Best Artificial Intelligence Software for Keras
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Compare the Top Artificial Intelligence Software that integrates with Keras as of June 2025
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This a list of Artificial Intelligence software that integrates with Keras. Use the filters on the left to add additional filters for products that have integrations with Keras. View the products that work with Keras in the table below.
What is Artificial Intelligence Software for Keras?
Artificial Intelligence (AI) software is computer technology designed to simulate human intelligence. It can be used to perform tasks that require cognitive abilities, such as problem-solving, data analysis, visual perception and language translation. AI applications range from voice recognition and virtual assistants to autonomous vehicles and medical diagnostics. Compare and read user reviews of the best Artificial Intelligence software for Keras currently available using the table below. This list is updated regularly.
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1
TensorFlow
TensorFlow
An end-to-end open source machine learning platform. TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML powered applications. Build and train ML models easily using intuitive high-level APIs like Keras with eager execution, which makes for immediate model iteration and easy debugging. Easily train and deploy models in the cloud, on-prem, in the browser, or on-device no matter what language you use. A simple and flexible architecture to take new ideas from concept to code, to state-of-the-art models, and to publication faster. Build, deploy, and experiment easily with TensorFlow.Starting Price: Free -
2
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. -
3
OpenVINO
Intel
The Intel® Distribution of OpenVINO™ toolkit is an open-source AI development toolkit that accelerates inference across Intel hardware platforms. Designed to streamline AI workflows, it allows developers to deploy optimized deep learning models for computer vision, generative AI, and large language models (LLMs). With built-in tools for model optimization, the platform ensures high throughput and lower latency, reducing model footprint without compromising accuracy. OpenVINO™ is perfect for developers looking to deploy AI across a range of environments, from edge devices to cloud servers, ensuring scalability and performance across Intel architectures.Starting Price: Free -
4
Gradient
Gradient
Explore a new library or dataset in a notebook. Automate preprocessing, training, or testing with a 2orkflow. Bring your application to life with a deployment. Use notebooks, workflows, and deployments together or independently. Compatible with everything. Gradient supports all major frameworks and libraries. Gradient is powered by Paperspace's world-class GPU instances. Move faster with source control integration. Connect to GitHub to manage all your work & compute resources with git. Launch a GPU-enabled Jupyter Notebook from your browser in seconds. Use any library or framework. Easily invite collaborators or share a public link. A simple cloud workspace that runs on free GPUs. Get started in seconds with a notebook environment that's easy to use and share. Perfect for ML developers. A powerful no-fuss environment with loads of features that just works. Choose a pre-built template or bring your own. Try a free GPU!Starting Price: $8 per month -
5
BentoML
BentoML
Serve your ML model in any cloud in minutes. Unified model packaging format enabling both online and offline serving on any platform. 100x the throughput of your regular flask-based model server, thanks to our advanced micro-batching mechanism. Deliver high-quality prediction services that speak the DevOps language and integrate perfectly with common infrastructure tools. Unified format for deployment. High-performance model serving. DevOps best practices baked in. The service uses the BERT model trained with the TensorFlow framework to predict movie reviews' sentiment. DevOps-free BentoML workflow, from prediction service registry, deployment automation, to endpoint monitoring, all configured automatically for your team. A solid foundation for running serious ML workloads in production. Keep all your team's models, deployments, and changes highly visible and control access via SSO, RBAC, client authentication, and auditing logs.Starting Price: Free -
6
neptune.ai
neptune.ai
Neptune.ai is a machine learning operations (MLOps) platform designed to streamline the tracking, organizing, and sharing of experiments and model-building processes. It provides a comprehensive environment for data scientists and machine learning engineers to log, visualize, and compare model training runs, datasets, hyperparameters, and metrics in real-time. Neptune.ai integrates easily with popular machine learning libraries, enabling teams to efficiently manage both research and production workflows. With features that support collaboration, versioning, and experiment reproducibility, Neptune.ai enhances productivity and helps ensure that machine learning projects are transparent and well-documented across their lifecycle.Starting Price: $49 per month -
