AUTOMATICALLY ADAPT YOUR DEEP LEARNING MODEL DESIGN
- Integrate your business and production constraints into the design of your models
- Generate model variants thanks to RAISE and its Deep Neuroevolution technology
- Select the model best suited to your case
- Automatically adapt your model to changing data (Datadrift)
- Use RAISE in many other use cases: bias control, ensembling, distributed learning...
For AI engineering users
A Powerful change in AI model design
RAISE allows the selection to business and production requirements to be integrated into the process of automated model creation instead of a manual trial-and-error process today.
enhancement with RAISE
each profile has its benefits
Optimize any existing AI deep learning model
Create models that auto-adapt to changing reference data (DataDrift handling)
Unlock Ensembling (e.g. having different AIs with different biases) to get consensus-based decisions
Behavioral model selection focus on constraints
Compatible with most market frameworks (Tensor Flow, Pytorch...)
Industrialize NN-based AI creation to open the democratization of AI
Allows Data Scientist to focus on modeling the business problem rather than focusing on technical prowess
Process can keep data confidential and work on spread sources
robust and resilient AI models
designed to meet business challenges
Towards the 1st AI model for your business
For companies wishing to have an AI model, the RAISE platform automatically and easily generates an artificial intelligence architecture customized according to your business needs and your data.
For skilled Enterprise AI Users
For companies already aware of and using AI, RAISE accelerates the performance of existing neural network models. The platform leverages your data scientists' strike force by building even more scalable AI models, allowing them to focus on preparing new models for new projects.
Suitable for all sizes and types of businesses
our custommers and use cases
Join our partners and offer your customers unique automated AI generation software