Private 1:1 threads · Coordinating across everyone

Message the agent privately. It coordinates everyone involved.

From dinner plans to concert tickets and payments, the agent talks to each person individually and coordinates the action across everyone involved. No shared noise, no repeating yourself, and no exposed private messages.

Private coordination model

3 private threads feeding into one coordinated action.

Rohan privately messages the agent to organize tickets for Friday. The agent reaches out to Alex and Maya individually, gathers their confirmations, and purchases all 3 tickets.

ModelUser → Agent ├── Rohan / Alex / Maya → Coordinated Action
Separate 1:1 threads · Never a shared channel
R
Rohan
Private thread ↔ @agent
Organizer
Rohan messages the agent individually
Rohan
R
Can you get tickets for me, Alex, and Maya for the concert Friday?
@agent
@agent On it. I'll message Alex and Maya privately to confirm availability and pricing.
After private check-ins
@agent
Alex and Maya are both in. Tickets are $82 each. Want me to purchase yours?
Rohan
R
Yes, grab all 3!
Isolated threadNot shared with other diners
A
Alex
Private thread ↔ @agent
Participant
Separate private conversation
@agent
@agent Rohan is organizing tickets for Friday. Are you in?
Alex
A
Yep.
@agent
Awesome. Tickets are $82 each. Adding your seat to the order.
Alex
A
Sounds good, thanks!
Isolated threadNot shared with other diners
M
Maya
Private thread ↔ @agent
Participant
Separate private conversation
@agent
@agent Rohan is organizing tickets for Friday. Are you in?
Maya
M
Yes, under $100.
@agent
Found floor seats at $82. Reserving your ticket now!
Maya
M
Perfect!
Isolated threadNot shared with other diners
Conversations converge internally
Coordinated Action
Concert Tickets · Sabrina Carpenter
3 participants3 private threads3/3 confirmed
Individual Participant State
RRohan
✓Confirmed
AAlex
✓Confirmed
MMaya
✓Confirmed
Final Action
3 Tickets Purchased
Confirmed booking #SC-9042 · $246 settled · Individual passes delivered privately
✓
🔒 Responses collected individually. No participant sees another person's private thread.
How it works

Private 1:1 threads. Zero shared noise.

You never need to add the agent into a shared channel. You text the agent in private. The agent reaches out to each person in their own private thread, collects their response, and coordinates the final outcome.

1
Private 1:1 messaging
Every message with @agent is strictly between that person and the assistant. No shared channels or broadcast pings.
2
Internal coordination
The agent coordinates preferences, availability, dietary constraints, and approvals behind the scenes without leaking messages.
3
Coordinated shared action
Once everyone's constraints are met and approvals are in, the agent executes the final action and notifies each person separately.
Restaurant coordination

One request. Individual diner check-ins. Done.

One person asks the agent to organize dinner. The agent messages each diner individually to collect availability and dietary needs, then places the reservation call.

R
Rohan (Organizer)
Private thread ↔ @agent
Host
Private thread ↔ @agent
Rohan
R
Can you organize dinner for me, Elena, and David at Carbone around 8?
@agent
@agent Got it. I'll reach out to Elena and David individually to check their timing and dietary preferences.
@agent
Both confirmed for 8:00 PM! Elena wants Italian, David is vegetarian (Carbone has plenty of options). Ready for me to call Carbone?
Rohan
R
Yes, call them!
Isolated threadNot shared with other diners
D
David (Diner)
Private thread ↔ @agent
Guest
Private thread ↔ @agent
@agent
@agent Rohan is organizing dinner tonight at Carbone around 8. Are you free, and any dietary restrictions?
David
D
I'm in! Strictly vegetarian for me.
@agent
Noted in your private profile. I'll make sure the table accommodates vegetarian options.
Isolated threadNot shared with other diners
E
Elena (Diner)
Private thread ↔ @agent
Guest
Private thread ↔ @agent
@agent
@agent Rohan is organizing dinner tonight at Carbone around 8. Are you free?
Elena
E
Yes! 8 works great for me.
@agent
Great! Adding you to the reservation count.
Isolated threadNot shared with other diners
Coordinated Result3/3 confirmed
Rohan (Host)✓ Confirmed
Elena (Guest)✓ Confirmed (8pm)
David (Guest)✓ Confirmed (Vegetarian)
Next Coordinated Action:
ElevenLabs AI Phone Call Placed
Table for 3 at 8:00 PM confirmed with Carbone host.
AI phone calls

It calls the restaurant directly.

