End-to-End MLOps Platform

Manage your datasets, keep track of your experiments, and deploy your models in a single MLOps platform.

Our platform covers it all

Picsellia’s Features

No need for a compute infrastructure or fast connectivity. Picsellia's infrastructure is robust and redundant—we handle the tedious work so you can focus on what really matters to your business: developing your AI models.
Datalake dashboard

Data Management

Ensure data consistency. Store, search, filter, and annotate all your data in one single place.

Picsellia’s centralized and intuitive labeling interface lets your teams annotate simultaneously.

Our native versioning feature lets you go back to your old annotations, experiments, and models, at any time.
Datalake dashboard

Experiment Tracking

Assure reproducibility and traceability. Track and compare your experiments and find your best-performing model. Once identified your best architecture, Picsellia helps you find the best hyperparameter combination to optimize your model performance.

Store and share your experiments and models, on a single platform.
AI experiment tracking graphics
Cloud connected serverless platform

Model Deployment

Put your models into production in just one minute, without a server. Enjoy Picsellia’s robust infrastructure and native monitoring. We deploy your models for you, so you can focus on developing your models. We’ll give you a scalable and serverless API endpoint!
Cloud connected serverless platform

Model Monitoring

Monitor your model performance in real-time. Identify and fix potential failure cases, before your clients experience them. Identify exceptions in no time and add them to your training set.
production reviewed
ML pipelines showing computer vision workflow

Automated Pipelines

Turn your computer vision life cycle into a workflow. Easily set up automatic triggers based on any event, to notify you and your team when something goes wrong.

Directly visualize and review your predictions to debug your models and increase your training set.
ML pipelines showing computer vision workflow

Got any questions?

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