Alternatives to Gradio
Compare Gradio alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Gradio in 2026. Compare features, ratings, user reviews, pricing, and more from Gradio competitors and alternatives in order to make an informed decision for your business.
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1
Vertex AI
Google
Build, deploy, and scale machine learning (ML) models faster, with fully managed ML tools for any use case. Through Vertex AI Workbench, Vertex AI is natively integrated with BigQuery, Dataproc, and Spark. You can use BigQuery ML to create and execute machine learning models in BigQuery using standard SQL queries on existing business intelligence tools and spreadsheets, or you can export datasets from BigQuery directly into Vertex AI Workbench and run your models from there. Use Vertex Data Labeling to generate highly accurate labels for your data collection. Vertex AI Agent Builder enables developers to create and deploy enterprise-grade generative AI applications. It offers both no-code and code-first approaches, allowing users to build AI agents using natural language instructions or by leveraging frameworks like LangChain and LlamaIndex. -
2
Google Cloud BigQuery
Google
BigQuery is a serverless, multicloud data warehouse that simplifies the process of working with all types of data so you can focus on getting valuable business insights quickly. At the core of Google’s data cloud, BigQuery allows you to simplify data integration, cost effectively and securely scale analytics, share rich data experiences with built-in business intelligence, and train and deploy ML models with a simple SQL interface, helping to make your organization’s operations more data-driven. Gemini in BigQuery offers AI-driven tools for assistance and collaboration, such as code suggestions, visual data preparation, and smart recommendations designed to boost efficiency and reduce costs. BigQuery delivers an integrated platform featuring SQL, a notebook, and a natural language-based canvas interface, catering to data professionals with varying coding expertise. This unified workspace streamlines the entire analytics process. -
3
RunPod
RunPod
RunPod offers a cloud-based platform designed for running AI workloads, focusing on providing scalable, on-demand GPU resources to accelerate machine learning (ML) model training and inference. With its diverse selection of powerful GPUs like the NVIDIA A100, RTX 3090, and H100, RunPod supports a wide range of AI applications, from deep learning to data processing. The platform is designed to minimize startup time, providing near-instant access to GPU pods, and ensures scalability with autoscaling capabilities for real-time AI model deployment. RunPod also offers serverless functionality, job queuing, and real-time analytics, making it an ideal solution for businesses needing flexible, cost-effective GPU resources without the hassle of managing infrastructure. -
4
Google Cloud Vision AI
Google
Derive insights from your images in the cloud or at the edge with AutoML Vision or use pre-trained Vision API models to detect emotion, understand text, and more. Google Cloud offers two computer vision products that use machine learning to help you understand your images with industry-leading prediction accuracy. Automate the training of your own custom machine learning models. Simply upload images and train custom image models with AutoML Vision’s easy-to-use graphical interface; optimize your models for accuracy, latency, and size; and export them to your application in the cloud, or to an array of devices at the edge. Google Cloud’s Vision API offers powerful pre-trained machine learning models through REST and RPC APIs. Assign labels to images and quickly classify them into millions of predefined categories. Detect objects and faces, read printed and handwritten text, and build valuable metadata into your image catalog. -
5
Dialogflow
Google
Dialogflow from Google Cloud is a natural language understanding platform that makes it easy to design and integrate a conversational user interface into your mobile app, web application, device, bot, interactive voice response system, and so on. Using Dialogflow, you can provide new and engaging ways for users to interact with your product. Dialogflow can analyze multiple types of input from your customers, including text or audio inputs (like from a phone or voice recording). It can also respond to your customers in a couple of ways, either through text or with synthetic speech. Dialogflow CX and ES provide virtual agent services for chatbots and contact centers. If you have a contact center that employs human agents, you can use Agent Assist to help your human agents. Agent Assist provides real-time suggestions for human agents while they are in conversations with end-user customers. -
6
Amazon SageMaker
Amazon
