Alternatives to ScoopML
Compare ScoopML alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to ScoopML in 2026. Compare features, ratings, user reviews, pricing, and more from ScoopML 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
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. -
3
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. -
4
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 -
5
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 -
6
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 -
7
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. -
8
Altair Knowledge Studio
Altair
Data scientists and business analysts use Altair to generate actionable insight from their data. Knowledge Studio is a market-leading easy to use machine learning and predictive analytics solution that rapidly visualizes data as it quickly generates explainable results - without requiring a single line of code. A recognized analytics leader, Knowledge Studio brings transparency and automation to machine learning with features such as AutoML and explainable AI without restricting how models are configured and tuned, giving you control over model building. Knowledge Studio is designed to enable collaboration across the business. Data scientists and business analysts can complete complex projects in minutes or hours, not weeks or months. Results are easily understood and explained. The ease of use and automation of steps of the modeling process enable data scientists to efficiently develop more machine learning models faster than coding or using other tools. -
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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. -
10
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. -
11
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. -
12
MyDataModels TADA
MyDataModels
Deploy best-in-class predictive analytics models TADA by MyDataModels helps professionals use their Small Data to enhance their business with a light, easy-to-set-up tool. TADA provides a predictive modeling solution leading to fast and usable results. Shift from days to a few hours into building ad hoc effective models with our 40% reduced time automated data preparation. Get outcomes from your data without programming or machine learning skills. Optimize your time with explainable and understandable models made of easy-to-read formulas. Turn your data into insights in a snap on any platform and create effective automated models. TADA removes the complexity of building predictive models by automating the generative machine learning process – data in, model out. Build and run machine learning models on any devices and platforms through our powerful web-based pre-processing features.Starting Price: $5347.46 per year -
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
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 -
15
Amazon Augmented AI (A2I)
Amazon
Amazon Augmented AI (Amazon A2I) makes it easy to build the workflows required for human review of ML predictions. Amazon A2I brings human review to all developers, removing the undifferentiated heavy lifting associated with building human review systems or managing large numbers of human reviewers. Many machine learning applications require humans to review low confidence predictions to ensure the results are correct. For example, extracting information from scanned mortgage application forms can require human review in some cases due to low-quality scans or poor handwriting. But building human review systems can be time consuming and expensive because it involves implementing complex processes or “workflows”, writing custom software to manage review tasks and results, and in many cases, managing large groups of reviewers. -
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PI.EXCHANGE
PI.EXCHANGE
Easily connect your data to the engine, either through uploading a file or connecting to a database. Then, start analyzing your data through visualizations, or prepare your data for machine learning modeling with the data wrangling actions with repeatable recipes. Get the most out of your data by building machine learning models, using regression, classification or clustering algorithms - all without any code. Uncover insights into your data, using the feature importance, prediction explanation, and what-if tools. Make predictions and integrate them seamlessly into your existing systems through our connectors, ready to go so you can start taking action.Starting Price: $39 per month -
17
Neuton AutoML
Neuton.AI
Neuton, a no-code AutoML solution, makes Machine Learning available to everyone. Explore data insights and make predictions leveraging Automated Artificial Intelligence. • NO coding • NO need for technical skills • NO need for data science knowledge Neuton provides comprehensive Explainability Office©, a unique set of tools that allow users to evaluate model quality at every stage, identify the logic behind the model analysis, understand why certain predictions have been made. • Exploratory Data Analysis • Feature Importance Matrix with class granularity • Model Interpreter • Feature Influence Matrix • Model-to-Data Relevance Indicators historical and for every prediction • Model Quality Index • Confidence Interval • Extensive list of supported metrics with Radar Diagram Neuton enables users to implement ML in days instead of months.Starting Price: $0 -
18
JADBio AutoML
JADBio
JADBio is a state-of-the-art automated Machine Learning Platform without the need for coding. With its breakthrough algorithms it can solve open problems in machine learning. Anybody can use it and perform a sophisticated and correct machine learning analysis even if they do not know any math, statistics, or coding. It is purpose-built for life science data and particularly molecular data. This means that it can deal with the idiosyncrasies of molecular data such as very low sample size and very high number of measured quantities that could reach to millions. Life scientists need it to understand what are the features and biomarkers that are predictive and important, what is their role, and get intuition about the molecular mechanisms involved. Knowledge discovery is often more important than a predictive model. So, JADBio focuses on feature selection and its interpretation.Starting Price: Free -
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
SquareML
SquareML
