive approach not only accelerates decision-making but also fosters innovation across various sectors.

Composable is an enterprise-grade DataOps platform designed for business users who want to build data-driven products and create data intelligence solutions. It can be used to design data-driven products that leverage disparate data sources, live streams, and event data, regardless of their format or structure. Composable offers a user-friendly, intuitive dataflow visual editor, built-in services that facilitate data engineering, as well as a composable architecture which allows abstraction and integration of any analytical or software approach. It is the best integrated development environment for discovering, managing, transforming, and analysing enterprise data.

Embrace a groundbreaking age of analytics through the Alteryx AI Platform. Equip your organization with streamlined data preparation, analytics powered by artificial intelligence, and accessible machine learning, all while ensuring governance and security are built in. This marks the dawn of a new era for data-driven decision-making accessible to every user and team at all levels. Enhance your teams' capabilities with a straightforward, user-friendly interface that enables everyone to develop analytical solutions that boost productivity, efficiency, and profitability. Foster a robust analytics culture by utilizing a comprehensive cloud analytics platform that allows you to convert data into meaningful insights via self-service data preparation, machine learning, and AI-generated findings. Minimize risks and safeguard your data with cutting-edge security protocols and certifications. Additionally, seamlessly connect to your data and applications through open API standards, facilitating a more integrated and efficient analytical environment. By adopting these innovations, your organization can thrive in an increasingly data-centric world.

RapidMiner is redefining enterprise AI so anyone can positively shape the future. RapidMiner empowers data-loving people from all levels to quickly create and implement AI solutions that drive immediate business impact. Our platform unites data prep, machine-learning, and model operations. This provides a user experience that is both rich in data science and simplified for all others. Customers are guaranteed success with our Center of Excellence methodology, RapidMiner Academy and no matter what level of experience or resources they have.

A platform for Machine Learning and Predictive Analytics enhances data-driven decision-making and propels business growth through sophisticated artificial intelligence within an integrated machine learning and big data analytics framework. OpenText Magellan leverages AI technologies to deliver predictive analytics through user-friendly and adaptable data visualizations that enhance the utility of business intelligence. The implementation of artificial intelligence software streamlines the big data processing task, providing essential business insights in a format that aligns with the organization’s most significant goals. By enriching business operations with a tailored combination of features such as predictive modeling, data exploration tools, data mining methods, and IoT data analytics, companies can effectively utilize their data to refine their decision-making processes based on actionable business intelligence and analytics. This comprehensive approach not only improves operational efficiency but also fosters a culture of data-driven innovation within the organization.

Analance is a comprehensive and scalable solution that integrates Data Science, Advanced Analytics, Business Intelligence, and Data Management into one seamless, self-service platform. Designed to empower users with essential analytical capabilities, it ensures that data insights are readily available to all, maintains consistent performance as user demands expand, and meets ongoing business goals within a singular framework. Analance is dedicated to transforming high-quality data into precise predictions, providing both seasoned data scientists and novice users with intuitive, point-and-click pre-built algorithms alongside a flexible environment for custom coding. By bridging the gap between advanced analytics and user accessibility, Analance facilitates informed decision-making across organizations. Company – Overview Ducen IT supports Business and IT professionals in Fortune 1000 companies by offering advanced analytics, business intelligence, and data management through its distinctive, all-encompassing data science platform known as Analance.

A data science platform designed to enhance productivity offers unmatched features that facilitate the development and assessment of superior machine learning (ML) models. By leveraging enterprise-trusted data swiftly, businesses can achieve greater flexibility and meet their data-driven goals through simpler deployment of ML models. Cloud-based solutions enable organizations to uncover valuable business insights efficiently. The journey of constructing a machine learning model is inherently iterative, and this ebook meticulously outlines the stages involved in its creation. Readers can engage with notebooks to either build or evaluate various machine learning algorithms. Experimenting with AutoML can yield impressive data science outcomes, allowing users to create high-quality models with greater speed and ease. Moreover, automated machine learning processes quickly analyze datasets, recommending the most effective data features and algorithms while also fine-tuning models and clarifying their results. This comprehensive approach ensures that businesses can harness the full potential of their data, driving innovation and informed decision-making.

