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Aggregion DataLabs & CleanRoom

aggregion.com

WebAPISelf-hosted
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Spec score 7.4 #7 of 21 in Data Clean Room Software

What it is

Aggregion DataLabs & CleanRoom is an environment for building and running models on data shared by multiple partners. Its workflow spans cataloging, discovering partner datasets, developing models in protected DataLabs, performing CleanRoom calculations, and activating results. Partners connect through a virtual data warehouse, with structured and semi-structured data supported. DataLabs virtual machines depersonalize data and apply distortion models during development. Listed languages include Python, R, PySparc, Scala, and Java. The architecture includes adapters for RDBMS, Hive, and Kafka, plus an advanced integration API. Intel SGX hardware-level encryption is described for enclave memory during shared computations. A decentralized protocol governs metadata, permissions, rights, approvals, and related collaboration actions. Scripts may be reviewed, approved, scheduled, or invoked through API, with execution logs kept on an immutable ledger. Deployment can be cloud or on-premise, and customers choose hosting for the DataLab and enclave. Pricing is available on request.

Spec sheet

Purpose
Provides an end-to-end environment for building and running models on joint data.Read 4 Oct 2026 · aggregion.com
Intended users
The product page describes the solution as trusted by large banks, telecom companies, and retailers.Read 4 Oct 2026 · aggregion.com
Deployment
The maker offers cloud or on-premise deployment and says customers can choose where to host the DataLab and enclave.Read 4 Oct 2026 · aggregion.com
Integrations
The technical architecture lists database adapters for RDBMS, Hive, and Kafka, plus an advanced API for integrations.Read 4 Oct 2026 · aggregion.com
Security
The maker describes Intel SGX hardware-level encryption for enclave memory during shared-data computations.Read 4 Oct 2026 · aggregion.com
Auditability
Scripts can be reviewed and approved, scheduled or invoked by API, and execution can be monitored through logs stored on an immutable ledger.Read 4 Oct 2026 · aggregion.com
Data sources
Partners connect data through a virtual data warehouse, and the platform supports structured and semi-structured data.Read 4 Oct 2026 · aggregion.com
Enterprise operations
Enterprise readiness includes Kubernetes application management, a central administration console, and authentication protocols listed as OAuth and AD.Read 4 Oct 2026 · aggregion.com
Governance
A decentralized protocol manages metadata, rights, permissions, script approvals, and other collaboration actions.Read 4 Oct 2026 · aggregion.com
Languages
The product lists Python, R, PySparc, Scala, and Java among supported programming languages.Read 4 Oct 2026 · aggregion.com
Modeling
DataLabs VMs automatically depersonalize data and apply distortion models for model development.Read 4 Oct 2026 · aggregion.com
Workflow
The workflow covers data cataloging, partner dataset discovery, model development in protected DataLabs, CleanRoom calculations, and result activation.Read 4 Oct 2026 · aggregion.com

Plans and prices

DataLabs & CleanRoom Priced on request Pricing not listed; request a demo Read 4 Oct 2026 · aggregion.com

Every Aggregion DataLabs & CleanRoom plan and price →

Strong points and limits

Strong points

  • Supports structured and semi-structured partner data
  • Offers Python, R, Scala, Java, and PySparc
  • Immutable-ledger execution logs
  • Cloud or on-premise deployment
  • Privacy-safe matching and audit logs

Limits

  • Pricing is available only on request
  • Requires partner data collaboration workflows
  • Hosting architecture includes specialized enclave components
  • No specific standalone desktop platform listed

Who it suits

This suits organizations coordinating privacy-safe analytics across partners, including the banks, telecom companies, and retailers named by the maker. It also fits teams needing cloud or on-premise deployment and governed collaboration.

Verdict

Aggregion combines partner data discovery, protected modeling, governed scripts, and CleanRoom computation. Its deployment choices and audit controls are clearly described, while buyers must request pricing and assess the collaboration architecture.

Where Specifiction places it

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