
AI agents designed for secure legal document analysis and enterprise workflows.

The platform enables teams to query large sets of files across connected storage systems while maintaining security and compliance. Agents break down complex questions, reference specific clauses or pages, and deliver results in formats such as tables or charts derived directly from the source materials. Advanced OCR capabilities convert scanned PDFs and mixed-content documents into searchable, structured data. This includes extraction from contracts, bills of quantities, engineering drawings, and annotated files, allowing for accurate indexing and analysis even with handwritten notes or official stamps. Users can set up dedicated workspaces for individual matters, run targeted agents for tasks like clause comparison or risk assessment, and export findings with full audit trails back into existing document management systems.
AI agents analyze multiple legal instruments such as contracts, amendments, and NDAs simultaneously to surface conflicts and inconsistencies across documents.
The OCR engine converts scanned PDFs and images into searchable, structured data including text, tables, and extracted values from legal contracts or construction drawings.
Agents produce timelines, clause comparisons, risk summaries, Gantt charts, and tables directly from matter documents for client-ready outputs.
Pricing model: Paid. Plan details are indicative — check the site for current prices.
Our take: Magic Circle is a solid productivity choice. It's valued for strong source citation and audit trail for legal review and handles scanned, mixed-language, and technical documents. The main trade-off is requires initial workspace configuration and repository connections. Best when you need reliable, professional output.
Every response includes citations to the exact page, clause, and sentence from the source documents.
Magic Circle is a solid productivity choice. It's valued for strong source citation and audit trail for legal review and handles scanned, mixed-language, and technical documents. The main trade-off is requires initial workspace configuration and repository connections. Best when you need reliable, professional output.
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