No matter what your business requirements are, quickly unearth concealed insights with HyperCube, a platform tailored to meet the needs of data scientists. Harness your business data effectively to gain clarity, identify untapped opportunities, make forecasts, and mitigate risks before they arise. HyperCube transforms vast amounts of data into practical insights. Whether you're just starting with analytics or are a seasoned machine learning specialist, HyperCube is thoughtfully crafted to cater to your needs. It serves as the multifaceted tool of data science, integrating both proprietary and open-source code to provide a diverse array of data analysis capabilities, available either as ready-to-use applications or tailored business solutions. We are committed to continuously enhancing our technology to offer you the most cutting-edge, user-friendly, and flexible outcomes. You can choose from a variety of applications, data-as-a-service (DaaS), and tailored solutions for specific industries, ensuring that your unique requirements are met efficiently. With HyperCube, unlocking the full potential of your data has never been more accessible.

The Databricks Data Intelligence Platform empowers every member of your organization to leverage data and artificial intelligence effectively. Constructed on a lakehouse architecture, it establishes a cohesive and transparent foundation for all aspects of data management and governance, enhanced by a Data Intelligence Engine that recognizes the distinct characteristics of your data. Companies that excel across various sectors will be those that harness the power of data and AI. Covering everything from ETL processes to data warehousing and generative AI, Databricks facilitates the streamlining and acceleration of your data and AI objectives. By merging generative AI with the integrative advantages of a lakehouse, Databricks fuels a Data Intelligence Engine that comprehends the specific semantics of your data. This functionality enables the platform to optimize performance automatically and manage infrastructure in a manner tailored to your organization's needs. Additionally, the Data Intelligence Engine is designed to grasp the unique language of your enterprise, making the search and exploration of new data as straightforward as posing a question to a colleague, thus fostering collaboration and efficiency. Ultimately, this innovative approach transforms the way organizations interact with their data, driving better decision-making and insights.

Neural Designer is a data-science and machine learning platform that allows you to build, train, deploy, and maintain neural network models. This tool was created to allow innovative companies and research centres to focus on their applications, not on programming algorithms or programming techniques. Neural Designer does not require you to code or create block diagrams. Instead, the interface guides users through a series of clearly defined steps. Machine Learning can be applied in different industries. These are some examples of machine learning solutions: - In engineering: Performance optimization, quality improvement and fault detection - In banking, insurance: churn prevention and customer targeting. - In healthcare: medical diagnosis, prognosis and activity recognition, microarray analysis and drug design. Neural Designer's strength is its ability to intuitively build predictive models and perform complex operations.

Oversee and protect the entire data lifecycle from the Edge to AI across any cloud platform or data center. Functions seamlessly within all leading public cloud services as well as private clouds, providing a uniform public cloud experience universally. Unifies data management and analytical processes throughout the data lifecycle, enabling access to data from any location. Ensures the implementation of security measures, regulatory compliance, migration strategies, and metadata management in every environment. With a focus on open source, adaptable integrations, and compatibility with various data storage and computing systems, it enhances the accessibility of self-service analytics. This enables users to engage in integrated, multifunctional analytics on well-managed and protected business data, while ensuring a consistent experience across on-premises, hybrid, and multi-cloud settings. Benefit from standardized data security, governance, lineage tracking, and control, all while delivering the robust and user-friendly cloud analytics solutions that business users need, effectively reducing the reliance on unauthorized IT solutions. Additionally, these capabilities foster a collaborative environment where data-driven decision-making is streamlined and more efficient.

Experience the entire journey of developing machine learning algorithms and forecasting results with just a single click. Not every dataset is inherently suitable for machine learning; leverage the Data Dialog to effortlessly refine your data without the hassle of file manipulation. You can easily distribute your prediction reports among your team or make them publicly accessible, allowing anyone to engage with your model and generate predictions. Integrate dynamic ML predictions directly into your application through our user-friendly low-code API. Assess factors like willingness to pay, evaluate leads, and more, all in real-time. Obviously AI equips you with the latest groundbreaking algorithms while ensuring top-notch performance is maintained. You can now accurately forecast revenue, streamline supply chains, and tailor marketing efforts to individual needs. With just a CSV upload or a quick integration with your preferred data sources, you can select your prediction column from a convenient dropdown menu and watch as we automatically construct the AI for you. Additionally, enjoy beautifully crafted visualizations of predicted outcomes, identify key influencers, and explore "what-if" scenarios to better understand potential futures. This innovative approach transforms the way you interact with data and make predictions.

