Jumpstart your AI transformation with a unified interface that combines all the building blocks you need to go from data to AI outcomes
Data scientists can use our notebook interface on web, or choose their preferred notebook interface and use the RapidCanvas SDK.
Business users can use our no-code interface and drag-and-drop options, making it easy for them to explore and analyse data without needing coding skills.
Setup and configure custom environments depending on the size of your data, libraries you need, compute requirements, and prediction requirements, whether batch or real-time.
Enjoy seamless GIT integration.
Bring your data in a few clicks from anywhere across cloud storage solutions such as S3 buckets, Azure blob, Google Cloud storage, databases such as Redis, MongoDB, data warehouses such as Snowflake, Google BigQuery, or bring your own data connectors.
Connect your data from anywhere; over 300+ third-party apps are supported out-of-the-box.
Get a quick start with ready-made templates for exploratory data analysis, data cleanup, quick feature correlation, and ontology.
For doing any data transformations via code, create templates as you need and publish them to your workspace. Published templates are available even for no-code business users in exploring and preparing the data, and enable seamless collaboration on your project.
Perform joins and aggregations, and any data transformations using prebuilt templates. Augment your data with any third-party data for deriving larger insights.
Use automated feature engineering and unlock the value from advanced techniques like deep feature synthesis to identify complex relationships and generate new features from raw data.
Automatically identify and select the most relevant features for your model and ensure that you are using only the most informative features and avoid overfitting.
Use our prebuilt machine learning models or build your own machine learning models quickly and efficiently using our copilot. Our prebuilt models provide coverage across problem types such as classification, clustering, continuous estimation, time-series analysis, recommendation engines, anomaly detection, optimisation.
Automatically evaluate, rank and use the most effective machine learning model for your data. Optimise the hyperparameters of your models such as learning rate, and improve the performance and accuracy of your models.
Access any machine learning model as a service via API and get predictions to feed into your business workflows. Build explainability into your modeling workflow with visual flows.
Easily deploy your models to production. Get either batch predictions or real-time predictions depending on the needs of your business.
Create segments from your data to better understand any niche or underlying patterns and deal with them using alternate ML models via scenarios. Get segment specific insights.
Create different versions of your ML Models with different configuration/tuning of hyperparameters.
Do what-if analysis via data apps for last mile considerations, experiments and prudent decision-making in operations and customer-facing roles.
Build dashboards and reports to tell beautiful data stories the way you imagine with visualisations, analysis and insights you want.
Publish custom interactive data apps to your operations and customer-facing team so that they get the alerts, signals and triggers they need, to do better at what they do.
Control access to your custom apps via secure authentication using single sign on.
At RapidCanvas, we empower human experts to focus on problem solving and create great products using data, in a matter of days. Combine domain expertise and automated machine learning to build the future.