7
Comet
Comet
Manage and optimize models across the entire ML lifecycle, from experiment tracking to monitoring models in production. Achieve your goals faster with the platform built to meet the intense demands of enterprise teams deploying ML at scale. Supports your deployment strategy whether it’s private cloud, on-premise servers, or hybrid. Add two lines of code to your notebook or script and start tracking your experiments. Works wherever you run your code, with any machine learning library, and for any machine learning task. Easily compare experiments—code, hyperparameters, metrics, predictions, dependencies, system metrics, and more—to understand differences in model performance. Monitor your models during every step from training to production. Get alerts when something is amiss, and debug your models to address the issue. Increase productivity, collaboration, and visibility across all teams and stakeholders.Starting Price: $179 per user per month -
8
Superwise
Superwise
Get in minutes what used to take years to build. Simple, customizable, scalable, secure, ML monitoring. Everything you need to deploy, maintain and improve ML in production. Superwise is an open platform that integrates with any ML stack and connects to your choice of communication tools. Want to take it further? Superwise is API-first and everything (and we mean everything) is accessible via our APIs. All from the comfort of the cloud of your choice. When it comes to ML monitoring you have full self-service control over everything. Configure metrics and policies through our APIs and SDK or simply select a monitoring template and set the sensitivity, conditions, and alert channels of your choice. Try Superwise out or contact us to learn more. Easily create alerts with Superwise’s ML monitoring policy templates and builder. Select from dozens of pre-build monitors ranging from data drift to equal opportunity, or customize policies to incorporate your domain expertise.Starting Price: Free -
9
Akira AI
Akira AI
Akira.ai provides businesses with Agentic AI, a set of specialized AI agents designed to optimize and automate complex workflows across various industries. These AI agents collaborate with human teams, enhancing productivity, making real-time decisions, and automating repetitive tasks, such as data analysis, incident management, and HR processes. The platform integrates smoothly with existing systems, including CRMs and ERPs, ensuring a disruption-free transition to AI-enhanced operations. Akira’s AI agents help businesses streamline their operations, increase decision-making speed, and boost overall efficiency, driving innovation across sectors like manufacturing, finance, and IT.Starting Price: $15 per month -
10
Guild AI
Guild AI
Guild AI is an open-source experiment tracking toolkit designed to bring systematic control to machine learning workflows, enabling users to build better models faster. It automatically captures every detail of training runs as unique experiments, facilitating comprehensive tracking and analysis. Users can compare and analyze runs to deepen their understanding and incrementally improve models. Guild AI simplifies hyperparameter tuning by applying state-of-the-art algorithms through straightforward commands, eliminating the need for complex trial setups. It also supports the automation of pipelines, accelerating model development, reducing errors, and providing measurable results. The toolkit is platform-agnostic, running on all major operating systems and integrating seamlessly with existing software engineering tools. Guild AI supports various remote storage types, including Amazon S3, Google Cloud Storage, Azure Blob Storage, and SSH servers.Starting Price: Free -
11
Google AI Edge
Google
Google AI Edge offers a comprehensive suite of tools and frameworks designed to facilitate the deployment of artificial intelligence across mobile, web, and embedded applications. By enabling on-device processing, it reduces latency, allows offline functionality, and ensures data remains local and private. It supports cross-platform compatibility, allowing the same model to run seamlessly across embedded systems. It is also multi-framework compatible, working with models from JAX, Keras, PyTorch, and TensorFlow. Key components include low-code APIs for common AI tasks through MediaPipe, enabling quick integration of generative AI, vision, text, and audio functionalities. Visualize the transformation of your model through conversion and quantification. Overlays the results of the comparisons to debug the hotspots. Explore, debug, and compare your models visually. Overlays comparisons and numerical performance data to identify problematic hotspots.Starting Price: Free -
12
Flower
Flower