Once all participants have confirmed privately, the assistant holds a natural voice phone conversation with restaurant staff to secure the booking.

Calling Carbone…
00:42
“Hi — I'd like a table for three at 8pm tonight, under Rohan.”
Reservation confirmed
Carbone · Saturday 8:00 PM
3 people · confirmed by the restaurant on the phone call
Individual confirmation cards sent privately to Rohan, Elena, and David.
Private 1:1 request→Individual confirmations gathered→ElevenLabs call placed→Restaurant confirms table→Separate 1:1 confirmations sent
Conversational payments

Customer ↔ Agent and Merchant ↔ Agent. Separate threads.

For a transaction involving a customer and merchant, the agent communicates separately with each. Each person gets their own private thread and only sees information relevant to them.

C
Customer (Rohan)
Private thread ↔ @agent
Customer ↔ Agent
Private payment authorization
Rohan
R
Ready to pay the $82 deposit for the Carbone table.
@agent
@agent Carbone has requested an $82 reservation deposit. Do you want to send $82 from your XRPL Testnet wallet?
Rohan
R
yes
@agent
Sent $82 to Carbone. XRPL Testnet Tx: 4F2A...89B1 validated on ledger.
Isolated threadNot shared with other diners
M
Merchant (Carbone)
Private thread ↔ @agent
Merchant ↔ Agent
Private merchant receipt
@agent
@agent Incoming reservation deposit: $82 from customer Rohan for 8:00 PM party of 3.
@agent
Payment validated on XRPL Testnet ledger (ledger index 914208). Funds settled.
Carbone
C
Deposit of $82 received. Table is confirmed and locked in.
Isolated threadNot shared with other diners
Coordinated Action
Payment · $82 (Reservation Deposit)
2 participants2 private threadsSettled confirmed
Individual Participant State
CCustomer (Rohan)
✓Authorized
MMerchant (Carbone)
✓Ready
XXRPL Testnet
✓Settled
Final Action
Payment Completed · $82
Settled on XRPL Testnet ledger · Both parties updated in private threads
✓
🔒 Responses collected individually. No participant sees another person's private thread.
Isolated memory

Preferences stay private to the person they belong to.

Backboard keeps an isolated memory store per person. When coordinating multiple people, @agent checks each participant's saved preferences without revealing one person's private notes to another.

RRohan's private memory
starts at Columbiaprefers subway
EElena's private memory
no shellfishlikes Italian
DDavid's private memory
strict vegetarianbudget: under $100
Where memory sits in the private coordination loop
Private 1:1 iMessage request
Photon message router
Isolated Backboard memory per person
Gemini synthesizes constraints internally
Individual 1:1 follow-ups sent to each participant
Architecture

Independent private conversations. One coordination engine.

Instead of a shared channel where everyone's messages collide, each participant communicates over an independent private line. The agent orchestrates actions internally.

Private 1:1 Architecture · No Shared Channel
Independent 1:1 Threads
U
User (Rohan)
iMessage ↔ @agent
1:1
P
Participant (Alex)
iMessage ↔ @agent
1:1
P
Participant (Maya)
iMessage ↔ @agent
1:1
Agent Orchestrator
Privacy & Coordination Boundary

Maintains isolated context per participant. Merges responses internally without broadcasting messages to other participants.

BackboardIsolated memory
GeminiCoordination logic
Coordinated Action Layer
Tickets / Bookings
Coordinated orders & reservations
ElevenLabs Voice
Restaurant phone calls
XRPL Testnet
Individual wallet settlements
Maps & Tiger Data
Grounded location synthesis
No shared chat channel exists.Every participant only receives their personalized result in their private thread.
Getting places

Transportation across separate locations, handled.

When coordinating meetups, the agent privately checks where each person is starting from and calculates optimal routes using Google Maps grounding.

↗
Columbia & Midtown → Times Square
Multiple starting locations resolved via Maps grounding · directions sent privately to each person
Directions sent
Stay aware

“Is this walk okay at midnight?”

