Best Machine Learning Software for Startups - Page 10
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Compare the Top Machine Learning Software for Startups as of October 2025 - Page 10
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Tenstorrent DevCloud
Tenstorrent
We developed Tenstorrent DevCloud to give people the opportunity to try their models on our servers without purchasing our hardware. We are building Tenstorrent AI in the cloud so programmers can try our AI solutions. The first log-in is free, after that, you get connected with our team who can help better assess your needs. Tenstorrent is a team of competent and motivated people that came together to build the best computing platform for AI and software 2.0. Tenstorrent is a next-generation computing company with the mission of addressing the rapidly growing computing demands for software 2.0. Headquartered in Toronto, Canada, Tenstorrent brings together experts in the field of computer architecture, basic design, advanced systems, and neural network compilers. ur processors are optimized for neural network inference and training. They can also execute other types of parallel computation. Tenstorrent processors comprise a grid of cores known as Tensix cores. -
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Zinia
Zinia
The Zinia artificial intelligence platform connects the dots between the key business decision maker and AI. You can now build your trusted AI models without depending on technical teams and ensure alignment of AI with business objectives. Ground-breaking technology simplified to help you build AI backwards from business. Improves revenue by 15-20% and increases efficiency by cutting AI implementation time from months to days. Zinia optimises business outcomes with human-centered AI. Most AI development in organisations is misaligned with business KPIs. Zinia is built with the vision to address this key problem by democratising AI for you. Zinia brings business fit cutting-edge ML and AI Technology into your hands. Built by a team with more than 50 years of experience in AI, Zinia is your trusted platform that simplifies ground-breaking technology and gives you the fastest path from data to business decisions. -
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Vector
Bain & Company
Automation, machine learning, data mining and design thinking. These are no longer things that companies do, they are how companies do what they do. Vector is a digital delivery platform that propels innovation and accelerates digital transformation by ensuring that the right digital capabilities are at the heart of everything you do. Now you don’t have to focus on "going digital," you are digital. The era of the standalone digital project is over. Today, digital powers virtually every move a company makes. Analytics informs every high-stakes decision. And emerging technologies confer a huge advantage to the companies quick enough to spot them first. Vector brings all this together, infusing every project we work on with an integrated set of digital capabilities tailored to your strategy. Bain has experts in data science, smart automation, prototyping, digital marketing, enterprise technology, and related disciplines, enabling us to take a digital-first approach to every engagement. -
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Synthesis AI
Synthesis AI
A synthetic data platform for ML engineers to enable the development of more capable AI models. Simple APIs provide on-demand generation of perfectly-labeled, diverse, and photoreal images. Highly-scalable cloud-based generation platform delivers millions of perfectly labeled images. On-demand data enables new data-centric approaches to develop more performant models. An expanded set of pixel-perfect labels including segmentation maps, dense 2D/3D landmarks, depth maps, surface normals, and much more. Rapidly design, test, and refine your products before building hardware. Prototype different imaging modalities, camera placements, and lens types to optimize your system. Reduce bias in your models associated with misbalanced data sets while preserving privacy. Ensure equal representation across identities, facial attributes, pose, camera, lighting, and much more. We have worked with world-class customers across many use cases. -
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Sama
Sama
We offer the highest quality SLA (>95%), even on the most complex workflows. Our team assists with anything from implementing a robust quality rubric to raising edge cases. As an ethical AI company, we have provided economic opportunities for over 52,000 people from underserved and marginalized communities. ML Assisted annotation created up to 3-4x efficiency improvement for a single class annotation. We quickly adapt to ramp-ups, focus shifts, and edge cases. ISO certified delivery centers, biometric authentication, and user authentication with 2FA ensure a secure work environment. Seamlessly re-prioritize tasks, provide quality feedback, and monitor models in production. We support data of all types. Get more with less. We combine machine learning and humans in the loop to filter data and select images relevant to your use case. Receive sample results based on your initial guidelines. We work with you to identify edge cases and recommend annotation best practices. -
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Elementary
Elementary
Elementary’s easy-to-use software, deep learning AI, and camera systems are built to capture visual data, deliver fast and reliable real-time judgments, and provide lasting value to your business. Elementary’s easy-to-use software, deep learning AI, and camera systems are built to capture visual data, deliver fast and reliable real-time judgments, and provide lasting value to your business. PLC, machine, and automation integrations. Run multiple inspections simultaneously. High-speed inspection from AI on the edge. Better utilize your factory floor and see an increase of 50% in warehouse associate productivity. Stay on top of your product line like never before. See 90% more detections in manufacturing operations. Save time and money with our plug-and-play system. It only takes 20 minutes for remote deployment. Today’s work environment demands remote accessibility in order to keep pace with rapidly changing conditions. Leveraging secure cloud technology is key to staying informed. -
