ML Can Be Complex, Confusing
and Costly With Other Tools
You shouldn’t need to jump over hurdles to use machine learning. That just slows your development.
With mlOS, Machine Learning is Easy
See mlOS in Action
A production machine learning platformwith extreme speed and control
Braintoy’s machine learning operating system (mlOS)
is loaded with features that make it easy to build, deploy, and monitor ML models at scale.
Braintoy's mlOS is a first of its kind.
A production machine learning platform
for people who need to build AI, FAST!
No-Coding or Coding
Light Mode or Dark Mode
Production Machine LearningFAQ
Artificial intelligence (AI) is a branch of computer science that endeavors to replicate or simulate human intelligence in machines so that they can think like humans and mimic their actions. AI systems are powered by machine learning and deep learning with the characteristic to rationalize and take actions that offer the best chance to achieve the target goal.
A model is what you get when you combine data with a machine learning algorithm. The three stages in building a model are the training, testing, and prediction. The training trains the model using past data, the testing phase validates the accuracy of the model that is built, and the prediction phase is when the model is deployed to production and live data fed into the model to predict the outcomes.
Tabular, vision, text, and time series can be used. Tabular data has rows and columns. Vision data is in the form of images or images from video. Text data is in the form of text such as documents, emails, or transcribed speech, commonly referred to as Natural Language Processing (NLP). Time series data is a series of data points indexed in time order and typically comes from sensors. mlOS comes pre-shipped with preprocessing algorithms for all such data types. You can also add your custom preprocessing algorithms as a code block.
mlOS is pre-shipped with over 60 popular algorithms. There are general-purpose classifiers and regressors for supervised learning e.g. Random Forest, Support Vector Machine (SVM), Deep Learning classifiers and regressors e.g. TensorFlow, as well as NLP classifiers e.g FastText. Algorithms are updated and added regularly. You can also add custom algorithms.
Models are deployed on the web as an API endpoint with a unique identifier. A user can now make requests to the model API endpoint URL and get predictions in real-time.
Every model is unique and version controlled. The user has the ability to build, view, interact with, customize, make new versions of, accept, reject or deploy any model. One model can be swapped for another one seamlessly.
Braintoymakes AI accessible.
who struggle with the complexity of machine learning, Braintoy makes it easy to build and deploy ML models in your applications.
For Development Teams
who struggle to collaborate when building and deploying machine learning in your products, Braintoy simplifies collaboration.
who struggle to afford and develop AI solutions that can increase their competitiveness, Braintoy makes AI feasible.