Amazon SageMaker is an advanced machine learning service that provides an integrated environment for building, training, and deploying machine learning (ML) models. It combines tools for model development, data processing, and AI capabilities in a unified studio, enabling users to collaborate and work faster. SageMaker supports various data sources, such as Amazon S3 data lakes and Amazon Redshift data warehouses, while ensuring enterprise security and governance through its built-in features. The service also offers tools for generative AI applications, making it easier for users to customize and scale AI use cases. SageMaker’s architecture simplifies the AI lifecycle, from data discovery to model deployment, providing a seamless experience for developers. -
7
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 -
8
NiceGUI
NiceGUI
NiceGUI is an open source Python library that enables developers to create web-based graphical user interfaces (GUIs) using only Python code. It provides a gentle learning curve while still offering the option for advanced customizations. NiceGUI follows a backend-first philosophy: it handles all the web development details, allowing developers to focus on writing Python code. This makes it ideal for a wide range of projects, including short scripts, dashboards, robotics projects, IoT solutions, smart home automation, and machine learning. The framework is built on FastAPI for backend operations, Vue.js for frontend interaction, and Tailwind CSS for styling. Developers can create buttons, dialogs, Markdown, 3D scenes, plots, and more, all within a Python environment. NiceGUI supports real-time interactivity through WebSocket connections, enabling instant updates in the browser without page reloads. It offers a variety of components and layout options, such as rows, columns, etc.Starting Price: Free -
9
Open WebUI
Open WebUI
Open WebUI is an extensible, feature-rich, and user-friendly self-hosted AI platform designed to operate entirely offline. It supports various LLM runners like Ollama and OpenAI-compatible APIs, with a built-in inference engine for Retrieval Augmented Generation (RAG), making it a powerful AI deployment solution. Key features include effortless setup via Docker or Kubernetes, seamless integration with OpenAI-compatible APIs, granular permissions and user groups for enhanced security, responsive design across devices, and full Markdown and LaTeX support for enriched interactions. Additionally, Open WebUI offers a Progressive Web App (PWA) for mobile devices, providing offline access and a native app-like experience. The platform also includes a Model Builder, allowing users to create custom models from base Ollama models directly within the interface. With over 156,000 users, Open WebUI is a versatile solution for deploying and managing AI models in a secure, offline environment. -
10
ComfyUI
ComfyUI
ComfyUI is a free and open source node-based application for generative AI, enabling users to build, create, and share without limits. It allows for the extension of functionality through custom nodes, letting users tailor workflows to their specific needs. Designed for performance, ComfyUI runs workflows directly on local machines, offering faster iteration, lower costs, and complete control. The visual interface provides full control by connecting nodes on a canvas, allowing for branching, remixing, and adjusting every part of the workflow at any time. Workflows can be saved, shared, and reused effortlessly, with exported media carrying metadata to instantly rebuild the full workflow. Users can see results in real-time as they adjust workflows, facilitating faster iteration with instant visual feedback. ComfyUI supports the generation of various media types, including images, videos, 3D assets, and audio.Starting Price: Free -
11
Fooocus
lllyasviel
Fooocus is an open source, offline image generation software built on Gradio and powered by Stable Diffusion XL (SDXL). Designed for simplicity, it minimizes manual tweaking, users focus on prompts while the system handles the rest. Fooocus includes an offline GPT-2-based prompt enhancement engine and sampling improvements, ensuring high-quality outputs from both short and long prompts. It supports features like inpainting, outpainting, upscaling, and image prompting, utilizing its own algorithms for superior results compared to standard SDXL methods. The software offers various presets, including anime and realistic modes, and allows for advanced customization through an intuitive interface. Installation is straightforward, with minimal clicks required, and it runs on systems with at least 4GB of NVIDIA GPU memory. Fooocus is in a state of limited long-term support, focusing on bug fixes, with no current plans to adopt newer model architectures.Starting Price: Free -
12
Chainlit
Chainlit