BIRD Analytics is an exceptionally rapid, high-performance, comprehensive platform for data management and analytics that leverages agile business intelligence alongside AI and machine learning models to extract valuable insights. It encompasses every component of the data lifecycle, including ingestion, transformation, wrangling, modeling, and real-time analysis, all capable of handling petabyte-scale datasets. With self-service features akin to Google search and robust ChatBot integration, BIRD empowers users to find solutions quickly. Our curated resources deliver insights, from industry use cases to informative blog posts, illustrating how BIRD effectively tackles challenges associated with Big Data. After recognizing the advantages BIRD offers, you can arrange a demo to witness the platform's capabilities firsthand and explore how it can revolutionize your specific data requirements. By harnessing AI and machine learning technologies, organizations can enhance their agility and responsiveness in decision-making, achieve cost savings, and elevate customer experiences significantly. Ultimately, BIRD Analytics positions itself as an essential tool for businesses aiming to thrive in a data-driven landscape.

Experience an enterprise-level architecture and a cloud data platform powered by Snowflake® that enables secure storage and utilization of your data in the cloud. With integrated ETL and an intuitive drag-and-drop visual workflow designer, you can easily connect, clean, and transform data from over 250 sources. Harness cutting-edge Search and AI technology to quickly generate insights and actionable analytics from your data within seconds. Utilize our advanced AI/ML environments to create, refine, and deploy your predictive analytics and forecasting models. Take your data capabilities further with our comprehensive AI/ML frameworks, allowing you to design, train, and implement AI models through the PurpleCube Data Science module. Additionally, construct engaging BI visualizations with PurpleCube Analytics, explore your data using natural language searches, and benefit from AI-driven insights and intelligent recommendations that reveal answers to questions you may not have considered. This holistic approach ensures that you are equipped to make data-driven decisions with confidence and clarity.

Machine learning reveals concealed patterns and valuable insights within enterprise data, ultimately adding significant value to businesses. Oracle Machine Learning streamlines the process of creating and deploying machine learning models for data scientists by minimizing data movement, incorporating AutoML technology, and facilitating easier deployment. Productivity for data scientists and developers is enhanced while the learning curve is shortened through the use of user-friendly Apache Zeppelin notebook technology based on open source. These notebooks accommodate SQL, PL/SQL, Python, and markdown interpreters tailored for Oracle Autonomous Database, enabling users to utilize their preferred programming languages when building models. Additionally, a no-code interface that leverages AutoML on Autonomous Database enhances accessibility for both data scientists and non-expert users, allowing them to harness powerful in-database algorithms for tasks like classification and regression. Furthermore, data scientists benefit from seamless model deployment through the integrated Oracle Machine Learning AutoML User Interface, ensuring a smoother transition from model development to application. This comprehensive approach not only boosts efficiency but also democratizes machine learning capabilities across the organization.

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.

Scribble Data empowers organizations to enhance their raw data, enabling swift and reliable decision-making to address ongoing business challenges. This platform provides data-driven support for enterprises, facilitating the generation of high-quality insights that streamline the decision-making process. With advanced analytics driven by machine learning, businesses can tackle their persistent decision-making issues rapidly. You can focus on essential tasks while Scribble Data manages the complexities of ensuring dependable and trustworthy data availability for informed choices. Take advantage of tailored data-driven workflows that simplify data usage and lessen reliance on data science and machine learning teams. Experience accelerated transformation from concept to operational data products in just a few weeks, thanks to feature engineering capabilities that effectively handle large volumes and complex data at scale. Additionally, this seamless integration fosters a culture of data-centric operations, positioning your organization for long-term success in an ever-evolving marketplace.

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.

Stata delivers everything you need for reproducible data analysis—powerful statistics, visualization, data manipulation, and automated reporting—all in one intuitive platform. 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.

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.

Dataiku serves as a sophisticated platform for data science and machine learning, aimed at facilitating teams in the construction, deployment, and management of AI and analytics projects on a large scale. It enables a diverse range of users, including data scientists and business analysts, to work together in developing data pipelines, crafting machine learning models, and preparing data through various visual and coding interfaces. Supporting the complete AI lifecycle, Dataiku provides essential tools for data preparation, model training, deployment, and ongoing monitoring of projects. Additionally, the platform incorporates integrations that enhance its capabilities, such as generative AI, thereby allowing organizations to innovate and implement AI solutions across various sectors. This adaptability positions Dataiku as a valuable asset for teams looking to harness the power of AI effectively.