Flower is an open source federated learning framework designed to simplify the development and deployment of machine learning models across decentralized data sources. It enables training on data located on devices or servers without transferring the data itself, thereby enhancing privacy and reducing bandwidth usage. Flower supports a wide range of machine learning frameworks, including PyTorch, TensorFlow, Hugging Face Transformers, scikit-learn, and XGBoost, and is compatible with various platforms and cloud services like AWS, GCP, and Azure. It offers flexibility through customizable strategies and supports both horizontal and vertical federated learning scenarios. Flower's architecture allows for scalable experiments, with the capability to handle workloads involving tens of millions of clients. It also provides built-in support for privacy-preserving techniques like differential privacy and secure aggregation.Starting Price: Free -
13
RazorThink
RazorThink
RZT aiOS offers all of the benefits of a unified artificial intelligence platform and more, because it's not just a platform — it's a comprehensive Operating System that fully connects, manages and unifies all of your AI initiatives. And, AI developers now can do in days what used to take them months, because aiOS process management dramatically increases the productivity of AI teams. This Operating System offers an intuitive environment for AI development, letting you visually build models, explore data, create processing pipelines, run experiments, and view analytics. What's more is that you can do it all even without advanced software engineering skills. -
14
Intel Tiber AI Studio
Intel
Intel® Tiber™ AI Studio is a comprehensive machine learning operating system that unifies and simplifies the AI development process. The platform supports a wide range of AI workloads, providing a hybrid and multi-cloud infrastructure that accelerates ML pipeline development, model training, and deployment. With its native Kubernetes orchestration and meta-scheduler, Tiber™ AI Studio offers complete flexibility in managing on-prem and cloud resources. Its scalable MLOps solution enables data scientists to easily experiment, collaborate, and automate their ML workflows while ensuring efficient and cost-effective utilization of resources. -
15
MLReef
MLReef
MLReef enables domain experts and data scientists to securely collaborate via a hybrid of pro-code & no-code development approaches. 75% increase in productivity due to distributed workloads. This enables teams to complete more ML projects faster. Domain experts and data scientists collaborate on the same platform reducing 100% of unnecessary communication ping-pong. MLReef works on your premises and uniquely enables 100% reproducibility and continuity. Rebuild all work at any time. You can use already well-known and established git repositories to create explorable, interoperable, and versioned AI modules. AI Modules created by your data scientists become drag-and-drop elements. These are adjustable by parameters, versioned, interoperable, and explorable within your entire organization. Data handling often requires expert knowledge that a single data scientist often lacks. MLReef enables your field experts to relieve your data processing task, reducing complexities. -
16
Cameralyze
Cameralyze
Empower your product with AI. Our platform offers a vast selection of pre-built models and a user-friendly no-code interface for custom models. Integrate AI seamlessly into your application and gain a competitive edge. Sentiment analysis, also known as opinion mining, is the process of extracting subjective information from text data, such as reviews, social media posts, or customer feedback, and categorizing it as positive, negative, or neutral. This technology has gained increasing importance in recent years, as more and more companies are using it to understand their customers' opinions and needs, and to make data-driven decisions that can improve their products, services, and marketing strategies. Sentiment analysis is a powerful technology that helps companies understand customer feedback and make data-driven decisions to improve their products, services, and marketing strategies.Starting Price: $29 per month -
17
Horovod
Horovod
Horovod was originally developed by Uber to make distributed deep learning fast and easy to use, bringing model training time down from days and weeks to hours and minutes. With Horovod, an existing training script can be scaled up to run on hundreds of GPUs in just a few lines of Python code. Horovod can be installed on-premise or run out-of-the-box in cloud platforms, including AWS, Azure, and Databricks. Horovod can additionally run on top of Apache Spark, making it possible to unify data processing and model training into a single pipeline. Once Horovod has been configured, the same infrastructure can be used to train models with any framework, making it easy to switch between TensorFlow, PyTorch, MXNet, and future frameworks as machine learning tech stacks continue to evolve.Starting Price: Free -
18
Comet LLM
Comet LLM