Chainlit is an open-source Python package designed to expedite the development of production-ready conversational AI applications. With Chainlit, developers can build and deploy chat-based interfaces in minutes, not weeks. The platform offers seamless integration with popular AI tools and frameworks, including OpenAI, LangChain, and LlamaIndex, allowing for versatile application development. Key features of Chainlit include multimodal capabilities, enabling the processing of images, PDFs, and other media types to enhance productivity. It also provides robust authentication options, supporting integration with providers like Okta, Azure AD, and Google. The Prompt Playground feature allows developers to iterate on prompts in context, adjusting templates, variables, and LLM settings for optimal results. For observability, Chainlit offers real-time visualization of prompts, completions, and usage metrics, ensuring efficient and trustworthy LLM operations. -
13
Alibaba Cloud Machine Learning Platform for AI
Alibaba Cloud
An end-to-end platform that provides various machine learning algorithms to meet your data mining and analysis requirements. Machine Learning Platform for AI provides end-to-end machine learning services, including data processing, feature engineering, model training, model prediction, and model evaluation. Machine learning platform for AI combines all of these services to make AI more accessible than ever. Machine Learning Platform for AI provides a visualized web interface allowing you to create experiments by dragging and dropping different components to the canvas. Machine learning modeling is a simple, step-by-step procedure, improving efficiencies and reducing costs when creating an experiment. Machine Learning Platform for AI provides more than one hundred algorithm components, covering such scenarios as regression, classification, clustering, text analysis, finance, and time series.Starting Price: $1.872 per hour -
14
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. -
15
Hugging Face
Hugging Face
Hugging Face is a leading platform for AI and machine learning, offering a vast hub for models, datasets, and tools for natural language processing (NLP) and beyond. The platform supports a wide range of applications, from text, image, and audio to 3D data analysis. Hugging Face fosters collaboration among researchers, developers, and companies by providing open-source tools like Transformers, Diffusers, and Tokenizers. It enables users to build, share, and access pre-trained models, accelerating AI development for a variety of industries.Starting Price: $9 per month -
16
Hive AutoML
Hive
Build and deploy deep learning models for custom use cases. Our automated machine learning process allows customers to create powerful AI solutions built on our best-in-class models and tailored to the specific challenges they face. Digital platforms can quickly create models specifically made to fit their guidelines and needs. Build large language models for specialized use cases such as customer and technical support bots. Create image classification models to better understand image libraries for search, organization, and more. -
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Teachable Machine
Teachable Machine
A fast, easy way to create machine learning models for your sites, apps, and more – no expertise or coding required. Teachable Machine is flexible – use files or capture examples live. It’s respectful of the way you work. You can even choose to use it entirely on-device, without any webcam or microphone data leaving your computer. Teachable Machine is a web-based tool that makes creating machine learning models fast, easy, and accessible to everyone. Educators, artists, students, innovators, makers of all kinds – really, anyone who has an idea they want to explore. No prerequisite machine learning knowledge required. You train a computer to recognize your images, sounds, and poses without writing any machine learning code. Then, use your model in your own projects, sites, apps, and more. -
18
Vertex AI Notebooks
Google
Vertex AI Notebooks is a fully managed, scalable solution from Google Cloud that accelerates machine learning (ML) development. It provides a seamless, interactive environment for data scientists and developers to explore data, prototype models, and collaborate in real-time. With integration into Google Cloud’s vast data and ML tools, Vertex AI Notebooks supports rapid prototyping, automated workflows, and deployment, making it easier to scale ML operations. The platform’s support for both Colab Enterprise and Vertex AI Workbench ensures a flexible and secure environment for diverse enterprise needs.Starting Price: $10 per GB -
19
Azure Machine Learning
Microsoft