SquareML is a no-code machine learning platform designed to democratize access to advanced data analytics and predictive modeling, particularly in the healthcare sector. It enables users, regardless of technical expertise, to harness machine learning capabilities without extensive coding knowledge. The platform specializes in data ingestion from multiple sources, including electronic health records, claims databases, medical devices, and health information exchanges. Key features include a no-code data science lifecycle, generative AI models for healthcare, unstructured data conversion, diverse machine learning models for predicting patient outcomes and disease progression, a library of pre-built models and algorithms, and seamless integration with various healthcare data sources. SquareML aims to streamline data processes, enhance diagnostic accuracy, and improve patient care outcomes by providing AI-powered insights. -
22
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. -
23
Cerebrium
Cerebrium
Deploy all major ML frameworks such as Pytorch, Onnx, XGBoost etc with 1 line of code. Don't have your own models? Deploy our prebuilt models that have been optimised to run with sub-second latency. Fine-tune smaller models on particular tasks in order to decrease costs and latency while increasing performance. It takes just a few lines of code and don't worry about infrastructure, we got it. Integrate with top ML observability platforms in order to be alerted about feature or prediction drift, compare model versions and resolve issues quickly. Discover the root causes for prediction and feature drift to resolve degraded model performance. Understand which features are contributing most to the performance of your model.Starting Price: $ 0.00055 per second -
24
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 -
25
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. -
26
C3 AI Suite
C3.ai
Build, deploy, and operate Enterprise AI applications. The C3 AI® Suite uses a unique model-driven architecture to accelerate delivery and reduce the complexities of developing enterprise AI applications. The C3 AI model-driven architecture provides an “abstraction layer,” that allows developers to build enterprise AI applications by using conceptual models of all the elements an application requires, instead of writing lengthy code. This provides significant benefits: Use AI applications and models that optimize processes for every product, asset, customer, or transaction across all regions and businesses. Deploy AI applications and see results in 1-2 quarters – rapidly roll out additional applications and new capabilities. Unlock sustained value – hundreds of millions to billions of dollars per year – from reduced costs, increased revenue, and higher margins. Ensure systematic, enterprise-wide governance of AI with C3.ai’s unified platform that offers data lineage and governance. -
27
CognitiveScale Cortex AI
CognitiveScale
Developing AI solutions requires an engineering approach that is resilient, open and repeatable to ensure necessary quality and agility is achieved. Until today these efforts are missing the foundation to address these challenges amid a sea of point tools and fast changing models and data. Collaborative developer platform for automating development and control of AI applications across multiple personas. Derive hyper-detailed customer profiles from enterprise data to predict behaviors in real-time and at scale. Generate AI-powered models designed to continuously learn and achieve clearly defined business outcomes. Enables organizations to explain and prove compliance with applicable rules and regulations. CognitiveScale's Cortex AI Platform addresses enterprise AI use cases through modular platform offerings. Our customers consume and leverage its capabilities as microservices within their enterprise AI initiatives. -
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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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Core ML
Apple
Core ML applies a machine learning algorithm to a set of training data to create a model. You use a model to make predictions based on new input data. Models can accomplish a wide variety of tasks that would be difficult or impractical to write in code. For example, you can train a model to categorize photos or detect specific objects within a photo directly from its pixels. After you create the model, integrate it in your app and deploy it on the user’s device. Your app uses Core ML APIs and user data to make predictions and to train or fine-tune the model. You can build and train a model with the Create ML app bundled with Xcode. Models trained using Create ML are in the Core ML model format and are ready to use in your app. Alternatively, you can use a wide variety of other machine learning libraries and then use Core ML Tools to convert the model into the Core ML format. Once a model is on a user’s device, you can use Core ML to retrain or fine-tune it on-device. -
30
Gradio
Gradio
Build & Share Delightful Machine Learning Apps. Gradio is the fastest way to demo your machine learning model with a friendly web interface so that anyone can use it, anywhere! Gradio can be installed with pip. Creating a Gradio interface only requires adding a couple lines of code to your project. You can choose from a variety of interface types to interface your function. Gradio can be embedded in Python notebooks or presented as a webpage. A Gradio interface can automatically generate a public link you can share with colleagues that lets them interact with the model on your computer remotely from their own devices. Once you've created an interface, you can permanently host it on Hugging Face. Hugging Face Spaces will host the interface on its servers and provide you with a link you can share. -
31
Codenull.ai
Codenull.ai
Build Any AI model without writing a single line of code. Use these models for Portfolio optimization, Robo-advisors, Recommendation Engines, Fraud detection and much more. Asset management can be overwhelming. Don't worry, Codenull is ready to help! with asset value history it can optimize your portfolio for the best returns. Train an AI model on past data of logistic costs and get accurate predictions on the same for future. We solve ANY possible AI use case. Get in touch, let's make AI models customized for your business. -
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Key Ward
Key Ward
