What's New

With new NLP hyperparameters and the power of automation, you can run new AI experiments much faster with DataRobot AI Cloud, which takes text data prediction explanations to the next level. Understand the impact of text, such as patterns of positive and negative feedback in customer reviews or product feedback. Access more granular insights to help determine new use cases and increase the trust, usability, and explainability of text features.

Find scale and speed with improvements in scoring code for time series models that involve large datasets. Now you can download the scoring code for time series models and run predictions on your largest datasets outside DataRobot AI Cloud in the environment of your choice. 

On top of these new features, we are excited to announce that Algorithmia is now integrated with the DataRobot AI Cloud platform. Reduce operational costs for AI projects by deploying custom models to the Algorithmia environment. Take advantage of autoscaling deployment while benefiting from the DataRobot MLOps built-in capabilities.
Learn more about other features that are only found in the DataRobot AI Cloud platform.

Navigate uncertainty with AI-powered forecasting

Customer behavior and needs have changed dramatically. As a result, businesses are becoming more agile to keep up with changes to identify new opportunities that meet customer needs.  Identifying trends in data helps to anticipate, which is why companies rely more on forecasting. But forecasting remains complex and laborious.  It requires manual updating of data and adjustments to forecast outputs. These steps can delay decisions, preventing businesses from responding immediately to new demand patterns and market changes.

AI-powered forecasting enables organizations to respond to changes faster and make the right decisions. A broader set of data scientists leverage DataRobot AI Cloud advances AI forecasting to combine automation with best-in-class modeling techniques to streamline forecasting. Now you can experiment faster, build models for new segments without sacrificing accuracy, and most importantly, operationalize models in a few clicks completely out-of-the-box.

Learn more about what’s new in DataRobot AI Cloud.

As AI adoption matures across organizations, there are increased business requirements for scale, speed, and ensuring that AI models are fair and accurate. The DataRobot AI Cloud May 2022 Release, the first in a series of monthly releases for the cloud-based AI platform, focuses on new features that help users spend less time on scripting and uploading data and more time focusing on refining models and delivering impactful results. 

The DataRobot AI Cloud May 2022 Release delivers nearly 40 new features to help data scientists and business leaders deliver AI results in a rapidly changing world.

Businesses across all industries are facing challenges and uncertainties. DataRobot AI Cloud 8.0 is the mission-critical innovation that empowers organizations to navigate changing market conditions and drive clear business results from accelerated growth, reduced operational costs, and improved customer engagement.

DataRobot AI Cloud 8.0 brings to market over 40 new and enhanced capabilities, further enriching one of the most trusted and widely deployed AI platforms in the world. Among the new capabilities are:

1. Time Series Integration with AI App Builder
2. Continuous AI extended to the entire multi-cloud architecture, including on premise environments
3. Enhanced connectivity extending to Microsoft Active Directory connections for SQL Server with Synapse and Scoring Code for Snowflake

Together, these new capabilities will help every business to navigate the most unpredictable of markets with better and more intelligent predictions.

We understand how critical it is to have access to AI-powered insights at the right time. Now users will be able to rapidly create intelligent applications on top of time series deployments and access actionable forecasts in a matter of minutes.

DataRobot AI Cloud 8.0 continuously monitors all models in production, keeping every model running at peak performance while adjusting for drift, adapting to changing ethics standards, and supporting governance policies. With real-world changes challenging every business on a daily basis, from COVID to changing economic climates and more, the continuous monitoring that DataRobot AI Cloud 8.0 offers is more important than ever.

Additionally, we extended the connectivity of the AI Cloud platform to give you access to data from Azure Synapse SQL, while DataRobot Scoring Code supports execution directly inside Snowflake, allowing you to store large datasets even faster. This gives all of our customers connectivity to the broadest set of data sources, including AWS Redshift, Oracle, SAP Hana, and Google BigQuery, along with the power to build the most complete, highest quality models.

Let’s dive in!

Empower Business Users with Predictive AI Apps

Even as many global markets continue their recovery from an extended pandemic response, significant uncertainty remains in the marketplace. Now more than ever, fast and accurate decisions make a difference in business performance. With growing pressure on organizations to empower frontline decision-makers with actionable insights, more companies are looking for ways to leverage tools for automated forecasting.

In Release 7.3, we are thrilled to announce expanded capabilities and features for all users to enable AI-driven decisions across all lines of business within a single platform.

Composable ML is now available for SaaS users. We also took modeling to the next level. Now you can leverage new, out-of-the-box capabilities, such as multimodal clustering, segmented modeling, unlimited multiclass, and multilabel classification, and combine them with data you have to solve a diverse set of challenges.

As part of the MLOps product, automatic compliance documentation helps you accelerate your preparation for regulatory reviews for any model. In addition, with built-in Challenger Models Comparison, you can review and compare model behavior for the champion or challenger model before deciding on a model replacement. 

In addition, Release 7.3 extends capabilities for our No-Code AI Apps. Now, the easy-to-use, customizable app builder supports time series models, allowing you to build more AI-driven apps for different complex use cases with no code. 

These are just a few headlines. Let’s dive in!

