Best Machine Learning Software - Page 12
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Compare the Top Machine Learning Software as of August 2025 - Page 12
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Amazon SageMaker makes it easy to deploy ML models to make predictions (also known as inference) at the best price-performance for any use case. It provides a broad selection of ML infrastructure and model deployment options to help meet all your ML inference needs. It is a fully managed service and integrates with MLOps tools, so you can scale your model deployment, reduce inference costs, manage models more effectively in production, and reduce operational burden. From low latency (a few milliseconds) and high throughput (hundreds of thousands of requests per second) to long-running inference for use cases such as natural language processing and computer vision, you can use Amazon SageMaker for all your inference needs.
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Outerbounds
Outerbounds
Design and develop data-intensive projects with human-friendly, open-source Metaflow. Run, scale, and deploy them reliably on the fully managed Outerbounds platform. One platform for all your ML and data science projects. Access data securely from your existing data warehouses. Compute with a cluster optimized for scale and cost. 24/7 managed orchestration for production workflows. Use results to power any application. Give your data scientists superpowers, approved by your engineers. Outerbounds Platform allows data scientists to develop rapidly, experiment at scale, and deploy to production confidently. All within the outer bounds of policies and processes defined by your engineers, running on your cloud account, fully managed by us. Security is in our DNA, not at the perimeter. The platform adapts to your policies and compliance requirements through multiple layers of security. Centralized auth, a strict permission boundary, and granular task execution roles. -
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Robust Intelligence
Robust Intelligence
The Robust Intelligence Platform integrates seamlessly into your ML lifecycle to eliminate model failures. The platform detects your model’s vulnerabilities, prevents aberrant data from entering your AI system, and detects statistical data issues like drift. At the core of our test-based approach is a single test. Each test measures your model’s robustness to a specific type of production model failure. Stress Testing runs hundreds of these tests to measure model production readiness. The results of these tests are used to auto-configure a custom AI Firewall that protects the model against the specific forms of failure to which a given model is susceptible. Finally, Continuous Testing runs these tests during production, providing automated root cause analysis informed by the underlying cause of any single test failure. Using all three elements of the Robust Intelligence platform together helps ensure ML Integrity. -
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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 -
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datuum.ai
Datuum
AI-powered data integration tool that helps streamline the process of customer data onboarding. It allows for easy and fast automated data integration from various sources without coding, reducing preparation time to just a few minutes. With Datuum, organizations can efficiently extract, ingest, transform, migrate, and establish a single source of truth for their data, while integrating it into their existing data storage. Datuum is a no-code product and can reduce up to 80% of the time spent on data-related tasks, freeing up time for organizations to focus on generating insights and improving the customer experience. With over 40 years of experience in data management and operations, we at Datuum have incorporated our expertise into the core of our product, addressing the key challenges faced by data engineers and managers and ensuring that the platform is user-friendly, even for non-technical specialists. -
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Layerup
Layerup
Extract and Transform any data from any data source with Natural Language connect to your data source - everything ranging from your DB to your CRM to your billing solution. Improve Productivity by 5-10x Forget about wasting time on clunky BI tools. Use Natural Language to query any complex data in seconds. Transition from DIY tools to non-DIY AI-powered tools. Generate complex dashboards and reports in a few lines. No more SQL or complex formulas - let Layerup AI do the heavy lifting for you. Layerup not only gives you instant answer to questions that would require 5-40 hours/month on SQL queries, but it will act as your personal data analyst 24/7 while providing you complex dashboards/charts that you can embed anywhere. -
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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. -
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Palantir AIP
Palantir
Deploy LLMs and other AI — commercial, homegrown or open-source — on your private network, based on an AI-optimized data foundation. AI Core is a real-time, full-fidelity representation of your business that includes all actions, decisions, and processes. Utilize the Action Graph, atop the AI Core, to set specific scopes of activity for LLMs and other models – including hand-off procedures for auditable calculations and human-in-the-loop operations. Monitor and control LLM activity and reach in real-time to help users promote compliance with legal, data sensitivity, and regulatory audit requirements. -
