# X / Twitter Thread

**1/**
We simulated running an AI agent ecosystem against 100,000 work orders.

⚠️ Fictional enterprise simulation — synthetic deployment model. The customer and all
data are invented. No real customer data. Every number is reproducible. 🧵

**2/**
The setup: a fictional 42,000-unit property manager ("Forge Property Management")
with 100k work orders/year, currently reviewed 100% by humans at ~8 min each.

**3/**
We ran the *real* ecosystem — 4 agents: classify → route → validate → action — over
real Postgres + real gRPC dispatch. The only synthetic part is the inbound volume
(100k seeded orders with a ground-truth answer key).

**4/**
Result: more than HALF of all orders were actioned automatically — classified,
routed, validated, dispatched, audited — with no human touch. (Synthetic, illustrative.)

**5/**
The number that matters most: ~0% false auto-actions on the answer key. The validator
is conservative — anything low-confidence, over-cost, duplicate, or missing info goes
to a human. Safety first.

**6/**
100% of orders got a complete, append-only audit trail. Duplicates suppressed,
emergencies escalated, malformed dispatches rejected over the wire, retries
idempotent. Boring on purpose.

**7/**
Illustrative ROI (stated assumptions, full arithmetic shown): ~$370K/yr labor
savings, sub-10-month payback, ~110% three-year ROI. It's a model, not a realized
result — and we say so.

**8/**
Why scream "FICTIONAL"? Because an unreproducible benchmark is marketing, not
evidence. Synthetic data + stated assumptions + seed-deterministic methodology +
full proof package = you can check our work.

**9/**
Read the impact study, dataset card, and proof package here: [link]
Synthetic deployment model. Reproducible from a single seed. 🔁
