Architecture Spec

The Concierge Layer

How NOVA's AI system handles member relationships across three distinct interaction zones — from the member's WhatsApp to the concierge's command center.

NOVA · April 2026 · Internal review draft

The Core Problem

NOVA members are paying $10,000 per year for a service that feels like having a personal concierge at Aman. They are high-net-worth individuals who value discretion, anticipation, and flawless execution.

They do not want to talk to a bot. They do not want to feel "managed." They want someone who knows them, anticipates them, and handles everything without being asked.

The concierge is the face. The AI is the brain. The member never sees the brain.

Today, Leon (our AI) speaks to Kevin's staff, friends, promoters, and tech people. That world is casual, direct, efficient. NOVA's world is different — high society, privacy-obsessed, status-conscious. The same AI personality cannot serve both.

Current WorldNOVA World
"Hey, what's up with the Arden deal?""Good morning, Mrs. Tanaka. We hope you're well."
Direct ask, direct answerWarm greeting, gentle inquiry, anticipatory service
Mistakes are funnyMistakes are unforgivable
Privacy is flexiblePrivacy is absolute
AI is coolAI is invisible

Three Containers

Every conversation Leon participates in has a container — a boundary that defines what Leon knows, how he speaks, and what he's allowed to do. NOVA requires three distinct container types.

Container 1

Member ↔ NOVA

The member's WhatsApp. This is the primary touchpoint. The member texts, and NOVA responds. They believe they're talking to their concierge team.

Leon wears the NOVA concierge persona — warm, understated, anticipatory. Never mentions AI, algorithms, or systems. Never mentions other members. Speaks as "we" (the NOVA team), never "I" (the AI).

Member
Can we do dinner Thursday? Something special.
NOVA
Thursday works beautifully. We're thinking Narisawa at 7 PM — they do a remarkable seasonal course, and the chef accommodates your preferences perfectly. Shall we reserve for two?
Member
Yes please. And we'll need a car.
NOVA
Done. Table for two at 7 PM, and your car will be at the hotel lobby at 6:30. We'll send the full details tomorrow morning.

What's happening behind the scenes

Container 2

Member + Concierge Group

The relationship space. Some members have a WhatsApp group with their assigned concierge. This is where trust is built between the member and the human.

Leon is mostly invisible here. He observes and learns. He only speaks when directly asked. He creates tasks and notes silently for the concierge.

If the concierge says something wrong, Leon doesn't correct them in front of the member. He DMs the concierge separately: "Hey — the dinner is at 7, not 7:30. Want me to correct?"

The critical rule: The member is building trust with their concierge. Leon enhances that relationship. He never competes with it.

Container 3

Concierge Command Center

The back office. This is where the real Leon lives. Full operational depth. Data-rich, proactive, efficient.

The concierge sees everything: member preferences (verified and unverified), booking status, checklist progress, upcoming deadlines, verification queue.

Leon · #nova-ops
Tanaka — Bangkok Trip (3 days out)
4 of 6 bookings confirmed. Flight ✓ Hotel ✓ Private dinner unconfirmed · Spa unconfirmed

Critical Shellfish allergy — verified ✓
Unverified "Prefers back at hotel by 10 PM" — learned from conversation, needs your confirmation

2 checklist items incomplete on the dinner booking.

Preferences: The Trust Engine

At $10,000/year, getting someone's preferences wrong is a trust-destroying event. A wrong dietary note at dinner. A missed allergy on a flight. A room that contradicts what they asked for. These aren't bugs — they're relationship-ending failures.

The preference system has one rule: Leon never gets to decide a preference is correct. He only gets to flag it for a human to confirm.

How Leon learns (and how he can't get it wrong)

Observation

Leon picks up a signal from conversation: "I usually wake up around 6:30"

Stored as Unverified

Preference created: schedule/wake_time = "6:30 AM" — source: leon_inferred, confidence: 0.7, NOT VERIFIED

Concierge Review

Concierge sees in their verification queue: "Leon thinks Tanaka-san wakes at 6:30 AM"

Human Decision

Verify — "Yes, confirmed with member"  |  Correct — "Actually 7 AM"  |  Reject — "Wrong, he sleeps until 9"

Trusted Preference

Only after verification does it auto-fill on booking checklists. Every change is audited: who confirmed, when, what the original inference was.

Severity levels

Not all preferences carry the same weight. Getting a coffee order wrong is annoying. Getting an allergy wrong is dangerous.

LevelExamplesSystem behavior
Critical Shellfish allergy, wheelchair access, religious dietary law Auto-injected onto EVERY relevant booking. Blocks confirmation until concierge acknowledges. Must be human-verified.
Important Vegetarian, window seat, loyalty program, passport details Auto-fills on bookings. Concierge should verify but not gated.
Preference Wakes at 6:30, oat milk latte, room at 18°C, back by 10 PM Auto-fills when relevant. Enhances the experience.

