VQV Signal
A new multi-agent platform built on CrewAI uses five specialized AI agents in sequence to handle natural language queries, analyze data, generate visualizations, and provide actionable business insights. The system incorporates a defense-in-depth security model to ensure multi-tenant data isolation.
A new multi-agent platform built on CrewAI uses five specialized AI agents in sequence to handle natural language queries, analyze data, generate visualizations, and provide actionable business insights. The system incorporates a defense-in-depth security model to ensure multi-tenant data isolation.
AI-assisted summary based on the listed source.
This paper proposes a multi-agent framework built on CrewAI [1] for conversational business intelligence. Five specialized AI agents operate in a sequential pipeline to process natural language queries, retrieve and analyze data, generate visualizations via the Model Context Protocol (MCP) [2], and deliver...
This approach streamlines enterprise analytics by automating complex data processing and insight generation through conversational interfaces. Its security architecture supports safe deployment in multi-tenant environments, addressing key enterprise concerns.
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VQV surfaced this signal because it is recent, relevant to AI Agents, connected to arXiv.
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