Accelerate the end-to-end machine learning lifecycle with Azure Machine Learning Studio. Empower developers and data scientists with a wide range of productive experiences for building, training, and deploying machine learning models faster. Accelerate time to market and foster team collaboration with industry-leading MLOps—DevOps for machine learning. Innovate on a secure, trusted platform, designed for responsible ML. Productivity for all skill levels, with code-first and drag-and-drop designer, and automated machine learning. Robust MLOps capabilities that integrate with existing DevOps processes and help manage the complete ML lifecycle. Responsible ML capabilities – understand models with interpretability and fairness, protect data with differential privacy and confidential computing, and control the ML lifecycle with audit trials and datasheets. Best-in-class support for open-source frameworks and languages including MLflow, Kubeflow, ONNX, PyTorch, TensorFlow, Python, and R. -
20
Predibase
Predibase
Declarative machine learning systems provide the best of flexibility and simplicity to enable the fastest-way to operationalize state-of-the-art models. Users focus on specifying the “what”, and the system figures out the “how”. Start with smart defaults, but iterate on parameters as much as you’d like down to the level of code. Our team pioneered declarative machine learning systems in industry, with Ludwig at Uber and Overton at Apple. Choose from our menu of prebuilt data connectors that support your databases, data warehouses, lakehouses, and object storage. Train state-of-the-art deep learning models without the pain of managing infrastructure. Automated Machine Learning that strikes the balance of flexibility and control, all in a declarative fashion. With a declarative approach, finally train and deploy models as quickly as you want. -
21
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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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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23
ScoopML
ScoopML
Easy-to-Use Build advanced predictive models without math & coding - in just a few clicks. Complete Experience. From cleaning data to building models to making predictions, we provide you all. Trustworthy. Know the 'why' behind AI decisions and drive business with actionable insights. Data Analytics in minutes, without writing code. The total process of building ML algorithms, explaining results, and predicting outcomes in one single click. Machine Learning in 3 Steps. Go from raw data to actionable analytics without writing a single line of code. Upload your data. Ask questions in plain english. Get the best performing model for your data and Share your results. Increase Customer Productivity. We help Companies to leverage no code Machine learning to improve their Customer Experience. -
24
Amazon SageMaker Studio
Amazon
Amazon SageMaker Studio is an integrated development environment (IDE) that provides a single web-based visual interface where you can access purpose-built tools to perform all machine learning (ML) development steps, from preparing data to building, training, and deploying your ML models, improving data science team productivity by up to 10x. You can quickly upload data, create new notebooks, train and tune models, move back and forth between steps to adjust experiments, collaborate seamlessly within your organization, and deploy models to production without leaving SageMaker Studio. Perform all ML development steps, from preparing raw data to deploying and monitoring ML models, with access to the most comprehensive set of tools in a single web-based visual interface. 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. -
25
Deeploy
Deeploy
Deeploy helps you to stay in control of your ML models. Easily deploy your models on our responsible AI platform, without compromising on transparency, control, and compliance. Nowadays, transparency, explainability, and security of AI models is more important than ever. Having a safe and secure environment to deploy your models enables you to continuously monitor your model performance with confidence and responsibility. Over the years, we experienced the importance of human involvement with machine learning. Only when machine learning systems are explainable and accountable, experts and consumers can provide feedback to these systems, overrule decisions when necessary and grow their trust. That’s why we created Deeploy. -
26
Exspanse
Exspanse
Exspanse streamlines the path from development to business value. Build, train & rapidly deploy powerful machine learning models from a single user interface that can scale with your business. Train, tune, and prototype models from the Exspanse Notebook with the help of high-powered GPUs, CPUs & our AI code assistant. Think beyond training & modeling when you can use the rapid deploy feature to deploy models as an API right from an Exspanse Notebook. Clone and publish unique AI projects to DeepSpace AI marketplace to advance the AI community. Power, efficiency, and collaboration in one comprehensive platform. Unleash your full potential as a solo data scientist while maximizing your impact. Manage and accelerate your AI development process through our integrated platform. Turn your innovative ideas into working models quickly and effectively. Seamlessly transition from building to deploying AI solutions, without the need for extensive DevOps knowledge.Starting Price: $50 per month -