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Galileo
Galileo
Models can be opaque in understanding what data they didn’t perform well on and why. Galileo provides a host of tools for ML teams to inspect and find ML data errors 10x faster. Galileo sifts through your unlabeled data to automatically identify error patterns and data gaps in your model. We get it - ML experimentation is messy. It needs a lot of data and model changes across many runs. Track and compare your runs in one place and quickly share reports with your team. Galileo has been built to integrate with your ML ecosystem. Send a fixed dataset to your data store to retrain, send mislabeled data to your labelers, share a collaborative report, and a lot more! Galileo is purpose-built for ML teams to build better quality models, faster. -
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Devron
Devron
Run machine learning on distributed data for faster insights and better outcomes without the cost, concentration risk, long lead times, and privacy concerns of centralizing data. The efficacy of machine learning algorithms is frequently limited by the accessibility of diverse, quality data sources. By unlocking access to more data and providing transparency of dataset model impacts, you get more effective insight. Obtaining approvals, centralizing data, and building out infrastructure takes time. By using data where it resides while federating and parallelizing the training process, you get trained models and valuable insights faster. Because Devron offers access to data in situ and removes the need for masking and anonymizing, you won’t need to move data—greatly reducing the overhead of the extraction, transformation, and loading process. -
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navio
craftworks GmbH
Seamless machine learning model management, deployment, and monitoring for supercharging MLOps for any organization on the best AI platform. Use navio to perform various machine learning operations across an organization's entire artificial intelligence landscape. Take your experiments out of the lab and into production, and integrate machine learning into your workflow for a real, measurable business impact. navio provides various Machine Learning operations (MLOps) to support you during the model development process all the way to running your model in production. Automatically create REST endpoints and keep track of the machines or clients that are interacting with your model. Focus on exploration and training your models to obtain the best possible result and stop wasting time and resources on setting up infrastructure and other peripheral features. Let navio handle all aspects of the product ionization process to go live quickly with your machine learning models. -
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Fiddler AI
Fiddler AI
Fiddler is a pioneer in Model Performance Management for responsible AI. The Fiddler platform’s unified environment provides a common language, centralized controls, and actionable insights to operationalize ML/AI with trust. Model monitoring, explainable AI, analytics, and fairness capabilities address the unique challenges of building in-house stable and secure MLOps systems at scale. Unlike observability solutions, Fiddler integrates deep XAI and analytics to help you grow into advanced capabilities over time and build a framework for responsible AI practices. Fortune 500 organizations use Fiddler across training and production models to accelerate AI time-to-value and scale, build trusted AI solutions, and increase revenue. -
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AI Squared
AI Squared
Empower data scientists and application developers to collaborate on ML projects. Build, load, optimize and test models and integrations before publishing to end-users for integration into live applications. Reduce data science workload and improve decision-making by storing and sharing ML models across the organization. Publish updates to automatically push changes to models in production. Drive efficiency by instantly providing ML-powered insights within any web-based business application. Our self-service, drag-and-drop browser extension enables analysts and business users to integrate models into any web-based application with zero code. -
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BlueML
Explorance
Get an in-depth analysis of your open text comments in seconds with Blue Machine Learning (BlueML) solutions. Now you can see what matters most to your students and employees and instantly get more actionable insights to streamline your decisions. Most comment analysis tools use a generic one-size-fits-all approach usually based on customer experience machine learning models. However, when you look at the employee or student journey, they’re made up of specific components around experience and learning. With BlueML, you can leverage three specialized models that will accurately consume and analyze comments from each area along the student and employee journeys, giving you context-specific categorization. Get an accurate view of the overall sentiments in employee and student comments (very negative, negative, neutral, positive, very positive, ambiguous). Gain insights about what emotions employees and students have expressed in their comments. -
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Feast
Tecton
Make your offline data available for real-time predictions without having to build custom pipelines. Ensure data consistency between offline training and online inference, eliminating train-serve skew. Standardize data engineering workflows under one consistent framework. Teams use Feast as the foundation of their internal ML platforms. Feast doesn’t require the deployment and management of dedicated infrastructure. Instead, it reuses existing infrastructure and spins up new resources when needed. You are not looking for a managed solution and are willing to manage and maintain your own implementation. You have engineers that are able to support the implementation and management of Feast. You want to run pipelines that transform raw data into features in a separate system and integrate with it. You have unique requirements and want to build on top of an open source solution. -
