BlazorData

For developers, analysts, and data-savvy users who want the power of AI-assisted data analysis without the privacy concerns or ongoing costs of cloud-based data platforms, BlazorData provides a compelling self-hosted alternative.

Data import is the first step in the BlazorData workflow. The platform accepts data from Excel files, SQL Server databases, and Microsoft Fabric Warehouse connections, giving it broad compatibility with the data sources most commonly used in business environments.

Once data is imported, users can describe the analysis or transformation they want to perform in plain language, and the AI generates the appropriate Python or C# script to execute itwhether that's identifying top customers, calculating aggregations, detecting anomalies, or reformatting the data for reporting.

The AI-enhanced query layer incorporates the Kusto Query Language (KQL) through a contribution to the kusto-loco project, with OpenAI integration helping users construct KQL queries for data visualizations without needing to know the syntax.

This capability makes sophisticated time-series analysis and log-style data querying accessible to users who have never written KQL, using natural language descriptions to express the analysis intent and letting the AI handle the technical query construction.

Reporting output follows an SSRS-style format, generating structured reports that summarize and present transformed data in a professional layout suitable for sharing with colleagues or stakeholders.

This reporting capability means BlazorData covers the full analytics workflow from import to insight to output, without requiring a separate reporting tool or BI platform. All computation and report generation happens locally, eliminating the need for continuous cloud compute subscriptions.