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Data Packages

Transform Data Chaos into Reusable Assets

Flexible, interoperable data packages that compound value over time

Give teams the power to define their own processes, use their own datatypes, and innovate as quickly as they want. Gain organizational-wide data findability while building reliable, trustable, version-controlled data products.

What's Data Chaos?
Quilt Open Source
ccle-test-3/SRR8788981
@ 2f07364e26
METADATA
study: "CCLE"
cancer_type: "Lung Cancer"
organism: "Homo sapiens"
data_type: "WGS"
Showing 1-5 out of 5
SRR8788981.runinfo_ftp.tsv 1.6 kB
SRX5578768_SRR8788981_1.fastq.gz 66.5 kB
SRX5578768_SRR8788981_2.fastq.gz 66.2 kB
Resilience
90%
faster data lookup

What Are Data Packages?

Data packages are intelligent manifests that combine pointers to data (like objects in Amazon S3) with rich context about that data, including lineage, metadata, and revision history.

If you can't find the data, you can't reproduce the analysis.

Data without context is not reusable. Traditional file storage separates data from its meaning, making collaboration and discovery nearly impossible.

🔗

Intelligent Manifests

Combine pointers to data with rich context and lineage

📋

Self-Contained

Everything needed to understand and reproduce the analysis

🔄

Versioned

Track every change with cryptographic integrity

🔍

Discoverable

Find and access data through metadata and search

What data packages give you

Data packages pair familiar data management with cloud-native storage, so your data stays reliable, easy to find, and ready to reuse.

Data Provenance

Immutable hash-based version history — audit-ready for GxP and 21 CFR Part 11

Open Source

Rich Visualizations

Document previews, dashboards, and in-browser charts anchored to package versions

Platform

Powerful Search

Curator natural-language search across metadata and file contents

Platform

Team Collaboration

Web catalog, role-scoped permissions, and shareable package URIs

Platform
See it in action

Browse packages with full context

Every package combines your files, README, and metadata in one view — backed by S3 in your AWS account, never copied elsewhere.

02 Package catalog

Browse your data like objects in S3, with context

Every package is a self-contained unit: data, a README, rich metadata, and previews. Explore the tree, read the docs, and see exactly what's inside before you pull a byte.

  • File tree, README, and key/value metadata in one view
  • In-browser previews for images, tables, and notebooks
  • Backed by your own S3, so the data never moves
Explore the platform

Built for Your Infrastructure

Data packages work with your existing cloud infrastructure and analysis platforms, giving your data a vendor-neutral foundation.

Amazon Web Services

Native S3 integration with advanced AWS technology partnership

Integration

Amazon Web Services

Native S3 integration with advanced AWS technology partnership

Integration

Amazon Web Services

Native S3 integration with advanced AWS technology partnership

Integration

The Data Package Lifecycle

From creation to collaboration

Data packages follow a simple workflow. Start with the free Python SDK for basic packaging, or use the full platform for team collaboration.

1

Create

Bundle data with metadata (SDK) or use web interface (Platform)

2

Version

Track changes with SHA-256 checksums

3

Share

Collaborate across teams and platforms

4

Discover

Access via SDK commands or rich web search (Platform)

Real-World Applications

See how teams across biotech and life sciences use data packages to accelerate discovery and ensure reproducibility.

🧬

Genomics Research

Package sequencing data with sample metadata for reproducible analysis pipelines

Key Benefit: Reproducible Analysis
Example: FASTQ, VCF, BAM files + sample metadata
🧬

Genomics Research

Package sequencing data with sample metadata for reproducible analysis pipelines

Key Benefit: Reproducible Analysis
Example: FASTQ, VCF, BAM files + sample metadata
🧬

Genomics Research

Package sequencing data with sample metadata for reproducible analysis pipelines

Key Benefit: Reproducible Analysis
Example: FASTQ, VCF, BAM files + sample metadata
🧬

Genomics Research

Package sequencing data with sample metadata for reproducible analysis pipelines

Key Benefit: Reproducible Analysis
Example: FASTQ, VCF, BAM files + sample metadata
Measured impact

Outcomes teams see with Quilt

90%
faster data lookup
Resilience
3×
NGS analysis throughput
Tessera
Weeks → minutes
from instrument to AI-ready package
30+
biotech & pharma teams
incl. Allen Institute, Inari

Trusted by life-sciences organizations

Data lookups that used to take our scientists days now take minutes, with a single, governed source of truth the whole team can trust.
90% faster data lookup Data Platform team, Resilience
The Data Revolution

From Expendable Resource to Reusable Asset

AI and Machine Learning are creating new opportunities to answer much broader questions than lab data was originally intended for. To be competitive in biotech, using data beyond its original scope is no longer just nice to have. It's an imperative.

Start Building Data Assets

Beyond the lab

Extend the rigor of your data beyond instruments, spreadsheets, and scattered hard drives.

Reusable assets

Versioned packages turn one-off datasets into durable, shareable assets your team can trust.

AI-ready by default

Governed, contextual data that your models and agents can actually use.