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Butler
Butler
Butler is a platform that helps developers turn AI into easy to use APIs. Create, train, and deploy AI Models in minutes. No AI experience required. Use Butler’s easy-to-use user interface to build a comprehensive labeled data set. Forget about painful labeling exercises. Butler automatically chooses and trains the correct ML model for your use case. No need to spend hours analyzing which models perform the best. With a library of features to customize, Butler enables you to tune your model to your exact requirements. Stop spending time wrestling with rigid predefined models or building homegrown custom solutions. Parse key data fields and tables from any unstructured document or image. Free your users from manual data entry with lightning fast document parsing APIs. Extract information from free form text like names, places, terms and any other custom data. Make your product understand your users the same way you do. -
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Incedo Lighthouse
Incedo
Next generation cloud native AI powered Decision Automation platform to develop use case specific solutions. Incedo LighthouseTM harnesses the power of AI in a low code environment to deliver insights and action recommendations, every day, by leveraging the capabilities of Big Data at superfast speed. Incedo LighthouseTM enables you to increase revenue potential by optimizing customer experiences and delivering hyper-personalized recommendations. Our AI and ML driven models allow personalization across the customer lifecycle. Incedo LighthouseTM allows you to achieve lower costs by accelerating the loop of problem discovery, generation of insights and execution of targeted actions. The platform is powered by our ML driven metric monitoring and root cause analyses models. Incedo LighthouseTM monitors the quality of the high volumes of frequent data loads and leverages AI/ML to fix some of the quality issues, thereby improving trust in data. -
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integrate.ai
integrate.ai
We help developers solve the world’s most important problems by unlocking the value from sensitive data, without increasing risk. That's why we're building tools for privacy-safe machine learning and analytics for the distributed future of data. Data of all types are being generated and stored in the cloud, on prem, and increasingly at the edge. The cost of de-identifying, moving, centrally storing, and managing high volumes of data can be prohibitive. HIPAA, GDPR, PIPEDA, CCPA and other regulations limit the ways data can come together, especially across jurisdictions. With federated learning and analytics, only model parameters leave each private server, so data custodians retain full control of their data. Grow your business with existing customers by building valuable new product features that harness the collective intelligence of your customers' data. -
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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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TAZI
TAZI
TAZI is highly focused on business outcome and ROI of AI predictions. TAZI can be used by any business user, whether it is a business intelligence analyst or a C-level executive. TAZI Profiler to immediately understand and gain insights on your ML-Ready data sources. TAZI Business Dashboards and Explanation model to understand and validate the AI models for production. Detect and predict different subsets of your operations for ROI optimization. Empowers you to check data quality and important statistics by automating the manual work usually involved in data discovery and preparation. Makes feature engineering easier with recommendations even for composite features and data transformations. -
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Yottamine
Yottamine
Our highly innovative machine learning technology is designed specifically to accurately predict financial time series where only a small number of training data points are available. Advance AI is computationally consuming. YottamineAI leverages the cloud to eliminate the need to invest time and money on managing hardware, shortening the time to benefit from higher ROI significantly. Strong encryption and protection of keys ensure trade secrets stay safe. We follow the best practices of AWS and utilize strong encryption to secure your data. We evaluate how your existing or future data can generate predictive analytics in helping you make information-based decisions. If you need predictive analytics on a project basis, Yottamine Consulting Services provides project-based consulting to accommodate your data-mining needs. -
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Arthur AI
Arthur
Track model performance to detect and react to data drift, improving model accuracy for better business outcomes. Build trust, ensure compliance, and drive more actionable ML outcomes with Arthur’s explainability and transparency APIs. Proactively monitor for bias, track model outcomes against custom bias metrics, and improve the fairness of your models. See how each model treats different population groups, proactively identify bias, and use Arthur's proprietary bias mitigation techniques. Arthur scales up and down to ingest up to 1MM transactions per second and deliver insights quickly. Actions can only be performed by authorized users. Individual teams/departments can have isolated environments with specific access control policies. Data is immutable once ingested, which prevents manipulation of metrics/insights. -
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Materials Zone
Materials Zone
From materials data to better products, faster! Accelerates R&D, scale-up, and optimizes manufacturing QC and supply chain decisions. Discover new materials, use ML guidance to forecast outcomes, and achieve faster and improved results. Build a model on your way to production. Test the model's limits behind your products to design cost-efficient and robust production lines. Use models to predict future failures based on supplied materials informatics and production line parameters. The Materials Zone platform aggregates data from independent entities, materials providers, factories, or manufacturing facilities, communicating between them through a secured platform. By using machine learning (ML) algorithms on your experimental data, you can discover new materials with desired properties, generate ‘recipes’ for materials synthesis, build tools to analyze unique measurements automatically, and retrieve insights. -
