Data Sharing & Collaboration

Share AI Tables Seamlessly

Collaborate on multimodal AI datasets with Pixeltable's replica system. Share tables between local and cloud environments with automatic synchronization, complete versioning, and full data lineage tracking.

100%

Data Integrity

Auto

Sync Updates

Full

Versioning

Secure

Access Control

How It Works

1. Publish

Publish your local table to Pixeltable Cloud with a single command. Control access with public or private visibility.

2. Replicate

Team members replicate the shared table to their local environment. All data, schema, and computed columns are copied.

3. Sync

Push and pull updates seamlessly. Changes are automatically tracked with full versioning and lineage.

Key Features

Complete Replicas

Shared tables include full schema, raw data, computed columns, and metadata.

Auto Synchronization

Push and pull updates with simple commands. Only changed data is transferred.

Full Versioning

Every change is tracked with complete lineage and reproducibility.

Access Control

Publish tables as public or private with fine-grained permissions.

Incremental Updates

Only new or changed data triggers recomputation for efficiency.

Distributed Workflows

Work locally with full performance, sync to cloud when ready.

Code Examples

Three simple commands for complete data sharing and collaboration

publish_example.py

1import pixeltable as pxt
2from pixeltable.functions import openai
3
4# Create and populate your table
5pxt.create_dir('demo')
6t = pxt.create_table('demo.images', {'input_image': pxt.Image})
7
8# Add AI-powered computed columns
9t.add_computed_column(
10    description=openai.vision(
11        prompt="Describe this image in detail.",
12        image=t.input_image,
13        model='gpt-4o-mini'
14    )
15)
16
17# Insert data
18t.insert(input_image='https://example.com/photo.jpg')
19
20# Publish to cloud (make it shareable)
21pxt.publish(
22    source=t,
23    destination_uri='pxt://org_name/demo/shared_images',
24    access='public'
25)

Use Cases

Perfect for teams collaborating on AI and ML projects

ML Team Collaboration

Share training datasets, models, and results across your machine learning team with complete annotations and automated distribution.

Data Science Projects

Collaborate on data analysis with shared cleaned datasets, computed embeddings, and version-tracked reproducibility.

Production Deployment

Develop locally with full performance, then publish to cloud for production with seamless sync between environments.

Dataset Distribution

Share public datasets and benchmark results with the research community for reproducible science.

Start sharing today

Join developers and researchers collaborating on multimodal AI datasets.

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