@agent checks public NYPD complaint data stored in Tiger Data around the block you're on, at the hour you're asking about, and tells you how it compares to that area's usual pattern.

Private 1:1 · Walking home
Private 1:1
You
Y
@agent is it okay to walk through Washington Square at midnight?
@agent
Historically quieter than its peak: fewer reports around midnight than around 4pm near the park. Stick to the lit paths on the west side.
@agent
Historical NYPD reports, not a live safety score.
Time-aware
Counts are compared by hour of day from a Tiger Data hypertable, so 2pm and 2am get different answers.
Block-level
It looks at the streets around a specific point, never labels a whole neighborhood.
Honest by design
No “safe/unsafe” score and no demographic data. It's context from public reports, clearly labeled.
Talk or text

Send a private voice memo. Get one back.

Hold the mic button in iMessage and just ask. ElevenLabs transcribes it, @agent answers in text (with links), then replies out loud as a voice memo.

Private 1:1 · @agent
Private 1:1
▶0:06
@agent
@
1. Caffe Reggio, 5 min walk: espresso and cannoli. 2. The Stand, 10 min: comedy tonight.
▶0:14
Live settlement

Real ledger, test money.

Customer wallets, balances, and validated transactions read live from XRPL Testnet, plus payments the guardrails refused before anything was signed.

XRPL Testnet · no real money
  1. 1Request
    Someone asks @agent to pay
  2. 2Confirmation
    The same person says yes in the same chat
  3. 3Policy check
    Deterministic rules, no model
  4. 4Sign
    Only after ALLOW
  5. 5XRPL
    Submitted to XRPL Testnet
  6. 6Validated
    tesSUCCESS on a validated ledger
Connecting to the live XRPL Testnet feed…
Built with

One brain, many hands.

Photon
iMessage infrastructure
  • Handles distinct private iMessage conversations
  • Routes individual messages to and from @agent
  • Sends replies directly to the right person's thread
Gemini
Intelligence and coordination
  • Interprets natural-language requests
  • Coordinates multiple participant constraints internally
  • Maintains conversational context without message cross-talk
Backboard
Isolated user memory
  • Strictly separate memory per person
  • Never reveals private preferences to other diners
  • Supplies memory to Gemini when relevant
DeepSpace
Accounts, plans, and delivery
  • Sign-in: email code, then one text to @agent
  • Stores accounts, plans, and each person's own @agent number
  • Queues plan and payment notices for the iMessage agent to deliver
ElevenLabs
Voice and phone interaction
  • Gives the agent a natural speaking voice
  • Conducts the reservation call with restaurant staff
  • Transcribes voice memos and replies with one
Tiger Data
Time-series city data
  • NYPD complaint history in a Postgres hypertable
  • Hour-of-day comparisons around a location
  • City event feeds for “what's on near us”
Ripple
Payments and transactions
  • Executes test transactions wallet to wallet
  • Coordinates customer authorizations and merchant confirmations
  • Returns individual status to each party's private thread
  • Requires explicit confirmation before execution
Demo story

From one private text to a coordinated evening.

  1. 1Rohan privately messages the agent: “Can you organize dinner for me, Elena, and David tonight?”
  2. 2The agent opens separate 1:1 threads with Elena and David to gather availability and dietary preferences.
  3. 3Each person responds in private — no noisy threads, no exposed personal notes.
  4. 4Gemini synthesizes everyone's constraints and Backboard memory to find the best spot.
  5. 5The agent sends options privately to Rohan; Rohan confirms Carbone at 8pm.
  6. 6The agent reaches out to each diner privately to confirm attendance.
  7. 7The ElevenLabs integration calls Carbone to reserve the table.
  8. 8If a deposit is required, the agent privately prompts the customer for XRPL authorization.
  9. 9XRPL Testnet validates and settles the payment wallet-to-wallet.
  10. 10The restaurant confirms the reservation on the call.
  11. 11Each participant receives their personalized confirmation in their own private thread.

Message the agent privately.

From dinner plans to concert tickets and payments, the agent talks to each person individually and coordinates the action across everyone involved.

Get your beta spot

plansaroundus · conversations shown are demo examples, not real bookings