Code-Centric Data Science

Composable ML

Augmenting Your Expertise with World-Class Automation. We are happy to share that DataRobot Composable ML is available in the 7.3 Release for SaaS users. Composable ML provides customizable blueprints containing reusable building blocks so that data science experts can save time on managing libraries, editing code, and prepping routine model operations tasks and focus instead on experimenting with data, working with advanced algorithms, and other high-value data science activities. DataRobot can automatically generate and train blueprints to bring good options to the surface, which a data scientist can marry up with custom code to create new tasks and incorporate any modeling logic you want. Share the components you create, and all users in your organization will benefit from your work. Focus on the task and the code, and seamlessly integrate with a wide range of DataRobot capabilities with no extra DevOps work: Leaderboard, Insights, Compliance docs, Deployments, Monitoring and Governance, and more.

In release 7.2, we have opened up DataRobot for data science experts who love to code via Composable ML and code-centric data preparation and pipelines. MLOps adds Continuous AI to keep production models at peak performance, bias monitoring to keep models fair, and new Decision Intelligence flows that let you apply business rules to each and every prediction.

Keep reading to understand more about our most exciting release yet.

Powerful Tools for Data Science Experts Who Love to Code

Composable ML

Your Expertise Extended with Our World-Class Automation. To build best-in-class models, data scientists need to constantly experiment with data and algorithms. In reality, data scientists spend much of their time on repetitive or mundane tasks, like writing code for feature transformations or model operationalization, leaving them with little time to actually experiment.

As we reach the midpoint of 2021, we’re thrilled to announce our second major release of the year! In AutoML, automated feature discovery with push-down integration for Snowflake is now generally available. Automated Time Series now includes automatic data prep, and we have enhanced our unique Eureqa forecasting models. MLOps users can now perform major lifecycle operations on remote models using our new MLOps management agents. We’ve also introduced No-Code AI Apps that allows you to quickly create beautiful and powerful AI applications using a visual drag-and-drop user interface. No coding skills required.

And this is just a fraction of the release. Are you excited? So are we, so let’s jump in.

Automated AI Reports

Trusted Insights for Your AI Projects. Automated AI Reports are now available. AI reports are designed to summarize the most important findings of your modeling project to stakeholders in an easily consumable format. In just a few clicks you receive a comprehensive summary of your AI project. The report provides accuracy insights for the top-performing model, including speed and cross-validation scores. It also captures interpretability insights from the Feature Impact histogram for your top-performing model. Detailed model explanations , performance metrics, and ethics insights generated in the AI Report help you build overall trust in your AI projects and prove value to your key stakeholders.

It’s our very first release of 2021, and we’re excited to share it with you. Release 7.0 of DataRobot, provides innovation across our entire platform through enhancements to all the products you know and love. We’ve improved our scoring tools in Data Prep, added image augmentation to Visual AI, introduced customizable compliance reports in AutoML and AutoTS, and added a way to easily compare your forecasting models to ours. In MLOps, we’ve added the ability to challenge any model built in any language or framework, and deployed to any environment. Here are the major headlines for this exciting new release.

Enhanced Prediction Preparation

Ultimate Flexibility For Scored Data. DataRobot’s self-service data preparation just got even more powerful in Release 7.0. Not only can you quickly and easily prepare your data for model training, you can also use our visual data prep capabilities to score new data after your models are built and use it for whatever purpose you choose. Since our data prep tools work seamlessly within our end-to-end AI Platform, we make it incredibly easy for anyone to get scored data from any deployed model. You can then integrate the scored data back into your production data pipelines or write it out to a huge variety of well-known enterprise data sources on-prem and in the cloud. All of the scored data is intelligently cached to accelerate the read performance of downstream applications. You can also get both SHAP and XEMP-based explanations for every single prediction, ensuring full transparency and trusted AI.

DataRobot Release 6.3 is here and contains bounty of highly requested features. Bias and fairness testing is new in Automated Machine Learning, MLOps introduces Portable Prediction Servers, and Automated Time Series includes visual feature lineage, new deep learning blueprints, pre-loaded holiday calendars, and many other enhancements to provide deeper insights and more human-friendly explanations for all your time series models.

Automatic Bias and Fairness Testing

AI that Shares Your Values. A key component of building trusted AI is ensuring alignment with your ethics and values. New in DataRobot Release 6.3, bias and fairness testing allows you to flag protected features in your dataset and then actively guides you through the selection of the best fairness metric to fit the specifics of your use case. Once your models are built, we then surface visual insights to illustrate the results of the selected bias and fairness test. If bias is identified, you can use the Cross-Class Data Disparity tool to perform root cause analysis, diagnosing the source of bias in your data, and ultimately directing you towards mitigation steps in your data collection or processing.

DataRobot Release 6.2 is here, and it’s packed with innovation for every step of your AI journey from data to value. The release includes next-level feature discovery, a new comprehensive autopilot mode for maximum accuracy, anomaly assessment insights, governed approval workflows for MLOps, and so much more.

Next-Level Feature Discovery

Find Predictive Signal In Related Data. Release 6.2 takes our automated feature discovery capabilities to a new level. We have enhanced the dataset relationship workflow, making it much more intuitive. You can now select multiple datasets, as well as define, edit, and visualize all your relationships at the same time. Feature discovery is also more transparent. You can access logs to get details on which features were explored, discarded, or generated. You can also download the full training dataset, including all the values derived during the feature discovery process.