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Dynamic Universes
Screening-based
Instruments selected based on current market conditions
Liquidity-based
Instruments selected based on current market conditions
Volatility-based
Instruments selected based on current market conditions
Correlation-based
Instruments selected based on current market conditions
Popular ML/AI Frameworks
Stable Baselines3 (SB3) is a set of reliable implementations of reinforcement learning algorithms in PyTorch.
TensorFlow makes it easy to create ML models that can run in any environment.
Scikit-learn, also known as sklearn, is an open-source, machine learning and data modelling library for Python. It features various classification, regression and clustering algorithms
Reuse existing models with our integration with Hugging Face, or train your own models
RLib is an open source library for reinforcement learning (RL), offering support for production-level, highly scalable, and fault-tolerant RL workloads
RLib is an open source library for reinforcement learning (RL), offering support for production-level, highly scalable, and fault-tolerant RL workloads
Other Features
Build, train, and deploy smarter trading strategies with seamless multi-broker and AI integrations.
Machine Learning Workflows
Machine learning workflows in Praevisio notebooks provide a comprehensive framework for developing, training, and deploying ML models for algorithmic trading. These workflows integrate seamlessly with the platform’s data infrastructure and deployment pipeline.
Multi Brokerage
Break free from the limitations of a single broker and unlock the full potential of your trading strategies. Our powerful Multi-Brokerage System empowers traders, platforms, and asset managers to seamlessly connect with multiple brokerage firms — all from one intuitive interface.
Market Training Data
Unlock the power of accurate, reliable, and comprehensive financial data — sourced directly from the industry’s most trusted providers
Distributed Training
Distributed training is a machine learning approach where training a model is split across multiple computing devices — typically multiple GPUs, nodes, or even data centers — to speed up the training process and scale to larger datasets or models.
Offerings
Our platform unifies the entire lifecycle—enabling quants, data scientists, and portfolio managers to seamlessly move from research
SAAS
Ideal for small trading groups, shared platform
24/7 Basic Support.
Managed Service
Request Custom Libraries
Bring your own data
Scalable Infrastructure.
SELF HOSTED
Dedicated platform, managed by you or managed by us
Bring your own data.
Secured access to internal network via VPN only or DX
Managed Service
24/7 Bespoke Support & Development
Scalable Infrastructure.