Lead Quorum uses multi-agent AI to score sales leads with full auditability

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A developer has built Lead Quorum, a multi-agent lead qualification system using Google's Agent Development Kit (ADK) and the Agent-to-Agent (A2A) protocol, submitted to DEV's multi-agent systems competition. The system uses two independent LLM readers running different Gemini models on separate Cloud Run services to extract structured data from raw sales notes, then compares their outputs before assigning any score. A deterministic scoring agent — with no LLM involved — applies a fixed rubric where every point awarded is explained in the same line of code, ensuring the score and its reasoning can never diverge. When the two readers disagree on key signals, the system issues an EXCLUDED verdict and abstains from scoring rather than producing a misleading number. The design aims to eliminate three common failures in lead scoring: opaque results, self-referential model grading, and false confidence on ambiguous input.

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