27
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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Obviously AI
Obviously AI
The entire process of building machine learning algorithms and predicting outcomes, packed in one single click. Not all data is built to be ready for ML, use the Data Dialog to seamlessly shape your dataset without wrangling your files. Share your prediction reports with your team or make them public. Allow anyone to start making predictions on your model. Bring dynamic ML predictions into your own app using our low-code API. Predict willingness to pay, score leads and much more in real-time. Obviously AI puts the world’s most cutting-edge algorithms in your hands, without compromising on performance. Forecast revenue, optimize supply chain, personalize marketing. You can now know what happens next. Add a CSV file OR integrate with your favorite data sources in minutes. Pick your prediction column from a dropdown, we'll auto build the AI. Beautifully visualize predicted results, top drivers and simulate "what-if" scenarios.Starting Price: $75 per month -
29
Xero.AI
Xero.AI
Building an AI-powered machine learning engineer that can handle all your data science and ML needs. Xero's artificial analyst is the future of data science and ML. Just ask Xara what you want to do with your data and she will do it for you. Explore your data and create custom visuals using natural language to help you better understand your data and generate insights. Clean and transform your data and extract new features in the most seamless way possible. Create, train, and test unlimited customizable machine learning models by simply asking XARA.Starting Price: $30 per month -
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Daria
XBrain
Daria’s advanced automated features allow users to quickly and easily build predictive models, significantly cutting back on days and weeks of iterative work associated with the traditional machine learning process. Remove financial and technological barriers to build AI systems from scratch for enterprises. Streamline and expedite workflows by lifting weeks of iterative work through automated machine learning for data experts. Get hands-on experience in machine learning with an intuitive GUI for data science beginners. Daria provides various data transformation functions to conveniently construct multiple feature sets. Daria automatically explores through millions of possible combinations of algorithms, modeling techniques and hyperparameters to select the best predictive model. Predictive models built with Daria can be deployed straight to production with a single line of code via Daria’s RESTful API. -
31
FieldDay
FieldDay
Unlock the world of AI and Machine Learning right on your phone with FieldDay. We’ve taken the complexity out of creating machine learning models and turned it into an engaging, hands-on experience that’s as simple as using your camera. FieldDay allows you to create custom AI apps and embed them in your favourite tools, using just your phone. Feed FieldDay examples to learn from, and generate a custom model ready to be embedded in your app/project. A range of projects and apps driven by custom FieldDay machine learning models. Our range of integrations and export options simplifies the process of embedding a machine-learning model into the platform you prefer. With FieldDay, you can collect data directly from your phone’s camera. Our bespoke interface is designed for easy and intuitive annotation during collection, so you can build a custom dataset in no time. FieldDay lets you preview and correct your models in real-time.Starting Price: $19.99 per month -
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Striveworks Chariot
Striveworks
Make AI a trusted part of your business. Build better, deploy faster, and audit easily with the flexibility of a cloud-native platform and the power to deploy anywhere. Easily import models and search cataloged models from across your organization. Save time by annotating data rapidly with model-in-the-loop hinting. Understand the full provenance of your data, models, workflows, and inferences. Deploy models where you need them, including for edge and IoT use cases. Getting valuable insights from your data is not just for data scientists. With Chariot’s low-code interface, meaningful collaboration can take place across teams. Train models rapidly using your organization's production data. Deploy models with one click and monitor models in production at scale. -
