CLIENT: AFAS LIVE

Quantifying
the unknown.

The Challenge

Venues rely on gut feel and promoter assurances to assess crowd risk, reputational exposure, and operational complexity. When a high-profile act goes wrong, the venue absorbs the fallout.

The Protocol

Dual-AI agent (OpenAI + Grok) generates structured risk reports before shows are confirmed. Dual-model verification catches blind spots a single model would miss.

STACKNext.js / OpenAI / Grok (XAI)
ORCHESTRATIONn8n / Supabase
OUTPUTRisk PDF / Dashboard
internal.afaslive.protocol.events/risk/analysis
Risk Level
HIGH
Now Analysing
Deftones
Feb 10, 2025 · Concert
Red Flags
3 FLAGS

Risk Score History (Dual-Model Average)

HIGH RISK THRESHOLD: 70

Agent Activity Log

14:22:18
Risk score elevated — 3 red flags identified
14:22:14
Grok analysis complete. Confidence: 84%
14:22:09
OpenAI analysis complete. Confidence: 91%
14:21:55
Discrepancy check... models aligned.
14:21:42
Processing: Deftones — Feb 10, 2025

The Dual-Model Approach

A single AI has blind spots. When one model flags a crowd risk the other misses, the system catches it. By running OpenAI and Grok in parallel and cross-referencing their outputs, the agent produces assessments that neither model could deliver alone. This is about trust in the output, not just automation.

Instead of a spreadsheet of scores, venue teams get a structured intelligence report with actionable watch-fors their security teams can brief on before doors open. The agent does the research a venue team would spend days on, in minutes.

Webhook Request → Dual-Model Analysis → Risk Intelligence Report

< 20 min
From request to full risk intelligence report
94%
Average dual-model agreement across analyses
0
Unmitigated incidents at flagged shows
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