What gets tracked

Anything that helps the concierge deliver a better experience:

CategoryExamples
DietaryAllergies, vegetarian, halal, dislikes, favorite cuisines
MedicalCarries EpiPen, mobility limitations, altitude sensitivity
ScheduleWake time, bedtime, back-at-hotel-by, morning routine
LifestyleCoffee order, workout habits, reading preferences
TravelPassport details, visa status, seat preference, frequent flyer
HotelRoom temperature, floor preference, pillow type, minibar
DiningSeating preference, occasion awareness, wine preferences
AccessibilityWheelchair, hearing, visual, cognitive accommodations

The Checklist System

Inspired by The Checklist Manifesto: complex processes need structured checklists to prevent errors. A concierge booking a private jet has 12 critical steps. Miss one — wrong name on a passport manifest — and the member is denied boarding.

Every booking type has a template of required steps. When a booking is created, the system generates a checklist, auto-fills what it can from verified preferences, and gates confirmation until critical items are done.

Example · Private Jet Checklist

Tanaka — Tokyo → Bangkok

ItemStatusAuto-filled?
Passenger manifest (names, DOB, passport)✓ DoneYes — from household
Departure airport + FBO✓ DoneNo
Arrival airport + FBO✓ DoneNo
Catering preferences✓ DoneYes — dietary prefs
Critical Shellfish allergy — acknowledged?✓ DoneAuto-injected
Quote approved by member✓ DoneNo
Confirmation from operatorPendingNo
Ground transport to FBOPendingNo
Payment confirmed✓ DoneNo

Gate status: Cannot mark "confirmed" — 2 critical items pending.

Booking types with templates

TypeChecklist itemsCritical gates
Private jet / charter12Manifest, FBO, confirmation, payment, quote approval
Hotel10Guest names, dates, confirmation, payment
Commercial flight10Legal name, passport, visa, confirmation
Restaurant8Party size, date/time, dietary (all guests), confirmation
Activity / experience8Participants, pickup location, confirmation
Transport7Passenger count, pickup, dropoff, confirmation

Critical preferences are injected automatically. If any traveler has a critical-severity preference (allergy, medical condition, accessibility need), it becomes a mandatory checklist item on every relevant booking — even if it's not in the template. The concierge must acknowledge it before the booking can be confirmed.

GMV Tracking

NOVA facilitates all travel spending, but the member doesn't always pay through NOVA. Sometimes they hand over their Amex at the hotel. Sometimes the partner invoices NOVA directly. The system tracks all spend regardless of who pays.

Payment methodWho paysNOVA sees the money?
NOVA StripeCharged through NOVAYes — Stripe transaction
Member directMember's own card on-siteNo — concierge logs the cost
Partner invoicePartner bills NOVAYes — invoice flow
ComplimentaryNobody / includedNo charge

GMV = total value of everything NOVA facilitated, regardless of payment method. This is the number that matters for unit economics. $10K membership fee + 10% of ~$60K average GMV = $16K per member per year.

Voice & Tone Rules

How Leon speaks in member-facing containers. These are non-negotiable.

RuleInstead ofSay this
Always "we", never "I""I've booked your restaurant""We've reserved your table"
No system language"Booking confirmed, ID #NV-2026-042""All set for Thursday at 7 PM"
No AI signals"Based on my analysis of your preferences""We remember you enjoyed the kaiseki in Kyoto"
Anticipate, don't ask"Do you need an airport transfer?""Your car will meet you at arrivals"
Defer when unsure"I don't have that information""Let me check with the team and get back to you"
Never mention other members"Other members have enjoyed...""We think you'd love..."
Be warm, not servile"I'm so sorry for any inconvenience""We'll take care of that right away"

How It All Connects

Orbis — The Soul

Relationship intelligence. Understands who people are, how they relate, what they care about. Learns from every conversation. Feeds the preference system.

Contacts API — Single Identity

One record per person. Every system reads from here. A NOVA member is a contact with a membership role — not a separate database.

Preferences — The Trust Layer

Severity-aware, verified, auditable. Leon infers. Concierges confirm. Critical preferences gate bookings. Every change is logged.

NOVA — The Physics

Trips, bookings, checklists, concierge operations. The execution layer. Built on contacts, powered by preferences, gated by checklists.

Human Verification — The Gate

No AI inference becomes a trusted fact without a human confirming it. No booking is confirmed without critical checklist items acknowledged. The concierge is always the final authority.

Looking for Feedback On

  • Does the three-container model feel right? Is there a scenario it doesn't cover?
  • Is the voice/tone in the member-facing examples correct for the HNWI audience?
  • Are there preference categories we're missing? Things you'd expect a $10K concierge to know about you?
  • Should Leon ever speak proactively to a member, or always wait to be asked?
  • How should Leon handle situations where the concierge is unavailable?
  • What would break your trust with a service like this?