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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. -
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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. -
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IBM watsonx
IBM
IBM watsonx is a powerful suite of AI products designed to accelerate the adoption of generative AI across business workflows. With tools like watsonx.ai for AI application development, watsonx.data for data management, and watsonx.governance for regulatory compliance, businesses can create, manage, and deploy AI solutions seamlessly. The platform provides an integrated developer studio to foster collaboration and optimize the entire AI lifecycle. IBM watsonx also offers tools for automating processes, boosting productivity with AI assistants and agents, and supporting responsible AI through governance and risk management. Trusted by industries worldwide, IBM watsonx enables businesses to unlock the full potential of AI to drive innovation and enhance decision-making. -
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Openlayer
Openlayer
Onboard your data and models to Openlayer and collaborate with the whole team to align expectations surrounding quality and performance. Breeze through the whys behind failed goals to solve them efficiently. The information to diagnose the root cause of issues is at your fingertips. Generate more data that looks like the subpopulation and retrain the model. Test new commits against your goals to ensure systematic progress without regressions. Compare versions side-by-side to make informed decisions and ship with confidence. Save engineering time by rapidly figuring out exactly what’s driving model performance. Find the most direct paths to improving your model. Know the exact data needed to boost model performance and focus on cultivating high-quality and representative datasets. -
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Bifrost
Bifrost AI
Quickly and easily generate diverse and realistic synthetic data and high-fidelity 3D worlds to enhance model performance. Bifrost's platform is the fastest way to generate the high-quality synthetic images that you need to improve ML performance and overcome real-world data limitations. Prototype and test up to 30x faster by circumventing costly and time-consuming real-world data collection and annotation. Generate data to account for rare scenarios underrepresented in real data, resulting in more balanced datasets. Manual annotation and labeling is an error-prone, resource-intensive process. Easily and quickly generate data that is pre-labeled and pixel-perfect. Real-world data can inherit the biases of conditions under which the data was collected, and generate data to solve for these instances. -
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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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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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Modelbit
Modelbit
Don't change your day-to-day, works with Jupyter Notebooks and any other Python environment. Simply call modelbi.deploy to deploy your model, and let Modelbit carry it — and all its dependencies — to production. ML models deployed with Modelbit can be called directly from your warehouse as easily as calling a SQL function. They can also be called as a REST endpoint directly from your product. Modelbit is backed by your git repo. GitHub, GitLab, or home grown. Code review. CI/CD pipelines. PRs and merge requests. Bring your whole git workflow to your Python ML models. Modelbit integrates seamlessly with Hex, DeepNote, Noteable and more. Take your model straight from your favorite cloud notebook into production. Sick of VPC configurations and IAM roles? Seamlessly redeploy your SageMaker models to Modelbit. Immediately reap the benefits of Modelbit's platform with the models you've already built. -
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Picterra
Picterra
Picterra is the leading geospatial AI enterprise software. Detect objects, patterns, and change in satellite and drone imagery faster than ever before by managing the entire geospatial ML pipeline with our cloud-native platform. By combining a no-code approach, a user-friendly interface, seamless scalability, and cutting-edge machine learning technology, Picterra accelerates the development of full-scale ML projects. -
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Vaex
Vaex
At Vaex.io we aim to democratize big data and make it available to anyone, on any machine, at any scale. Cut development time by 80%, your prototype is your solution. Create automatic pipelines for any model. Empower your data scientists. Turn any laptop into a big data powerhouse, no clusters, no engineers. We provide reliable and fast data driven solutions. With our state-of-the-art technology we build and deploy machine learning models faster than anyone on the market. Turn your data scientist into big data engineers. We provide comprehensive training of your employees, enabling you to take full advantage of our technology. Combines memory mapping, a sophisticated expression system, and fast out-of-core algorithms. Efficiently visualize and explore big datasets, and build machine learning models on a single machine. -