CometLLM is a tool to log and visualize your LLM prompts and chains. Use CometLLM to identify effective prompt strategies, streamline your troubleshooting, and ensure reproducible workflows. Log your prompts and responses, including prompt template, variables, timestamps and duration, and any metadata that you need. Visualize your prompts and responses in the UI. Log your chain execution down to the level of granularity that you need. Visualize your chain execution in the UI. Automatically tracks your prompts when using the OpenAI chat models. Track and analyze user feedback. Diff your prompts and chain execution in the UI. Comet LLM Projects have been designed to support you in performing smart analysis of your logged prompt engineering workflows. Each column header corresponds to a metadata attribute logged in the LLM project, so the exact list of the displayed default headers can vary across projects.Starting Price: Free -
19
Gemma 3
Google
Gemma 3, introduced by Google, is a new AI model built on the Gemini 2.0 architecture, designed to offer enhanced performance and versatility. This model is capable of running efficiently on a single GPU or TPU, making it accessible for a wide range of developers and researchers. Gemma 3 focuses on improving natural language understanding, generation, and other AI-driven tasks. By offering scalable, powerful AI capabilities, Gemma 3 aims to advance the development of AI systems across various industries and use cases.Starting Price: Free -
20
Dragonfly 3D World
Dragonfly
Dragonfly 3D World by Object Research Systems (ORS) is a comprehensive software platform for multidimensional image visualization, analysis, and collaboration in scientific and industrial fields. It provides powerful tools to visualize, process, and interpret 2D, 3D, and 4D imaging data acquired through modalities such as CT, MRI, electron microscopy, and more. Dragonfly supports real-time volume rendering, surface rendering, and orthogonal slicing, allowing users to explore complex structures interactively. With its AI integration, users can apply deep learning for image segmentation, classification, and object detection. It offers advanced quantitative analysis tools, including region-of-interest analysis, measurements, and statistical evaluations. Its intuitive graphical user interface enables researchers to build reproducible workflows and perform batch processing. -
21
Gemma 3n
Google DeepMind
Gemma 3n is our state-of-the-art open multimodal model, engineered for on-device performance and efficiency. Made for responsive, low-footprint local inference, Gemma 3n empowers a new wave of intelligent, on-the-go applications. It analyzes and responds to combined images and text, with video and audio coming soon. Build intelligent, interactive features that put user privacy first and work reliably offline. Mobile-first architecture, with a significantly reduced memory footprint. Co-designed by Google's mobile hardware teams and industry leaders. 4B active memory footprint with the ability to create submodels for quality-latency tradeoffs. Gemma 3n is our first open model built on this groundbreaking, shared architecture, allowing developers to begin experimenting with this technology today in an early preview. -
22
Databricks Data Intelligence Platform
Databricks
The Databricks Data Intelligence Platform allows your entire organization to use data and AI. It’s built on a lakehouse to provide an open, unified foundation for all data and governance, and is powered by a Data Intelligence Engine that understands the uniqueness of your data. The winners in every industry will be data and AI companies. From ETL to data warehousing to generative AI, Databricks helps you simplify and accelerate your data and AI goals. Databricks combines generative AI with the unification benefits of a lakehouse to power a Data Intelligence Engine that understands the unique semantics of your data. This allows the Databricks Platform to automatically optimize performance and manage infrastructure in ways unique to your business. The Data Intelligence Engine understands your organization’s language, so search and discovery of new data is as easy as asking a question like you would to a coworker. -
23
Weights & Biases
Weights & Biases
Experiment tracking, hyperparameter optimization, model and dataset versioning with Weights & Biases (WandB). Track, compare, and visualize ML experiments with 5 lines of code. Add a few lines to your script, and each time you train a new version of your model, you'll see a new experiment stream live to your dashboard. Optimize models with our massively scalable hyperparameter search tool. Sweeps are lightweight, fast to set up, and plug in to your existing infrastructure for running models. Save every detail of your end-to-end machine learning pipeline — data preparation, data versioning, training, and evaluation. It's never been easier to share project updates. Quickly and easily implement experiment logging by adding just a few lines to your script and start logging results. Our lightweight integration works with any Python script. W&B Weave is here to help developers build and iterate on their AI applications with confidence. -
24
MLflow
MLflow