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Amazon SageMaker JumpStart
Amazon
Amazon SageMaker JumpStart is a machine learning (ML) hub that can help you accelerate your ML journey. With SageMaker JumpStart, you can access built-in algorithms with pretrained models from model hubs, pretrained foundation models to help you perform tasks such as article summarization and image generation, and prebuilt solutions to solve common use cases. In addition, you can share ML artifacts, including ML models and notebooks, within your organization to accelerate ML model building and deployment. SageMaker JumpStart provides hundreds of built-in algorithms with pretrained models from model hubs, including TensorFlow Hub, PyTorch Hub, HuggingFace, and MxNet GluonCV. You can also access built-in algorithms using the SageMaker Python SDK. Built-in algorithms cover common ML tasks, such as data classifications (image, text, tabular) and sentiment analysis. -
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Nyckel
Nyckel
Nyckel makes it easy to auto-label images and text using AI. We say ‘easy’ because trying to do classification through complex “we-do-it-all” AI/ML tools is hard. Especially if you’re not a machine learning expert. That’s why Nyckel built a platform that makes image and text classification easy for everyone. In just a few minutes, you can train an AI model to identify attributes of any image or text. Whether you’re sorting through images, moderating text, or needing real-time content labeling, Nyckel lets you build a custom classifier in just 5 minutes. And with our Classification API, you can auto-label at scale. Nyckel’s goal is to make AI-powered classification a practical tool for anyone. Learn more at Nyckel.com.Starting Price: Free -
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Tencent Cloud TI Platform
Tencent
Tencent Cloud TI Platform is a one-stop machine learning service platform designed for AI engineers. It empowers AI development throughout the entire process from data preprocessing to model building, model training, model evaluation, and model service. Preconfigured with diverse algorithm components, it supports multiple algorithm frameworks to adapt to different AI use cases. Tencent Cloud TI Platform delivers a one-stop machine learning experience that covers a complete and closed-loop workflow from data preprocessing to model building, model training, and model evaluation. With Tencent Cloud TI Platform, even AI beginners can have their models constructed automatically, making it much easier to complete the entire training process. Tencent Cloud TI Platform's auto-tuning tool can also further enhance the efficiency of parameter tuning. Tencent Cloud TI Platform allows CPU/GPU resources to elastically respond to different computing power needs with flexible billing modes. -
36
Snorkel AI
Snorkel AI
AI today is blocked by lack of labeled data, not models. Unblock AI with the first data-centric AI development platform powered by a programmatic approach. Snorkel AI is leading the shift from model-centric to data-centric AI development with its unique programmatic approach. Save time and costs by replacing manual labeling with rapid, programmatic labeling. Adapt to changing data or business goals by quickly changing code, not manually re-labeling entire datasets. Develop and deploy high-quality AI models via rapid, guided iteration on the part that matters–the training data. Version and audit data like code, leading to more responsive and ethical deployments. Incorporate subject matter experts' knowledge by collaborating around a common interface, the data needed to train models. Reduce risk and meet compliance by labeling programmatically and keeping data in-house, not shipping to external annotators. -
37
Microsoft Foundry
Microsoft
Microsoft Foundry is an end-to-end platform for building, optimizing, and governing AI apps and agents at scale. It gives developers access to more than 11,000 models — from foundational to multimodal — all available through one unified interface. With a simple, interoperable API and SDK, teams can build faster, ship confidently, and reduce integration complexity. Foundry connects seamlessly with your business systems, enabling AI solutions that understand your data and operate securely across your organization. Built-in governance, monitoring, and fleetwide controls ensure responsible AI deployment from day one. Microsoft Foundry helps companies turn AI into real business impact with speed, security, and precision. -
38
Simplismart
Simplismart
