Picsellia is an MLOps platform for computer vision that helps build, deploy, and monitor vision AI applications. It centralizes visual data, supports annotation, model training, and deployment all in one place.
Picsellia is an end-to-end MLOps platform specifically designed for computer vision applications. It provides a comprehensive solution for managing the entire lifecycle of vision AI, from data collection and organization to model deployment and monitoring. Key features include a Datalake for centralizing visual data, advanced annotation tools with AI assistance, experiment tracking for model training, and robust deployment options. The platform supports various industries like manufacturing, agriculture, and energy, enabling teams to build and scale AI applications efficiently. Picsellia is ISO 27001 certified and offers flexible deployment options including cloud, on-premise, and hybrid configurations.
Best used for
Ideal for data scientists and ML engineers who need to centralize visual data, streamline annotation processes, and deploy computer vision models efficiently. Especially valuable for teams building AI applications in manufacturing, agriculture, or energy that require robust MLOps capabilities and scalable infrastructure.
Common actions
manage visual data
annotate images
train computer vision models
deploy AI applications
monitor model performance
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Capabilities
Key features
MLOps for computer vision
Visual data management
AI-assisted annotation
Model training
Model deployment
Real-time monitoring
Experiment tracking
Target Audience
data scientistdeveloperproduct managerstartup founder
Annual pricing based on images and predictions, with discounts for higher volumes. Check picsellia.com for current pricing.
FAQs
What is a Data Processing Unit (DPU) and how is it priced?
A DPU measures data ingestion and processing. Standard images convert at 60 images = 1 DPU, videos at 1 video = 1 DPU, and multi-spectral images at 5 images = 1 DPU. The base rate is €0.80 per DPU, with discounts up to 60% at higher volumes.
What deployment options does Picsellia offer for my data and compute?
Picsellia provides SaaS (managed cloud), Hybrid (your data storage and compute, Picsellia's control plane), and On-Premise (full deployment to your infrastructure) options. You can connect your existing S3, GCS, or Azure storage, and bring your own GPU compute.
Does Picsellia support custom training code and existing ML stack integrations?
Yes, you can use any framework (PyTorch, TensorFlow) and containerize your training scripts. Picsellia integrates with MLflow, cloud storage providers, container registries, and CI/CD systems, and offers a Python SDK and REST API for custom integrations.
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