Lorian Analytics - 2026 Pricing, Features, Reviews & Alternatives

Lorian Analytics is a cloud-based DataOps platform built for business teams across Latin America that need clean, governed, and versioned data before feeding it into BI or AI systems. Operating in Spanish on a Medallion architecture (Bronze, Silver, and Gold layers), it serves as the data infrastructure layer where raw data is ingested, prepared, and made ready for downstream consumption. A free plan is available with no credit card required, and the platform is a member of the Microsoft AI Cloud Partner Program.

The Bronze layer supports manual file uploads, cloud storage connections (OneDrive, SharePoint, Google Drive), on-premises connectivity via an agent for SQL Server, ERP integration with Siesa, read-only connections to Databricks and Snowflake, and IoT sensor ingestion via MQTT. The Silver layer applies automatic data cleaning through the Lorian.AI module and provides column-level analysis. The Gold layer enables joins, filters, and column selection for final data modeling. Enterprise configurations add multi-workspace management, role-based access control, destination outputs, third-party integrations, and a REST API. Across all layers, automated scheduling flows, data quality scoring, data versioning, data lineage tracking, and a data catalog provide end-to-end operational control.

Lorian Analytics addresses compliance and regulatory requirements specific to LATAM environments through tax document validation covering seven countries, including NIT, RUT, RFC, CUIT, CPF, CNPJ, and RUC formats, without modifying original source values. An immutable audit log records 82 distinct actions with user identity, date, and IP address, and cannot be altered from within the application. Every data load, cleaning operation, and model is assigned a numbered version, giving organizations full traceability from ingestion to output. AI-powered dashboards and visualizations surface insights from governed data, positioning the platform for organizations preparing data infrastructure for AI-era workloads.