Extract, transform, manage, & process CAD, FE, CFD, and test data effortlessly. Create automatic data pipelines for machine learning, ROM, & 3D deep learning. Removing data science barriers without coding. Key Ward's platform is the first end-to-end engineering no-code solution that redefines how engineers interact with their data, experimental & CAx. Through leveraging engineering data intelligence, our software enables engineers to easily handle their multi-source data, extract direct value with our built-in advanced analytics tools, and custom-build their machine and deep learning models, all under one platform, all with a few clicks. Automatically centralize, update, extract, sort, clean, and prepare your multi-source data for analysis, machine learning, and/or deep learning. Use our advanced analytics tools on your experimental & simulation data to correlate, find dependencies, and identify patterns.Starting Price: €9,000 per year -
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Graviti
Graviti
Unstructured data is the future of AI. Unlock this future now and build an ML/AI pipeline that scales all of your unstructured data in one place. Use better data to deliver better models, only with Graviti. Get to know the data platform that enables AI developers with management, query, and version control features that are designed for unstructured data. Quality data is no longer a pricey dream. Manage your metadata, annotation, and predictions in one place. Customize filters and visualize filtering results to get you straight to the data that best match your needs. Utilize a Git-like structure to manage data versions and collaborate with your teammates. Role-based access control and visualization of version differences allows your team to work together safely and flexibly. Automate your data pipeline with Graviti’s built-in marketplace and workflow builder. Level-up to fast model iterations with no more grinding. -
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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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MosaicML
MosaicML
Train and serve large AI models at scale with a single command. Point to your S3 bucket and go. We handle the rest, orchestration, efficiency, node failures, and infrastructure. Simple and scalable. MosaicML enables you to easily train and deploy large AI models on your data, in your secure environment. Stay on the cutting edge with our latest recipes, techniques, and foundation models. Developed and rigorously tested by our research team. With a few simple steps, deploy inside your private cloud. Your data and models never leave your firewalls. Start in one cloud, and continue on another, without skipping a beat. Own the model that's trained on your own data. Introspect and better explain the model decisions. Filter the content and data based on your business needs. Seamlessly integrate with your existing data pipelines, experiment trackers, and other tools. We are fully interoperable, cloud-agnostic, and enterprise proved. -
36
Metacoder
Wazoo Mobile Technologies LLC
Metacoder makes processing data faster and easier. Metacoder gives analysts needed flexibility and tools to facilitate data analysis. Data preparation steps such as cleaning are managed reducing the manual inspection time required before you are up and running. Compared to alternatives, is in good company. Metacoder beats similar companies on price and our management is proactively developing based on our customers' valuable feedback. Metacoder is used primarily to assist predictive analytics professionals in their job. We offer interfaces for database integrations, data cleaning, preprocessing, modeling, and display/interpretation of results. We help organizations distribute their work transparently by enabling model sharing, and we make management of the machine learning pipeline easy to make tweaks. Soon we will be including code free solutions for image, audio, video, and biomedical data.Starting Price: $89 per user/month -
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Apache PredictionIO
Apache
Apache PredictionIO® is an open-source machine learning server built on top of a state-of-the-art open-source stack for developers and data scientists to create predictive engines for any machine learning task. It lets you quickly build and deploy an engine as a web service on production with customizable templates. Respond to dynamic queries in real-time once deployed as a web service, evaluate and tune multiple engine variants systematically, and unify data from multiple platforms in batch or in real-time for comprehensive predictive analytics. Speed up machine learning modeling with systematic processes and pre-built evaluation measures, support machine learning and data processing libraries such as Spark MLLib and OpenNLP. Implement your own machine learning models and seamlessly incorporate them into your engine. Simplify data infrastructure management. Apache PredictionIO® can be installed as a full machine learning stack, bundled with Apache Spark, MLlib, HBase, Akka HTTP, etc.Starting Price: Free -
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SANCARE
SANCARE
SANCARE is a start-up specializing in Machine Learning applied to hospital data. We collaborate with some of the best scientists in the field. SANCARE provides Medical Information Departments with an ergonomic and intuitive interface, promoting rapid adoption. The user has access to all the documents that constitute the computerized patient record. A true production tool, each step of the coding process is traced for external checks. Machine learning makes it possible to develop powerful predictive models from large volumes of data, and to take into account the notion of context, which is not possible for rule engines or semantic analysis engines. It is therefore possible to automate complex decision-making processes or to detect weak signals ignored by humans. The SANCARE software machine learning engine is based on a probabilistic approach. It learns over a large amount of examples to predict the right codes, without any indication. -
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Strong Analytics
Strong Analytics
Our platforms provide a trusted foundation upon which to design, build, and deploy custom machine learning and artificial intelligence solutions. Build next-best-action applications that learn, adapt, and optimize using reinforcement-learning based algorithms. Custom, continuously-improving deep learning vision models to solve your unique challenges. Predict the future using state-of-the-art forecasts. Enable smarter decisions throughout your organization with cloud based tools to monitor and analyze. The process of taking a modern machine learning application from research and ad-hoc code to a robust, scalable platform remains a key challenge for experienced data science and engineering teams. Strong ML simplifies this process with a complete suite of tools to manage, deploy, and monitor your machine learning applications. -