Fine-tune and deploy AI models with Simplismart's fastest inference engine. Integrate with AWS/Azure/GCP and many more cloud providers for simple, scalable, cost-effective deployment. Import open source models from popular online repositories or deploy your own custom model. Leverage your own cloud resources or let Simplismart host your model. With Simplismart, you can go far beyond AI model deployment. You can train, deploy, and observe any ML model and realize increased inference speeds at lower costs. Import any dataset and fine-tune open-source or custom models rapidly. Run multiple training experiments in parallel efficiently to speed up your workflow. Deploy any model on our endpoints or your own VPC/premise and see greater performance at lower costs. Streamlined and intuitive deployment is now a reality. Monitor GPU utilization and all your node clusters in one dashboard. Detect any resource constraints and model inefficiencies on the go. -
39
UnionML
Union
Creating ML apps should be simple and frictionless. UnionML is an open-source Python framework built on top of Flyte™, unifying the complex ecosystem of ML tools into a single interface. Combine the tools that you love using a simple, standardized API so you can stop writing so much boilerplate and focus on what matters: the data and the models that learn from them. Fit the rich ecosystem of tools and frameworks into a common protocol for machine learning. Using industry-standard machine learning methods, implement endpoints for fetching data, training models, serving predictions (and much more) to write a complete ML stack in one place. Data science, ML engineering, and MLOps practitioners can all gather around UnionML apps as a way of defining a single source of truth about your ML system’s behavior. -
40
PredictSense
Winjit
PredictSense is an end-to-end Machine Learning platform powered by AutoML to create AI-powered analytical solutions. Fuel the new technological revolution of tomorrow by accelerating machine intelligence. AI is key to unlocking value from enterprise data investments. PredictSense enables businesses to monetize critical data infrastructure and technology investments by creating AI driven advanced analytical solutions rapidly. Empower data science and business teams with advanced capabilities to quickly build and deploy robust technology solutions at scale. Easily integrate AI into the current product ecosystem and fast track GTM for new AI solutions. Incur huge savings in cost, time and effort by building complex ML models in AutoML. PredictSense democratizes AI for every individual in the organization and creates a simple, user-friendly collaboration platform to seamlessly manage critical ML deployments. -
41
Xilinx
Xilinx
The Xilinx’s AI development platform for AI inference on Xilinx hardware platforms consists of optimized IP, tools, libraries, models, and example designs. It is designed with high efficiency and ease-of-use in mind, unleashing the full potential of AI acceleration on Xilinx FPGA and ACAP. Supports mainstream frameworks and the latest models capable of diverse deep learning tasks. Provides a comprehensive set of pre-optimized models that are ready to deploy on Xilinx devices. You can find the closest model and start re-training for your applications! Provides a powerful open source quantizer that supports pruned and unpruned model quantization, calibration, and fine tuning. The AI profiler provides layer by layer analysis to help with bottlenecks. The AI library offers open source high-level C++ and Python APIs for maximum portability from edge to cloud. Efficient and scalable IP cores can be customized to meet your needs of many different applications. -
42
Delineate
Delineate
Delineate offers an easy-to-use platform for generating machine learning-driven predictive models for a range of purposes. Enrich your CRM data with churn predictions, sales forecasts, and even build data products for your customers and team, just to name a few. With Delineate you can access data-driven insights to improve decision-making with ease. The platform caters to founders, revenue teams, product managers, executives, and data enthusiasts. Try Delineate and unleash your data's full potential.Starting Price: $99 per month -
43
LatticeFlow
LatticeFlow
Empower your ML teams to deliver robust and performant AI models by auto-diagnosing and improving your data and models. The only platform that can auto-diagnose data and models, empowering ML teams to deliver robust and performant AI models faster. Covering camera noise, sign stickers, shadows, and others. Confirmed with real-world images on which the model systematically fails. While improving model accuracy by 0.2%. Our mission is to change the way the next generation of AI systems is built. If we are to use AI in our businesses, at doctor’s offices, on our roads, or in our homes, we need to build AI systems that companies and users can trust. We are leading AI professors and researchers from ETH Zurich with broad expertise in formal methods, symbolic reasoning, and machine learning. We started LatticeFlow with the goal of building the world’s first platform that enables companies to deliver robust AI models that work reliably in the wild. -
44