Data plays an essential role in the process of establishing, optimizing, and expanding your enterprise. Nevertheless, fully harnessing the potential of data can prove difficult as many businesses encounter issues like limited data access, mismatched tools, escalating expenses, and delayed outcomes. In simple terms, those who can effectively convert unrefined data into actionable insights will excel in the current business environment. A crucial aspect of achieving this is enabling all team members to analyze, create, and collaborate on comprehensive AI and machine learning projects efficiently and within a unified platform. Streamflux serves as a comprehensive solution for addressing your data analytics and AI needs. Our user-friendly platform empowers you to construct complete data solutions, utilize models to tackle intricate inquiries, and evaluate user interactions. Whether your focus is on forecasting customer attrition, estimating future earnings, or crafting personalized recommendations, you can transform raw data into meaningful business results within days rather than months. By leveraging our platform, organizations can not only enhance efficiency but also foster a culture of data-driven decision-making.

Decision intelligence aims to empower employees with the ability to make faster, more informed decisions that will allow them to take corrective steps, capitalize on opportunities, and drive innovation. The data and analytics platform that is purpose-built to help enterprises make better, faster decisions. A new type of engine drives it. Streamlining the entire analysis workflow. One platform for all data, any person, and any analytics needs. This is the future for intelligent decisions. This new platform combines data preparation, data science, and business analytics into one integrated platform. Streamline all aspects of decision-making. Everything from discovery to publishing to modeling is interconnected (and easy-to-use). It can be run at hyper-scale to support any data-driven decision. Advanced data science is available for all business needs, from the C-Suite to frontline.

Gathr is a Data+AI fabric, helping enterprises rapidly deliver production-ready data and AI products. Data+AI fabric enables teams to effortlessly acquire, process, and harness data, leverage AI services to generate intelligence, and build consumer applications— all with unparalleled speed, scale, and confidence. Gathr’s self-service, AI-assisted, and collaborative approach enables data and AI leaders to achieve massive productivity gains by empowering their existing teams to deliver more valuable work in less time. With complete ownership and control over data and AI, flexibility and agility to experiment and innovate on an ongoing basis, and proven reliable performance at real-world scale, Gathr allows them to confidently accelerate POVs to production. Additionally, Gathr supports both cloud and air-gapped deployments, making it the ideal choice for diverse enterprise needs. Gathr, recognized by leading analysts like Gartner and Forrester, is a go-to-partner for Fortune 500 companies, such as United, Kroger, Philips, Truist, and many others.

You can quickly find answers with the flexible visual query builder. You can access data via your browser or phone and analyze it anywhere you are. No SQL, data scientist, or desktop required. You can learn from your team mates and search for any questions within your organization with shared questions. @mentions, push notifications and shared chat allow you to bring the right people in the conversation and make data actionable. You can easily copy and modify shared questions, export data and change the way charts are displayed so you don't just see someone else's analysis but make it yours. External sharing can be turned on to allow access to data tables and partners outside your domain. In just two clicks, you can access the underlying data tables. Smart typeaheads make it easy to run custom SQL.

Doolytic is at the forefront of big data discovery, integrating data exploration, advanced analytics, and the vast potential of big data. The company is empowering skilled BI users to participate in a transformative movement toward self-service big data exploration, uncovering the inherent data scientist within everyone. As an enterprise software solution, doolytic offers native discovery capabilities specifically designed for big data environments. Built on cutting-edge, scalable, open-source technologies, doolytic ensures lightning-fast performance, managing billions of records and petabytes of information seamlessly. It handles structured, unstructured, and real-time data from diverse sources, providing sophisticated query capabilities tailored for expert users while integrating with R for advanced analytics and predictive modeling. Users can effortlessly search, analyze, and visualize data from any format and source in real-time, thanks to the flexible architecture of Elastic. By harnessing the capabilities of Hadoop data lakes, doolytic eliminates latency and concurrency challenges, addressing common BI issues and facilitating big data discovery without cumbersome or inefficient alternatives. With doolytic, organizations can truly unlock the full potential of their data assets.

