| A | B | C | D | E | F | ||
|---|---|---|---|---|---|---|---|
1 | name | url | service | category | capabilities | pitch | |
2 | 4paradigm | https://www.4paradigm.com/ | Migration Learning | SaaS | end-to-end lifecycle support | help enterprises improve efficiency, reduce risks, and obtain greater commercial value | |
3 | Abacus.AI | https://abacus.ai/ | Abacus.AI | SaaS | NAS and HPO for DL | easily and effortlessly embed cutting-edge deep learning models into their business processes, or customer experiences | |
4 | Aible | https://www.aible.com/automl-ai-for-business-impact/ | Blueprints | core | Gartner 2019 Cool Vendor | bring together the best in data science, domain expertise and modeling for business impact, giving you AI superpowers | |
5 | Amazon | https://aws.amazon.com/sagemaker/ | SageMaker | cloud | HPO; auto-scaling | tune and optimize models for deployment | |
6 | Auger | https://auger.ai/product | Auger | SaaS | data cleaning; features, HPO | patented Bayesian optimization search of ML algorithm/hyperparameter combinations | |
7 | Big Squid | https://www.bigsquid.com/kraken-platform | Kraken | SaaS | model development in BI platforms | gives business users deeper insight into the value and quality of their existing data | |
8 | BigML | https://bigml.com/features | BigML | SaaS | end-to-end lifecycle support | removes the complexities of Machine Learning so you can focus on what matters most, enhancing and automating decision making | |
9 | Comet | https://www.comet.ml/parameter-optimization | Comet.ml Hyperparameter Optimization | core | HPO; end-to-end lifecycle support | track code, experiments, and results on ML projects | |
10 | Compellon | https://www.compellon.com/explainable-bias-free-analytics/ | 20|20 | SaaS | model selection; continuous learning and evaluation | clear-box machine learning that provides valuable insights from your data to improve your business outcomes | |
11 | DataRobot | https://www.datarobot.com/platform/ | Automated Machine Learning | core | end-to-end lifecycle support | data scientists of all skill levels build and deploy accurate predictive models in a fraction of the time it used to take | |
12 | Determined AI | https://determined.ai/product/ | Determined AI | core | NAS and HPO for DL; reproducibility, GPU use optimization | search-driven model development, a new paradigm that can reproduce results from months of iterative work in 24 hours | |
13 | dotData | https://dotdata.com/product-overview/ | dotData Enterprise | core | end-to-end lifecycle support | enables your team to execute complex data science projects with speed, and at scale | |
14 | Firefly | https://firefly.ai/product/ | Firefly AI | core | end-to-end lifecycle support; incl. meta-learning | expedite the creation and deployment of machine learning models | |
15 | https://cloud.google.com/automl/ | Cloud AutoML | cloud | end-to-end lifecycle support | handles all of the hard work and trains and tunes your model for you | ||
16 | H2O | https://www.h2o.ai/products/h2o-driverless-ai/ | Driverless AI | core | end-to-end lifecycle support | everyone can develop trusted machine learning models | |
17 | IBM | https://www.ibm.com/cloud/watson-studio/autoai | AutoAI | cloud | end-to-end lifecycle support | enforce consistency and repeatability of end-to-end ML and AI development | |
18 | Kortical | https://kortical.com/ | Kortical | SaaS | model development | accelerate the creation, iteration, explanation and deployment of world class machine learning models | |
19 | Microsoft | https://azure.microsoft.com/en-us/services/machine-learning-service/ | Azure Machine Learning service | cloud | end-to-end lifecycle support | build models rapidly and operationalize at scale from cloud to edge | |
20 | MLJAR | https://mljar.com/automl/ | MLJAR Cloud | SaaS | end-to-end lifecycle support | anyone can train great machine learning models | |
21 | R2 | https://r2.ai/product | R2 Learn | SaaS | model development | cutting-edge AI development and deployment platform to drive mass AI adoption | |
22 | Salesforce | https://help.salesforce.com/articleView?id=custom_ai_prediction_builder.htm&type=5 | Einstein Prediction Builder | SaaS | model development; prescriptive analytics workflow | generate a churn prediction system from customer data | |
23 | SigOpt | https://sigopt.com/product/ | Optimization Engine | core | black-box HPO | accelerate and amplify the impact of machine learning, deep learning, and simulation models | |
24 | SparkCognition | https://www.sparkcognition.com/product/darwin/ | Darwin | SaaS | data cleaning; features, HPO | go from data to model in less time than traditional methods, enabling the rapid prototyping | |
25 | Squark | https://squarkai.com/squark-seer/ | Seer | SaaS | model development in Excel | the brilliance of data science is packaged in an easy, online AutoML app | |
26 | Stratio | https://www.stratio.com/a-data-centric-product/ | Rocket | core | end-to-end lifecycle support | AI-based data management, semantic ontologies, etc. | |
27 | Tazi | https://www.tazi.ai/platform/ | Tazi Platform | SaaS | model selection; continuous learning and evaluation | businesses cost reduction, increased efficiency, enhanced (dynamic) business insights, new business (uncovered) and business automation | |
28 | TIMi | https://timi.eu/products-solutions/timi/timi-modeler/ | TIMi Modeler | SaaS | model development | an analytic framework that covers all analytical needs, from the most basic data collection, KPI & dashboards to the creation of high-accuracy predictive Models | |
29 | Transwarp | http://transwarp.cn/en/transwarp/plan-study.html | Sophon | SaaS | end-to-end lifecycle support | help enterprises innovate and change in the AI era | |
30 | TurinTech | https://turintech.ai/platforms-evoml/ | EvoML | SaaS | end-to-end lifecycle support | evolutionary optimisation, enables enterprises to create, deploy and optimise AI at scale by automating the whole process of data science | |
31 | Xpanse | https://xpanse.ai/ | Xpanse AI | core | data/feature/models deployed to SQL | predicts customer behaviour by automatically integrating source data and analysing thousands of behavioural patterns in hours instead of months | |
32 | Zest Finance | https://www.zestfinance.com/zaml | ZAML | SaaS | data refining; model development | ML credit and risk modeling with end-to-end explainability | |
33 | |||||||
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