Multi-AgentInteractive Sandbox Active

Idea Harvestor

Autonomous Enterprise AI Breakthrough Scanner & Multi-Agent LLM Judge

System Simulator Sandbox

Node Ready

Sample Interaction:

Scan latest ArXiv paper on Agentic Orchestration and evaluate feasibility for enterprise rollout.

Execution Output:

Multi-Agent Consensus (87.5% Relevancy Score): • Ways of Working (W_k: 90%): Eliminates 18-hr manual review backlog. • Ways of Development (W_d: 85%): Compatible with existing PostgreSQL + pgvector cluster. • Commercial Feasibility (C: 88%): High ROI with sub-second latency.

The Problem

Organizations are overwhelmed by hundreds of weekly AI papers and announcements, lacking a structured, objective framework to triage and prioritize commercially viable initiatives.

The Architecture Solution

Deploys a 3-tier multi-agent pipeline (Proposer -> Critic -> Judge) scoring ideas on Ways of Working ($W_k$), Ways of Development ($W_d$), and Commercial Feasibility ($C$) with pgvector semantic similarity.

Key Innovations

Multi-Agent Evaluation Pipeline (Gemma 4-e2b Proposer, 4-e4b Critic, 12b-qat Judge)
Dynamic Relevancy Scoring ($W_k \times 0.4 + W_d \times 0.3 + C \times 0.3$)
pgvector Deduplication & Semantic Concept Clustering
Executive Council Agenda & Lifecycle Planning Builder

Verified Telemetry

Ingestion Speed

120 articles/min

Judge Consensus Accuracy

94.8%

Vector Similarity Query

< 12ms

LLM Eval Latency

1.4s

Tech Stack

Next.js 16React 19PostgreSQLpgvectorPrismaTailwind CSSLocal LLMsLM Studio

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