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Diveplane AI
Diveplane
With the proliferation of AI tools there has never been more critical time to support the ethical use of technology and data. Diveplane ® offers AI-powered business solutions across multiple industries. With six patents approved and multiple pending, our groundbreaking next generation AI gives you full understanding and decision transparency in support of your ethical AI policies and data privacy strategies. We designed this technology to put machines and people in harmony to produce verifiable data intelligence in support of leading-edge competitive business strategies. Diveplane allows humans to understand exactly WHY a decision was made, shining where neural networks can’t. Accountability is important, and Diveplane allows the user to see exactly what data influenced a decision, as well as how influential it was. -
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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. -
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RTE Runner
Cybersoft North America
It is the artificial intelligence solution to analyze complex data, empower decision making and transform human and industrial productivity. It is the automated machine solution that has the potential to reduce the burden on already overwhelmed teams by automating the main bottlenecks in the data science process. It breaks data silos with the intuitive creation of data pipelines that feed live data into deployed models and then dynamically creates model execution pipelines to obtain real-time predictions on incoming data. It monitors the health of deployed models based on the confidence of predictions to inform model maintenance. -
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SparkAI
SparkAI
SparkAI combines people and technology to resolve AI edge cases, false positives, and other exceptions encountered live in production, so you can launch & scale automation products faster than ever. -
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Amazon Monitron
Amazon
Detect machine issues before they occur with machine learning (ML), and take action. Start monitoring equipment in minutes with easy installation and automatic, secure analysis through the Amazon Monitron end-to-end system. Improve system accuracy continuously as Amazon Monitron learns from technician feedback entered in the mobile and web apps. Amazon Monitron is an end-to-end system that uses machine learning to detect abnormal conditions in industrial equipment and enable predictive maintenance. Save on costly repairs and prevent factory equipment downtime with easy-to-install hardware and the power of ML. Reduce unplanned equipment downtime with predictive maintenance and machine learning. Amazon Monitron uses machine learning on temperature and vibration data. Amazon Monitron can help you predict equipment downtime before it happens. Compare what it costs to get started with how much you could save. -
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Monitaur
Monitaur
Creating responsible AI is a business problem, not just a tech problem. We solve for the whole problem by bringing teams together onto one platform to mitigate risk, leverage your full potential, and turn intention into action. Uniting every stage of your AI/ML journey with cloud-based governance applications. GovernML is the kickstarter you need to bring good AI/ML systems into the world. We bring user-friendly workflows that document the lifecycle of your AI journey on one platform. That’s good news for your risk mitigation and your bottom line. Monitaur provides cloud-based governance applications that track your AI/ML models from policy to proof. We are SOC 2 Type II-certified to enhance your AI governance and deliver bespoke solutions on a single unifying platform. GovernML brings responsible AI/ML systems into the world. Get scalable, user-friendly workflows that document the lifecycle of your AI journey on one platform. -
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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 -
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Amazon SageMaker Debugger
Amazon
Optimize ML models by capturing training metrics in real-time and sending alerts when anomalies are detected. Automatically stop training processes when the desired accuracy is achieved to reduce the time and cost of training ML models. Automatically profile and monitor system resource utilization and send alerts when resource bottlenecks are identified to continuously improve resource utilization. Amazon SageMaker Debugger can reduce troubleshooting during training from days to minutes by automatically detecting and alerting you to remediate common training errors such as gradient values becoming too large or too small. Alerts can be viewed in Amazon SageMaker Studio or configured through Amazon CloudWatch. Additionally, the SageMaker Debugger SDK enables you to automatically detect new classes of model-specific errors such as data sampling, hyperparameter values, and out-of-bound values. -
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Amazon SageMaker Model Training reduces the time and cost to train and tune machine learning (ML) models at scale without the need to manage infrastructure. You can take advantage of the highest-performing ML compute infrastructure currently available, and SageMaker can automatically scale infrastructure up or down, from one to thousands of GPUs. Since you pay only for what you use, you can manage your training costs more effectively. To train deep learning models faster, SageMaker distributed training libraries can automatically split large models and training datasets across AWS GPU instances, or you can use third-party libraries, such as DeepSpeed, Horovod, or Megatron. Efficiently manage system resources with a wide choice of GPUs and CPUs including P4d.24xl instances, which are the fastest training instances currently available in the cloud. Specify the location of data, indicate the type of SageMaker instances, and get started with a single click.