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ONNX
ONNX
ONNX defines a common set of operators - the building blocks of machine learning and deep learning models - and a common file format to enable AI developers to use models with a variety of frameworks, tools, runtimes, and compilers. Develop in your preferred framework without worrying about downstream inferencing implications. ONNX enables you to use your preferred framework with your chosen inference engine. ONNX makes it easier to access hardware optimizations. Use ONNX-compatible runtimes and libraries designed to maximize performance across hardware. Our active community thrives under our open governance structure, which provides transparency and inclusion. We encourage you to engage and contribute. -
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Apache Mahout
Apache Software Foundation
Apache Mahout is a powerful, scalable, and versatile machine learning library designed for distributed data processing. It offers a comprehensive set of algorithms for various tasks, including classification, clustering, recommendation, and pattern mining. Built on top of the Apache Hadoop ecosystem, Mahout leverages MapReduce and Spark to enable data processing on large-scale datasets. Apache Mahout(TM) is a distributed linear algebra framework and mathematically expressive Scala DSL designed to let mathematicians, statisticians, and data scientists quickly implement their own algorithms. Apache Spark is the recommended out-of-the-box distributed back-end or can be extended to other distributed backends. Matrix computations are a fundamental part of many scientific and engineering applications, including machine learning, computer vision, and data analysis. Apache Mahout is designed to handle large-scale data processing by leveraging the power of Hadoop and Spark. -
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AWS Neuron
Amazon Web Services
It supports high-performance training on AWS Trainium-based Amazon Elastic Compute Cloud (Amazon EC2) Trn1 instances. For model deployment, it supports high-performance and low-latency inference on AWS Inferentia-based Amazon EC2 Inf1 instances and AWS Inferentia2-based Amazon EC2 Inf2 instances. With Neuron, you can use popular frameworks, such as TensorFlow and PyTorch, and optimally train and deploy machine learning (ML) models on Amazon EC2 Trn1, Inf1, and Inf2 instances with minimal code changes and without tie-in to vendor-specific solutions. AWS Neuron SDK, which supports Inferentia and Trainium accelerators, is natively integrated with PyTorch and TensorFlow. This integration ensures that you can continue using your existing workflows in these popular frameworks and get started with only a few lines of code changes. For distributed model training, the Neuron SDK supports libraries, such as Megatron-LM and PyTorch Fully Sharded Data Parallel (FSDP). -
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AWS Trainium
Amazon Web Services
AWS Trainium is the second-generation Machine Learning (ML) accelerator that AWS purpose built for deep learning training of 100B+ parameter models. Each Amazon Elastic Compute Cloud (EC2) Trn1 instance deploys up to 16 AWS Trainium accelerators to deliver a high-performance, low-cost solution for deep learning (DL) training in the cloud. Although the use of deep learning is accelerating, many development teams are limited by fixed budgets, which puts a cap on the scope and frequency of training needed to improve their models and applications. Trainium-based EC2 Trn1 instances solve this challenge by delivering faster time to train while offering up to 50% cost-to-train savings over comparable Amazon EC2 instances. -
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AtomBeam
AtomBeam
There’s no hardware to buy, no changes that need to be made to your network, and only a simple installation of a small library of software. By 2025, 75% of all enterprise-generated data, or 90 zettabytes, will be from IoT. To give a sense of scale, all of the storage capacity of every data center in the world today adds up to less than two zettabytes. Moreover, 98% of IoT data is unsecured, but all of it should be secured. Battery life for sensors is a major concern, with little relief on the horizon. Wireless data transmission range is a problem for many IoT users. We think that AtomBeam will impact IoT in the same way the electric light changed everyday living. Many key impediments to IoT adoption can be overcome with the simple addition of our compaction software. With our software alone, you can improve security, extend battery life, and increase transmission range. AtomBeam offers the opportunity for significant discounts on connectivity and cloud storage costs. -
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Kolena
Kolena
We’ve included some common examples, but the list is far from exhaustive. Our solution engineering team will work with you to customize Kolena for your workflows and your business metrics. Aggregate metrics don't tell the full story — unexpected model behavior in production is the norm. Current testing processes are manual, error-prone, and unrepeatable. Models are evaluated on arbitrary statistical metrics that align imperfectly with product objectives. Tracking model improvement over time as the data evolves is difficult and techniques sufficient in a research environment don't meet the demands of production. -
