RAGSUITE0.2.1

Ask natural-language questions about PDF, DOCX, TXT, and HTML files, and RAGSUITE returns answers grounded in specific documents with citations. It prepares those files through OCR, text extraction, chunking, and indexing, then supports conversations spanning multiple documents or focused on a single file. Document analysis can summarize long material, extract key entities, answer content questions, and interpret complex mathematical formulas.

RAGSUITE also turns requests such as “Show the top 5 customers by revenue this year” into SQL while accounting for the schema of SQLite, PostgreSQL, and MySQL databases. Prompt-based analysis can expose relationships, anomalies, trends, patterns, recommendations, and filtered results in structured or spreadsheet data. Database-to-text automation converts records into readable insights, summaries, and reports without manual query writing.

Its retrieval-augmented generation uses an organization’s private knowledge base, while agentic AI capabilities support sharing those resources for team collaboration. Felamity Technologies LLP presents RAGSUITE as a scalable private-AI platform for enterprises, with local processing suited to air-gapped, government, research, and other controlled environments. Small-scale industries can also use Felamity’s private GPU workstation offering, and professional support is available around the clock.

RAGSUITE runs offline on Linux with snapd and amd64 architecture, keeping data on the local system without cloud APIs from OpenAI, AWS, or Google. The current 0.2.1 release is commercial software with a no-code workflow for education, enterprise, government, and research use.