Year 1
1,280hrs
baseline
Year 1 baseline
soXal ingests the advance, gear sheets, post-mortem. No recommendation fires yet — this is the corpus AI TD will read from in Year 2.
Outcome
- $ saved
- —
- carbon avoided
- —
- est. value
- —
5-year case study · monitored event
soXal has been monitoring a recurring corporate gala for five years — same event, same producer, same venue stack. Each year, AI TD reads what worked the year before and recommends the next move. Year over year, those recommendations compound. Here’s exactly what fired and what it saved.
Year 1
1,280hrs
baseline
Year 1 baseline
soXal ingests the advance, gear sheets, post-mortem. No recommendation fires yet — this is the corpus AI TD will read from in Year 2.
Outcome
Year 2
1,410hrs
+10% labor
AI TD recommended
Bundle drape install across both adjacent zones · single-truck delivery · pre-stage scenic vendor one day early
Outcome
Year 3
1,525hrs
+8% labor
AI TD recommended
Drop the outdoor activation (low ROI per the Year 2 settlement) · auto-call the FOH board op who worked the room last year · auto-flag steward at crew 17 per the CBA
Outcome
Year 4
1,690hrs
+11% labor
AI TD recommended
Compress the 3-day install to 2 (carry pre-rig from Year 3) · bundle scenic vendor across tent + lobby · pre-confirm the certified rigger the moment the advance lands
Outcome
Year 5
1,820hrs
+8% labor
AI TD recommended
Re-use the Year 3 template wholesale (90% identical year over year) · BidSmith cost forecast came in 4% under actual settlement
Outcome
5-year totals — what AI TD compounded
$17,600
direct savings captured
2.1 t CO₂
carbon footprint avoided
+42%
labor hours dispatched
$63,600
est. value of AI TD recs
The producer doesn’t need to remember anything. The corpus does the remembering, AI TD does the recommending, and the savings + the carbon avoidance show up in the settlement. That’s the loop.