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UpTrain
UpTrain
Get scores for factual accuracy, context retrieval quality, guideline adherence, tonality, and many more. You can’t improve what you can’t measure. UpTrain continuously monitors your application's performance on multiple evaluation criterions and alerts you in case of any regressions with automatic root cause analysis. UpTrain enables fast and robust experimentation across multiple prompts, model providers, and custom configurations, by calculating quantitative scores for direct comparison and optimal prompt selection. Hallucinations have plagued LLMs since their inception. By quantifying degree of hallucination and quality of retrieved context, UpTrain helps to detect responses with low factual accuracy and prevent them before serving to the end-users. -
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WhyLabs
WhyLabs
Enable observability to detect data and ML issues faster, deliver continuous improvements, and avoid costly incidents. Start with reliable data. Continuously monitor any data-in-motion for data quality issues. Pinpoint data and model drift. Identify training-serving skew and proactively retrain. Detect model accuracy degradation by continuously monitoring key performance metrics. Identify risky behavior in generative AI applications and prevent data leakage. Protect your generative AI applications are safe from malicious actions. Improve AI applications through user feedback, monitoring, and cross-team collaboration. Integrate in minutes with purpose-built agents that analyze raw data without moving or duplicating it, ensuring privacy and security. Onboard the WhyLabs SaaS Platform for any use cases using the proprietary privacy-preserving integration. Security approved for healthcare and banks. -
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Shaip
Shaip
Shaip offers end-to-end generative AI services, specializing in high-quality data collection and annotation across multiple data types including text, audio, images, and video. The platform sources and curates diverse datasets from over 60 countries, supporting AI and machine learning projects globally. Shaip provides precise data labeling services with domain experts ensuring accuracy in tasks like image segmentation and object detection. It also focuses on healthcare data, delivering vast repositories of physician audio, electronic health records, and medical images for AI training. With multilingual audio datasets covering 60+ languages and dialects, Shaip enhances conversational AI development. The company ensures data privacy through de-identification services, protecting sensitive information while maintaining data utility. -
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Barbara
Barbara
Barbara is the Edge AI Platform for organizations looking to overcome the challenges of deploying AI, in mission-critical environments. With Barbara companies can deploy, train and maintain their models across thousands of devices in an easy fashion, with the autonomy, privacy and real- time that the cloud can´t match. Barbara technology stack is composed by: .- Industrial Connectors for legacy or next-generation equipment. .- Edge Orchestrator to deploy and control container-based and native edge apps across thousands of distributed locations .- MLOps to optimize, deploy, and monitor your trained model in minutes. .- Marketplace of certified Edge Apps, ready to be deployed. .- Remote Device Management for provisioning, configuration, and updates. More --> www. barbara.tech -
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Qualdo
Qualdo
We are a leader in Data Quality & ML Model for enterprises adopting a multi-cloud, ML and modern data management ecosystem. Algorithms to track Data Anomalies in Azure, GCP & AWS databases. Measure and monitor data issues from all your cloud database management tools and data silos, using a single, centralized tool. Quality is in the eye of the beholder. Data issues have different implications depending on where you sit in the enterprise. Qualdo is a pioneer in organizing all data quality management issues through the lens of multiple enterprise stakeholders, presenting a unified view in a consumable format. Deploy powerful auto-resolution algorithms to track and isolate critical data issues. Take advantage of robust reports and alerts to manage your enterprise regulatory compliance. -
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Zama
Zama
Improve patient care while maintaining privacy by allowing secure, confidential data sharing between healthcare providers. Facilitate secure financial data analysis for risk management and fraud detection, keeping client information encrypted and safe. Create targeted advertising and campaign insights in a post-cookie era, ensuring user privacy through encrypted data analysis. Enable data collaboration between different agencies, while keeping it confidential from each other, enhancing efficiency and data security, without revealing secrets. Give the ability to create user authentication applications without having to reveal their identities. Enable governments to create digitized versions of their services without having to trust cloud providers.