AI is tough, we made it simple.
Opportunity cost - rapidly tune and propagate model changes to strengthen the level of trust that users have in existing models.
Visibility - understanding how frequent a model is used and which applications and processes depend on them enable portfolio managers to confirm that model changes do not incur unintended consequences.
Adoption - it's easy for users to adopt built models since they could easily be integrated into existing applications and processes.
Standardization - with a common ML platform for a team or organization, it is easier to bring disparate ML assets together, govern all models from a central location and serve models to applications from one ML abstraction layer
Usability - simpler user interface (wizard-based) reduces complexity in solving complex machine learning problems.
Collaboration - a visible repository of enterprise modeling assets will foster collaboration and improve how AI capabilities developed are shared in an organization. Collaborative design and development lead to better AI products for an organization.
Extensibility - open source ML and AI algorithms and libraries are available for model builders across the enterprise (e.g. TensorFlow, H20, ScikitLearn and more)
Automation - rapidly develop and scale model to production - no need to develop API’s and micro-services; no need to write documentation for the model development process, easily track different versions of models.
Connect to or upload data sets, clean, explore, prepare, extract features, generate test datasets, normalize and visually analyze data for better understanding. Connect both structured and unstructured data sets in Hadoop, google cloud storage, MSSQL, PostgreSQL, Google drive and more and define data for modeling.
Choose from over 60 built-in algorithms to pre-process, transform and enrich data sets for modeling; Install packages or write custom data preprocessing algorithms in Jupyter notebooks, add to the platform, share and collaborate with team members.
Machine Learning Engine
Build machine learning models using classification, regression, and deep learning techniques. Choose from over 100 machine learning algorithms to solve problems in various domains including predictive analytics, image, video, audio, text, and voice as well as multivariate time series analysis.
Customize algorithms or just create a new one of your own. Create and apply model recipes to different data sets. Tag and track models, share for collaboration, visually analyze model performance and more.
Govern models for safe and ethical AI. Discover automated documentation, record data preparation, model building steps for easy and fast reproduction. Analyze results and feature performance, share and communicate with peers and portfolio managers to publish models towards deployment.
Manage different versions of created models, audit, schedule and swap out old models for new ones, and more.
Deploy models to production. Generate automated code around machine learning models, utilize automated deployment, effortless docker image creation and deploy to kubernetes. Discover API logging and controls, API key and AUTH generation and more.
Monitor and manage deployed models
Discover automated reports, monitor, and manage models deployed to production
Be an expert with more control. Utilize user management, control access privileges, manage versions, import models and collaborate with your team effectively and more.
Edit and create custom solutions in Jupyter notebook.
1 Named User
Data file upload
Create 5 models
Pay to deploy
1 - 5 named users
GPU on demand
CPU scaling on demand
All features included
Big Data connectivity
Unlimited models & versions
Automated API gen
Kubernetes on demand
Our cloud (GCP)
Your cloud (AWS, Azure, GCP)
All features included, plus:
Data science 101
D2D in 4 steps
AI for executives
Benefits of Braintoy
Braintoy’s AI platform creates and administers collaboration between team members so your organization can put the bleeding edge to work on real issues that matter to your customers.
Braintoy’s AI pipeline automation helps you to gain a competitive advantage from using AI. We increase your productivity by providing modules that you can leverage in building and integrating AI applications into your business processes.
Our AI platform centralizes and standardizes AI capabilities and products across your organization. All the machine learning algorithms and custom algorithms that you create in your organization will be centralized and managed from one location. By creating centralized access we simplified the adoption of AI products into business processes and applications across your enterprise.
We believe that AI systems should be safe and trustworthy. Braintoy’s AI Platform breaks the black box open by making complex models more transparent. Our automated documentation and validation ensure that every business unit can connect their application and process to the latest in machine learning and artificial intelligence. Your organization can establish accountability, explainability, responsibility, and fairness, facilitating data science adoption across the enterprise.
Agility - speed development of use cases requiring an ML model by 81%
Reusability - reuse models and algorithms with ease without recreating from scratch
Safe & ethical AI - automated documentation and governance
Support & focus - incorporate feedback and improvement in a central model, revert to previous models or swap current models with new or existing ones.