Best Business Intelligence Software for TensorFlow

Find and compare the best Business Intelligence software for TensorFlow in 2024

Use the comparison tool below to compare the top Business Intelligence software for TensorFlow on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.

  • 1
    Qloo Reviews
    Top Pick
    See Software
    Learn More
    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.
  • 2
    Flex83 Reviews

    Flex83

    IoT83

    $200 per month
    2 Ratings
    Flex83 Application Enablement Platform enables you to reimagine IoT innovation. You can create compelling and powerful IoT solutions faster than ever before, and at a fraction the cost. - Use no-code workflows to build professional-grade connect/monitor/analyze/manage solutions fast. - Connect to virtually any device with low-code tools, add custom business logic, create custom dashboards and launch multiple applications. - Use the SaaS model to build and prove your solution. Then scale using a "pay-as-you-grow" model. With the right tools and workflows, you can create IoT applications that are sophisticated in a matter of hours. This allows you to quickly build what your customers or business need, without worrying about lengthy development cycles, underlying complexity or large budgets. You can iteratively improve your solution to expand your capabilities and drive greater customer value. The Flex83 platform has been tested on 65M devices. Flex83 is worth a try!
  • 3
    Deepnote Reviews
    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.
  • 4
    RazorThink Reviews
    RZT aiOS provides all the benefits of a unified AI platform, and more. It's not just a platform, it's an Operating System that connects, manages, and unifies all your AI initiatives. AI developers can now do what used to take months in days thanks to aiOS process management which dramatically increases their productivity. This Operating System provides an intuitive environment for AI development. It allows you to visually build models, explore data and create processing pipelines. You can also run experiments and view analytics. It's easy to do all of this without any advanced software engineering skills.
  • 5
    GigaSpaces Reviews
    Smart DIH is a data management platform that quickly serves applications with accurate, fresh and complete data, delivering high performance, ultra-low latency, and an always-on digital experience. Smart DIH decouples APIs from SoRs, replicating critical data, and making it available using event-driven architecture. Smart DIH enables drastically shorter development cycles of new digital services, and rapidly scales to serve millions of concurrent users – no matter which IT infrastructure or cloud topologies it relies on. XAP Skyline is a distributed in-memory development platform that delivers transactional consistency, combined with extreme event-based processing and microsecond latency. The platform fuels core business solutions that rely on instantaneous data, including online trading, real-time risk management and data processing for AI and large language models.
  • 6
    Databricks Data Intelligence Platform Reviews
    The Databricks Data Intelligence Platform enables your entire organization to utilize data and AI. It is built on a lakehouse that provides an open, unified platform for all data and governance. It's powered by a Data Intelligence Engine, which understands the uniqueness in your data. Data and AI companies will win in every industry. Databricks can help you achieve your data and AI goals faster and easier. Databricks combines the benefits of a lakehouse with generative AI to power a Data Intelligence Engine which understands the unique semantics in your data. The Databricks Platform can then optimize performance and manage infrastructure according to the unique needs of your business. The Data Intelligence Engine speaks your organization's native language, making it easy to search for and discover new data. It is just like asking a colleague a question.
  • 7
    IBM Watson Studio Reviews
    You can build, run, and manage AI models and optimize decisions across any cloud. IBM Watson Studio allows you to deploy AI anywhere with IBM Cloud Pak®, the IBM data and AI platform. Open, flexible, multicloud architecture allows you to unite teams, simplify the AI lifecycle management, and accelerate time-to-value. ModelOps pipelines automate the AI lifecycle. AutoAI accelerates data science development. AutoAI allows you to create and programmatically build models. One-click integration allows you to deploy and run models. Promoting AI governance through fair and explicable AI. Optimizing decisions can improve business results. Open source frameworks such as PyTorch and TensorFlow can be used, as well as scikit-learn. You can combine the development tools, including popular IDEs and Jupyter notebooks. JupterLab and CLIs. This includes languages like Python, R, and Scala. IBM Watson Studio automates the management of the AI lifecycle to help you build and scale AI with trust.
  • 8
    Deep.BI Reviews
    Deep.BI allows media, insurance, E-commerce, and banking enterprises to increase their revenues by anticipating user behavior and automating actions to convert them to paying customers. Deep.BI's next-generation enterprise data warehouse provides predictive customer data platforms with real-time user scoring. We help digital platforms and businesses improve their products, content, and distribution. Deep.BI's platform gathers vast amounts of data about product usage and consumption, and provides real-time and actionable insights. The Deep.Conveyor data pipeline generates real-time, actionable insights in seconds. These insights can be augmented by the Deep.Score event scoring platform built with custom AI algorithms. They are also available for analysis in Deep.Explorer's business intelligence platform.
  • 9
    Zepl Reviews
    All work can be synced, searched and managed across your data science team. Zepl's powerful search allows you to discover and reuse models, code, and other data. Zepl's enterprise collaboration platform allows you to query data from Snowflake or Athena and then build your models in Python. For enhanced interactions with your data, use dynamic forms and pivoting. Zepl creates new containers every time you open your notebook. This ensures that you have the same image each time your models are run. You can invite your team members to join you in a shared space, and they will be able to work together in real-time. Or they can simply leave comments on a notebook. You can share your work with fine-grained access controls. You can allow others to read, edit, run, and share your work. This will facilitate collaboration and distribution. All notebooks can be saved and versioned automatically. An easy-to-use interface allows you to name, manage, roll back, and roll back all versions. You can also export seamlessly into Github.
  • Previous
  • You're on page 1
  • Next