VantageCloud by Teradata is a next-gen cloud analytics ecosystem built to unify disparate data sources, deliver real-time AI-powered insights, and drive enterprise innovation with unprecedented efficiency. The platform includes VantageCloud Lake, designed for elastic scalability and GPU-accelerated AI workloads, and VantageCloud Enterprise, which supports robust analytics capabilities across secure hybrid and multi-cloud deployments. It seamlessly integrates with leading cloud providers like AWS, Azure, and Google Cloud, and supports open table formats like Apache Iceberg for greater data flexibility. With built-in support for advanced analytics, workload management, and cross-functional collaboration, VantageCloud provides the agility and power modern enterprises need to accelerate digital transformation and optimize operational outcomes.

A new category of AI. Most AI solutions today are designed using a mathematical and statistical lens. We took a different approach. Intelligent Artifacts' team has created a new type of AI based on information theory. It is a true AGI that eliminates the current shortcomings in machine intelligence. Our framework separates the intelligence layer from the data and application layers, allowing it to learn in real time and allowing it to make predictions down to the root cause. A truly integrated platform is required for AGI. Intelligent Artifacts will allow you to model information, not data. Predictions and decisions can be made across multiple domains without the need for rewriting code. Our dynamic platform and specialized AI consultants will provide you with a tailored solution that quickly provides deep insights and better outcomes from your data.

TrueFoundry is a cloud-native platform-as-a-service for machine learning training and deployment built on Kubernetes, designed to empower machine learning teams to train and launch models with the efficiency and reliability typically associated with major tech companies, all while ensuring scalability to reduce costs and speed up production release. By abstracting the complexities of Kubernetes, it allows data scientists to work in a familiar environment without the overhead of managing infrastructure. Additionally, it facilitates the seamless deployment and fine-tuning of large language models, prioritizing security and cost-effectiveness throughout the process. TrueFoundry features an open-ended, API-driven architecture that integrates smoothly with internal systems, enables deployment on a company's existing infrastructure, and upholds stringent data privacy and DevSecOps standards, ensuring that teams can innovate without compromising on security. This comprehensive approach not only streamlines workflows but also fosters collaboration among teams, ultimately driving faster and more efficient model deployment.

FortressIQ is the industry's most advanced process-intelligence platform. It allows enterprises to decode work and transform experiences. FortressIQ combines innovative computer vision with artificial intelligence to provide unprecedented process insights. It is extremely fast and delivers detail and accuracy that are unattainable using traditional methods. The platform automatically acquires process data across multiple systems. This empowers enterprises to understand, monitor and improve their operations, employee and customer experience, and every business process. FortressIQ was established in 2017 and is supported by Lightspeed Venture Partners and Boldstart Ventures as well as Comcast Ventures and Eniac Ventures. Continuously and automatically identify inefficiencies and process variations to determine optimal process paths and reduce time to automate.

Effortlessly manage, process, and transform CAD, FE, CFD, and test data with ease. Establish automatic data pipelines for machine learning, reduced order modeling, and 3D deep learning applications. Eliminate the complexity of data science without the need for coding. Key Ward's platform stands out as the pioneering end-to-end no-code engineering solution, fundamentally changing the way engineers work with their data, whether it be experimental or CAx. By harnessing the power of engineering data intelligence, our software empowers engineers to seamlessly navigate their multi-source data, extracting immediate value through integrated advanced analytics tools while also allowing for the custom development of machine learning and deep learning models, all within a single platform with just a few clicks. Centralize, update, extract, sort, clean, and prepare your diverse data sources for thorough analysis, machine learning, or deep learning applications automatically. Additionally, leverage our sophisticated analytics tools on your experimental and simulation data to uncover correlations, discover dependencies, and reveal underlying patterns that can drive innovation in engineering processes. Ultimately, this approach streamlines workflows, enhancing productivity and enabling more informed decision-making in engineering endeavors.

Manage and optimize models throughout the entire ML lifecycle. This includes experiment tracking, monitoring production models, and more. The platform was designed to meet the demands of large enterprise teams that deploy ML at scale. It supports any deployment strategy, whether it is private cloud, hybrid, or on-premise servers. Add two lines of code into your notebook or script to start tracking your experiments. It works with any machine-learning library and for any task. To understand differences in model performance, you can easily compare code, hyperparameters and metrics. Monitor your models from training to production. You can get alerts when something is wrong and debug your model to fix it. You can increase productivity, collaboration, visibility, and visibility among data scientists, data science groups, and even business stakeholders.

