Leading AI
to full scale production
MLOps & LLMOps platform
Develop, deploy and pilot in production your Machine Learning models and LLMs in record time. Bring MLOps into your company to accelerate the development of your AI projects and make them more reliable.
Develop, deploy and pilot your Machine Learning models in production in record time, without DevOps or ML Engineer.

Break through the wall of production
85% of AI projects fail to go to production - Gartner

Accelerate models into production
From 6 months to 3 clicks
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Systematise the return on investment
+75% AI in production

Control your infrastructure costs
Energy efficiency
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Drive end-user adoption
Explainable AI
Discover our method
MLOps for AI
Develop the best models
Integrate and unify your structured and unstructured data flows. Build your Machine & Deep Learning models using any open-source framework.
Fine-tune your LLMs on your data assets. Version data, features, models and work collaboratively. Set up complete pipelines from data preparation to model training.

Deploy your models on a large scale
Execute your Pipelines and track each run. Deploy your models, make their results available and set re-training conditions. Serve model results in real time. Have working environments dedicated to experimentation, testing and production. Choose the exact size of your infrastructure and precisely manage the cost of each project.

Monitor the performance of your models
Monitor the accuracy and reliability of all your production models. Evaluate the reliability of your LLMs (loss of context, accuracy drift, hallucinations or tone alteration). Detect drifts and anomalies in models or data. Set up alerts to react as quickly as possible. Manage your infrastructure and deployments in real time. Optimize your infrastructure costs with a FinOps module.

A platform compatible with the entire ecosystem
Develop a trustworthy AI
44% of companies see "black box" AI as a major risk
The State of AI 2021 - MCKinsey
Discover our vision
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Explainable AI (XAI)
Explain the predictions of your models and keep the human in the loop.
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Frugality
Minimise the amount of energy needed to train your models.

Privacy
Respect privacy and confidentiality of data. Synthesise your data.

Fairness
Remove all bias and discrimination from the data.
Discover our vision
Lead your AI to production
Test our MLOps platform for accelerating the deployment and piloting of Machine Learning models for free.
Request a demo