MLflow is an open source platform to manage the ML lifecycle, including experimentation, reproducibility, deployment, and a central model registry. MLflow currently offers four components. Record and query experiments: code, data, config, and results. Package data science code in a format to reproduce runs on any platform. Deploy machine learning models in diverse serving environments. Store, annotate, discover, and manage models in a central repository. The MLflow Tracking component is an API and UI for logging parameters, code versions, metrics, and output files when running your machine learning code and for later visualizing the results. MLflow Tracking lets you log and query experiments using Python, REST, R API, and Java API APIs. An MLflow Project is a format for packaging data science code in a reusable and reproducible way, based primarily on conventions. In addition, the Projects component includes an API and command-line tools for running projects. -
25
TruEra
TruEra
A machine learning monitoring solution that helps you easily oversee and troubleshoot high model volumes. With explainability accuracy that’s unparalleled and unique analyses that are not available anywhere else, data scientists avoid false alarms and dead ends, addressing critical problems quickly and effectively. Your machine learning models stay optimized, so that your business is optimized. TruEra’s solution is based on an explainability engine that, due to years of dedicated research and development, is significantly more accurate than current tools. TruEra’s enterprise-class AI explainability technology is without peer. The core diagnostic engine is based on six years of research at Carnegie Mellon University and dramatically outperforms competitors. The platform quickly performs sophisticated sensitivity analysis that enables data scientists, business users, and risk and compliance teams to understand exactly how and why a model makes predictions. -
26
teX.ai
teX.ai
Given the sea of content, your business generates, identifies, and processes only text that is of interest to you, quickly, accurately, and efficiently. Regardless of your business needs, operational agility, faster decisions, obtaining customer insights or more, teXai, a Forbes recognized text analytics company, helps you take advantage of text to propel your business forward. teXai's powerful customizable preprocessor engine identifies and extracts objects of your interest in the nooks and crannies of your organization’s emails, text messages, tables, website, social media, archives, or any documents of your choice. Its intelligent customizable linguistic application identifies text genre, groups, similar content and creates concise summaries so that your business teams can obtain the right context from the right text. The easy-to-use text analytics software extracts the essence of your text and simplifies the decision-making process. -
27
StreamFlux
Fractal
Data is crucial when it comes to building, streamlining and growing your business. However, getting the full value out of data can be a challenge, many organizations are faced with poor access to data, incompatible tools, spiraling costs and slow results. Simply put, leaders who can turn raw data into real results will thrive in today’s landscape. The key to this is empowering everyone across your business to be able to analyze, build and collaborate on end-to-end AI and machine learning solutions in one place, fast. Streamflux is a one-stop shop to meet your data analytics and AI challenges. Our self-serve platform allows you the freedom to build end-to-end data solutions, uses models to answer complex questions and assesses user behaviors. Whether you’re predicting customer churn and future revenue, or generating recommendations, you can go from raw data to genuine business impact in days, not months. -
28
Polyaxon
Polyaxon
A Platform for reproducible and scalable Machine Learning and Deep Learning applications. Learn more about the suite of features and products that underpin today's most innovative platform for managing data science workflows. Polyaxon provides an interactive workspace with notebooks, tensorboards, visualizations,and dashboards. Collaborate with the rest of your team, share and compare experiments and results. Reproducible results with a built-in version control for code and experiments. Deploy Polyaxon in the cloud, on-premises or in hybrid environments, including single laptop, container management platforms, or on Kubernetes. Spin up or down, add more nodes, add more GPUs, and expand storage. -
29
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. -
30
Graphcore
Graphcore
Build, train and deploy your models in the cloud, using the latest IPU AI systems and the frameworks you love, with our cloud partners. Allowing you to save on compute costs and seamlessly scale to massive IPU compute when you need it. Get started with IPUs today with on-demand pricing and free tier offerings with our cloud partners. We believe our Intelligence Processing Unit (IPU) technology will become the worldwide standard for machine intelligence compute. The Graphcore IPU is going to be transformative across all industries and sectors with a real potential for positive societal impact from drug discovery and disaster recovery to decarbonization. The IPU is a completely new processor, specifically designed for AI compute. The IPU’s unique architecture lets AI researchers undertake entirely new types of work, not possible using current technologies, to drive the next advances in machine intelligence.