Google Colab is a complimentary, cloud-based Jupyter Notebook platform that facilitates environments for machine learning, data analysis, and educational initiatives. It provides users with immediate access to powerful computational resources, including GPUs and TPUs, without the need for complex setup, making it particularly suitable for those engaged in data-heavy projects. Users can execute Python code in an interactive notebook format, collaborate seamlessly on various projects, and utilize a wide range of pre-built tools to enhance their experimentation and learning experience. Additionally, Colab has introduced a Data Science Agent that streamlines the analytical process by automating tasks from data comprehension to providing insights within a functional Colab notebook, although it is important to note that the agent may produce errors. This innovative feature further supports users in efficiently navigating the complexities of data science workflows.

Coordinate, explore, and oversee all projects within your data science team efficiently. With Zepl's advanced search functionality, you can easily find and repurpose both models and code. The enterprise collaboration platform provided by Zepl allows you to query data from various sources like Snowflake, Athena, or Redshift while developing your models using Python. Enhance your data interaction with pivoting and dynamic forms that feature visualization tools such as heatmaps, radar, and Sankey charts. Each time you execute your notebook, Zepl generates a new container, ensuring a consistent environment for your model runs. Collaborate with teammates in a shared workspace in real time, or leave feedback on notebooks for asynchronous communication. Utilize precise access controls to manage how your work is shared, granting others read, edit, and execute permissions to facilitate teamwork and distribution. All notebooks benefit from automatic saving and version control, allowing you to easily name, oversee, and revert to previous versions through a user-friendly interface, along with smooth exporting capabilities to Github. Additionally, the platform supports integration with external tools, further streamlining your workflow and enhancing productivity.

AIXON is a comprehensive data science platform designed to integrate and enhance your existing customer information, allowing for a deeper understanding of your audience while enabling AI models to forecast their future behaviors effortlessly. By augmenting profiles with both internal data and external insights, you can achieve a well-rounded perspective of your users. The AI capabilities quickly identify the most effective marketing patterns, allowing you to act swiftly with insights generated for all communication channels. AIXON assembles a 360-degree view of your audience by consolidating data from various sources, including apps, websites, and CRM systems. By merging this information with users' external digital footprints sourced from Appier’s unique cross-screen database, you can significantly enrich your audience profiles. You can utilize pre-existing AI models or develop your own to create impactful predictions in just minutes. The platform also allows for the creation of audience segments based on user interests or personas, enabling you to discover lookalikes, analyze different audiences, and anticipate actions such as conversions. Overall, AIXON empowers businesses to harness data effectively, drive targeted marketing efforts, and achieve better outcomes through informed decision-making.

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.

ROBIN is the first hyper-converged Kubernetes platform in the industry for big data, databases and AI/ML. The platform offers a self-service App store experience to deploy any application anywhere. It runs on-premises in your private cloud or in public-cloud environments (AWS, Azure and GCP). Hyper-converged Kubernetes combines containerized storage and networking with compute (Kubernetes) and the application management layer to create a single system. Our approach extends Kubernetes to data-intensive applications like Hortonworks, Cloudera and Elastic stack, RDBMSs, NoSQL database, and AI/ML. Facilitates faster and easier roll-out of important Enterprise IT and LoB initiatives such as containerization and cloud-migration, cost consolidation, productivity improvement, and cost-consolidation. This solution addresses the fundamental problems of managing big data and databases in Kubernetes.

SAS Visual Statistics allows for collaborative data exploration among multiple users, enabling them to interactively develop and refine predictive models. Data scientists and statisticians can leverage the most suitable analytical techniques to act on insights at a detailed level. Consequently, you will discover insights at remarkable speeds, uncovering new opportunities for revenue growth. The platform facilitates the construction and fine-tuning of models aimed at specific demographics or segments while simultaneously running various scenarios. This capability encourages users to pose numerous what-if questions to enhance outcomes. Additionally, results can be operationalized through automatically generated score code. Users are empowered to visually manipulate data by adding or adjusting variables, eliminating outliers, and more. Changes can be instantly assessed for their impact on the model's predictive accuracy, allowing for swift adjustments. Data science teams enjoy the ultimate flexibility by working in their preferred programming languages, maximizing their expertise. Ultimately, SAS Visual Statistics integrates all analytical resources, making it a comprehensive solution for data-driven decision-making. It fosters an environment where innovation can thrive, pushing the boundaries of what data analysis can achieve.