40
Intelligent Artifacts
Intelligent Artifacts
A new category of AI. Most current AI solutions are engineered through a statistical and purely mathematical lens. We took a different approach. With discoveries in information theory, the team at Intelligent Artifacts has built a new category of AI: a true AGI that eliminates current machine intelligence shortcomings. Our framework keeps the data and application layers separate from the intelligence layer allowing it to learn in real-time, and enabling it to explain predictions down to root cause. A true AGI demands a truly integrated platform. With Intelligent Artifacts, you'll model information, not data — predictions and decisions are real-time and transparent, and can be deployed across various domains without the need to rewrite code. And by combining specialized AI consultants with our dynamic platform, you'll get a customized solution that rapidly offers deep insights and greater outcomes from your data. -
41
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. -
42
Oracle Data Science
Oracle
A data science platform that improves productivity with unparalleled abilities. Build and evaluate higher-quality machine learning (ML) models. Increase business flexibility by putting enterprise-trusted data to work quickly and support data-driven business objectives with easier deployment of ML models. Using cloud-based platforms to discover new business insights. Building a machine learning model is an iterative process. In this ebook, we break down the process and describe how machine learning models are built. Explore notebooks and build or test machine learning algorithms. Try AutoML and see data science results. Build high-quality models faster and easier. Automated machine learning capabilities rapidly examine the data and recommend the optimal data features and best algorithms. Additionally, automated machine learning tunes the model and explains the model’s results. -
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
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 -
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Baidu AI Cloud Machine Learning (BML), an end-to-end machine learning platform designed for enterprises and AI developers, can accomplish one-stop data pre-processing, model training, and evaluation, and service deployments, among others. The Baidu AI Cloud AI development platform BML is an end-to-end AI development and deployment platform. Based on the BML, users can accomplish the one-stop data pre-processing, model training and evaluation, service deployment, and other works. The platform provides a high-performance cluster training environment, massive algorithm frameworks and model cases, as well as easy-to-operate prediction service tools. Thus, it allows users to focus on the model and algorithm and obtain excellent model and prediction results. The fully hosted interactive programming environment realizes the data processing and code debugging. The CPU instance supports users to install a third-party software library and customize the environment, ensuring flexibility.
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Emly Labs
Emly Labs
Emly Labs is an AI framework designed to make AI accessible for users at all technical levels through a user-friendly platform. It offers AI project management with tools for guided workflows and automation for faster execution. The platform encourages team collaboration and innovation, provides no-code data preparation, and integrates external data for robust AI models. Emly AutoML automates data processing and model evaluation, reducing human input. It prioritizes transparency, with explainable AI features and robust auditing for compliance. Security measures include data isolation, role-based access, and secure integrations. Additionally, Emly's cost-effective infrastructure allows on-demand resource provisioning and policy management, enhancing experimentation and innovation while reducing costs and risks.Starting Price: $99/month -
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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. -
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With Amazon SageMaker Model Monitor, you can select the data you would like to monitor and analyze without the need to write any code. SageMaker Model Monitor lets you select data from a menu of options such as prediction output, and captures metadata such as timestamp, model name, and endpoint so you can analyze model predictions based on the metadata. You can specify the sampling rate of data capture as a percentage of overall traffic in the case of high volume real-time predictions, and the data is stored in your own Amazon S3 bucket. You can also encrypt this data, configure fine-grained security, define data retention policies, and implement access control mechanisms for secure access. Amazon SageMaker Model Monitor offers built-in analysis in the form of statistical rules, to detect drifts in data and model quality. You can also write custom rules and specify thresholds for each rule.
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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. -
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ioModel
Twin Tech Labs
ioModel is designed to provide existing analytics teams access to powerful machine learning models without having to write code, significantly reducing development and maintenance costs. Furthermore, analysts can then validate and understand the efficacy of models developed on the platform using well understood and proven statistical validation techniques. The ioModel Research Platform will do for machine learning what the spreadsheet did for general computing. The ioModel Research Platform is developed entirely using open source technology and is itself available (without support or warranty) under the GPL License on GitHub. We invite our community to collaborate with us on the roadmap, development, and governance of the Platform. We’re committed to working openly and transparently to drive forward analytics, modeling, and innovation..
