A complete Computer Vision development stack

All the tools you needs designed to super-charge your daily Data Science work.

Data Management & Annotation

Store your assets or access Open Data, manipulate your data in the most granular way, and annotate manually with optimized tools or leverage model-assisted annotation.
In one single place.

Experiment & Training Engine

Use dozens of base models with optimized parameters already filled for you. Leverage our training engine to quickly launch training, compare experiment and share your results with your team our community.

Deployment & Monitoring

Deploy production-ready model and monitor them in production. We automatically build feedback loops between your models and datasets to continuously improve performances.

Picsellia Data Management

A unique place to truly understand your data

Your own Datalake

Access a managed virtual Data Warehouse. You can now connect all your data sources to one unique place, filter, search, tag your assets and create meaningful datasets.

Easy to use
Enterprise ready
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Dataset Management

Manipulate your data like never before. Annotate, edit labels, merge annotations, leverage model-assisted annotation, and version your datasets so you're always confident in what you're working with.

Data annotation

Leverage our tools and automations in order to annotate Datasets the fastest way possible.

AI assisted Labeling tools

Leverage interactive segmentation tool in order to enhance speed and accuracy of your annotations.

Pre-annotation with your AI models

Fully automate your annotations and keep only the confident one in order to enlarge your training set easily.

Add context annotation

Simply add some questions & answers to create context annotation for your training sets.

Collaboration and feedbacks

Annotate as a Team and tag collaborators in your annotations to notify them when you need some help or second opinion.
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Picsellia Training & Experiment tracker

Insure reproductibility by tracking all your experiments and start organizing your work


Your go-to experiment storage

From hyper-parameters to trained model checkpoints and exported model through train/test/eval splits and training logs.

User friendly

Keep Track of all your experiments

Simply log every metrics that you want to monitor to visualize it in your experiment dashboard.

Log everything

Send every metrics that you want to log and analyze your trainings later.

Compare your experiments

You can compare every one of your results, from accuracy to loss curves so you are always aware of what has the most influence on your final models.

Share your work & collaborate

Invite your teammates in your project to work together. Collaborate on model creation seamlessly with comments, mentions and notifications.
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Quickly launch training from anywhere

We provide you with some already packaged training engine available in the most common formats.

Python Package

If you want to perform custom ML experiments, install our Python package to link your scripts with Picsellia seamlessly.

Docker Image

Simply pull our Docker image from Docker Hub to remotely launch training on any server.

Ready-to-use Notebooks

Or just run some notebooks on Google Colab or on your own machine.

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Picsellia Deployment & Pipelines

Manage your project life-cycle with our production pipelines.


Serve your models in production in a minute

Never worry about infrastructure with hosted models that are deployed for you automatically and start delivering value to your customers in no time.

Build your Pipelines

Simply create an enterprise grade pipeline between your models and your team by adding 2 lines of code.

First Version Deployed

Once you are satisfied with your model performance, simply deploy it and get your api endpoint.

Gather all predictions and store it into Picsellia

Visualize all prediction on Picsellia to analyze your model, configure rules to add them into your training data only if your models are confident enough.

Re-train your models

Use this new data to improve your model performances and enhance generalization.

Get a demo

We will get back to you as soon as possible


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