Access, manipulate, analyze and present information in visual formats using a powerful combination of SAS technologies. With SAS Visual Machine Learning, you can broaden your analytics with machine learning and deep learning capabilities that are accessible across your organization for better visualization and reporting. 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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45
vishwa.ai
vishwa.ai
vishwa.ai is an AutoOps platform for AI and ML use cases. It provides expert prompt delivery, fine-tuning, and monitoring of Large Language Models (LLMs). Features: Expert Prompt Delivery: Tailored prompts for various applications. Create no-code LLM Apps: Build LLM workflows in no time with our drag-n-drop UI Advanced Fine-Tuning: Customization of AI models. LLM Monitoring: Comprehensive oversight of model performance. Integration and Security Cloud Integration: Supports Google Cloud, AWS, Azure. Secure LLM Integration: Safe connection with LLM providers. Automated Observability: For efficient LLM management. Managed Self-Hosting: Dedicated hosting solutions. Access Control and Audits: Ensuring secure and compliant operations.Starting Price: $39 per month -
46
Flowise
Flowise AI
Flowise is an open-source platform that enables developers and teams to build AI agents and LLM-powered applications through a visual interface. The platform provides modular building blocks that allow users to create everything from simple chatbot workflows to complex multi-agent systems. With its drag-and-drop design environment, developers can rapidly prototype and deploy AI-powered applications without extensive coding. Flowise supports integrations with more than 100 large language models, embeddings, and vector databases. It also includes features such as human-in-the-loop workflows, observability tools, and execution tracing for monitoring agent behavior. Developers can extend applications through APIs, SDKs, and embedded chat interfaces using TypeScript or Python. By combining visual development tools with scalable infrastructure, Flowise simplifies the process of building and deploying production-ready AI agents.Starting Price: Free -
47
Tune Studio
NimbleBox
Tune Studio is an intuitive and versatile platform designed to streamline the fine-tuning of AI models with minimal effort. It empowers users to customize pre-trained machine learning models to suit their specific needs without requiring extensive technical expertise. With its user-friendly interface, Tune Studio simplifies the process of uploading datasets, configuring parameters, and deploying fine-tuned models efficiently. Whether you're working on NLP, computer vision, or other AI applications, Tune Studio offers robust tools to optimize performance, reduce training time, and accelerate AI development, making it ideal for both beginners and advanced users in the AI space.Starting Price: $10/user/month -
48
Steamship
Steamship
Ship AI faster with managed, cloud-hosted AI packages. Full, built-in support for GPT-4. No API tokens are necessary. Build with our low code framework. Integrations with all major models are built-in. Deploy for an instant API. Scale and share without managing infrastructure. Turn prompts, prompt chains, and basic Python into a managed API. Turn a clever prompt into a published API you can share. Add logic and routing smarts with Python. Steamship connects to your favorite models and services so that you don't have to learn a new API for every provider. Steamship persists in model output in a standardized format. Consolidate training, inference, vector search, and endpoint hosting. Import, transcribe, or generate text. Run all the models you want on it. Query across the results with ShipQL. Packages are full-stack, cloud-hosted AI apps. Each instance you create provides an API and private data workspace. -
49
Amazon SageMaker Canvas
Amazon
Amazon SageMaker Canvas expands access to machine learning (ML) by providing business analysts with a visual interface that allows them to generate accurate ML predictions on their own, without requiring any ML experience or having to write a single line of code. Visual point-and-click interface to connect, prepare, analyze, and explore data for building ML models and generating accurate predictions. Automatically build ML models to run what-if analysis and generate single or bulk predictions with a few clicks. Boost collaboration between business analysts and data scientists by sharing, reviewing, and updating ML models across tools. Import ML models from anywhere and generate predictions directly in Amazon SageMaker Canvas. With Amazon SageMaker Canvas, you can import data from disparate sources, select values you want to predict, automatically prepare and explore data, and quickly and more easily build ML models. You can then analyze models and generate accurate predictions. -
50
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.
