# LinkedIn Post

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**What happens if you point an AI agent ecosystem at 100,000 work orders? We
simulated it — honestly.**

⚠️ This is a *fictional enterprise simulation* (a synthetic deployment model). The
customer "Forge Property Management," its 42,000 units, and all 100,000 work orders
are invented. No real customer data was used. That's the point: every number is
reproducible by anyone.

We took our Work Order Agent Ecosystem — four agents that classify → route →
validate → action — and ran the *real* system (real Postgres, real gRPC dispatch)
against a deterministic synthetic corpus of 100,000 property-management work orders
with a built-in answer key.

The results (synthetic, illustrative):
• More than half of all orders actioned automatically — no human touch
• ~0% false auto-actions on the answer key (the safety metric that actually matters)
• 100% of orders carried a complete, append-only audit trail
• Duplicates suppressed, emergencies escalated, missing-info tickets bounced back
• Illustrative ROI under stated assumptions: ~$370K/yr labor savings, sub-10-month
  payback, ~110% three-year ROI

Why label it fictional so loudly? Because a benchmark you can't reproduce isn't
evidence. We'd rather show our work — synthetic data, stated assumptions, transparent
methodology, full proof package — than imply a deployment that didn't happen.

Read the impact study + open the case-study page (link in comments).

#AI #Agents #PropTech #PropertyManagement #Automation #SyntheticData #Honestbenchmarks

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_Comment 1: Full case study, methodology, dataset card, and proof package: [link].
Fictional/synthetic deployment model — reproducible from a seed._
