Superb Model
Train and deploy powerful models
in no time
Adopt, evaluate, and scale advanced AI with minimal effort using no-code deep learning model training and deployment.
A Seamless Ecosystem for End-to-End Machine Learning Development
Run your entire ML lifecycle from lab to production on one platform - from curating and labeling datasets to training, evaluating, and deploying models.
STEP 01
Select Baseline Model
Start with the best models
Begin developing AI in seconds with powerful baseline models. Select the model that best matches your use case or performance needs. New models are added and updated whenever algorithms are released, so you can always access the latest and greatest versions.
STEP 02
Select Data & Train
Let AutoML do the hard work
Whether you’re a business user, ML engineer, or developer, AutoML allows anyone to use ML to improve business outcomes. Simply select your dataset, and AutoML will automatically train your model using the optimal hyperparameters. Zero coding required.
STEP 03
Evaluate & Upgrade
Observe and iterate with ease
Get full transparency with an instant interface for evaluating model performance, including class-wise precision, recall, IoU, and more. Iterate efficiently by uncovering performance gaps and errors, and know what to curate and label to remedy or enrich your data.
STEP 04
Deploy & Monitor
Deploy and serve in one click
Deploy models to the cloud and access them via API endpoint, all in one click - no coding or infrastructure headaches to deal with. Just as easily monitor performance, refine with additional training, and replace models in production, all in one place.
Automatically train models with one click
Leverage our AutoML technology to train high-performance models, regardless of technical expertise, and prototype faster with powerful baseline models.
AutoML makes AI accessible for all
With AutoML, anyone can train, evaluate, and deploy models with zero coding. AutoML automates and abstracts away many of the steps and technical challenges in the ML workflow that make it difficult to adopt AI, empowering developers and business users alike to build computer vision applications.
"As a product manager with no technical background, I was able to train and deploy an AI model using this platform. It's intuitive, user-friendly, and requires no coding, making AI accessible for everyone."
Product Manager, Healthcare Company
AutoML saves ML engineers valuable time
With AutoML, ML engineers can quickly conduct feasibility checks, create prototypes, and confirm dataset quality, all without wasting hours or even days training a custom model only to discover that the dataset wasn’t good enough. AutoML allows your technical team to spend time on what matters most.
Easily evaluate and optimize performance
Everything you need to continually improve the predictive performance of your models - without ever breaking a sweat.
Diagnose model performance
Easily evaluate the performance of your models with accuracy, precision, and recall metrics, and compare different model trainings to uncover the best version for production. Know what changes to make to your underlying data by finding slices your model performs poorly on and why, including filtering by error type.
Hone models to perfection
Continual iteration is key to improving and maintaining performance, but often involves countless hours of fine-tuning model weights or architecture. Superb Model shows precisely when a model fails and how to remedy it by improving your data, including uncovering gaps in your training datasets and opportunities for enrichment.
Quickly deploy and manage models
Go from trained model to production in seconds with complete control and transparency.
Deploy to the cloud with one click
Create API endpoints for your models without writing a single line of code, and easily swap out deployed models with new, enhanced versions. Superb Model makes integrating AI into your product, service, or business logic incredibly simple.
Monitor and control AI usage
Visualize and track model endpoint usage with volume and frequency metrics to better understand performance and improve resource allocation. Easily control endpoint settings and turn them on or off with ease whenever needed.