Follow a Gemini Buyer Agent Through All 7 Stages of a Petra Tour Booking

A human told their Gemini agent: 'Book me a Petra tour for two in April, under $120 each.' From this point, the human is out of the loop. The Gemini buyer agent connects to your Salesforce org through Pardisio and queries your product catalog — Products, Price Books, Departures — the same objects your sales team uses.

Runs automatically. No Agentforce. No Commerce Cloud. No human in the loop.

Offer — The Seller's Agent Constructs a Response

Pardisio → Gemini: "3-Day Petra Explorer Tour, DEP-0414, April 14–17, $135/person, 6 seats available, guided Treasury hike + hotel included, negotiation: allowed"

This is the critical step most people miss: the seller's AI creates the offer, not the buyer. Pardisio evaluates the buyer agent's trust score and eligibility, checks real-time availability on matching departures, calculates a personalized price using your Salesforce pricing rules, and sends a structured offer back to the Gemini agent.

Agentforce can power personalized offers for high-value accounts. Standard catalog pricing runs automatically.

Negotiation — Two Agents Negotiate, No Humans Involved

Gemini → Pardisio: "counter-offer: $100/person"
Pardisio → Gemini: "counter: $115/person (15% discount)"
Gemini → Pardisio: "accepted: $115/person"

This is agent-to-agent negotiation — no human sees these messages. The Gemini agent tries below its budget constraint to get the best deal. Your seller agent responds using Agentforce: it reasons through your pricing rules (floor price, max discount, trust-level adjustments) and counter-offers. Two rounds, sub-second, fully governed.

This is where Agentforce shines — intelligent, multi-round agent-to-agent negotiation using your rules as context.

Agreement — Price Locked, Both Agents Confirm

Pardisio → Gemini: "agreement confirmed: $115/person × 2 = $230 total. Price locked. Proceed to reservation."

The price is now locked in Salesforce — neither agent can change it. If your trust policies require human approval for deals above a certain discount level, the seller agent pauses and escalates to your existing Salesforce approval workflow. For standard deals within policy — agreement is instant.

Runs automatically for standard deals. Escalates to your approval workflow for exceptions.

Commitment — Seats Reserved, Hold Timer Starts

Pardisio → Gemini: "reservation RES-0189 confirmed. 2 seats held on DEP-0414. Hold expires in 30 minutes."

Pardisio creates a reservation at the agreed price and locks the inventory — those 2 seats can't be sold to another buyer agent during the hold period. This is critical when multiple AI agents are shopping simultaneously. Inventory locking prevents double-selling.

Runs automatically. Inventory locking prevents overselling — critical when multiple AI agents shop simultaneously.

Execution — Payment Processed, Booking Confirmed

Gemini → Pardisio: "payment token: tok_gemini_28a7f..."
Pardisio → Gemini: "payment $230 confirmed. Order ORD-2847. E-ticket issued."

The Gemini agent sends payment credentials through its protocol. Pardisio creates the Order, records the Payment, generates an Invoice, and syncs the booking to an Opportunity in your CRM pipeline. The entire transaction happened without a single human interaction.

Runs automatically. Standard Salesforce objects: Order, Payment, Invoice, Opportunity.

Settlement — Cancellations, Refunds, Post-Sale

Gemini → Pardisio: "cancel reservation RES-0189"
Pardisio → Gemini: "cancellation policy: >24h = full refund. Departure Apr 14, today Apr 1. Full refund $230. Refund REF-0071 created."

Two weeks later, the human changes plans and tells their Gemini agent to cancel. Pardisio evaluates your cancellation policies automatically — penalty tiers based on time before departure, booking type, and buyer status. The refund is calculated, recorded, and confirmed — all agent-to-agent.

Runs automatically. Policy-driven. The full lifecycle — not just the purchase.

Example Output

Sample agent response

What the Gemini buyer agent receives:

{ status: "completed", reservation: "RES-0189", tour: "3-Day Petra Explorer", departure: "2026-04-14", pax: 2, agreed_price_per_person: 115, total: 230, includes: ["guided Treasury hike", "hotel"], e_ticket: "ETK-2847", cancellation_policy: ">24h full refund, <24h 50% penalty" }

What your Salesforce org recorded (7-stage audit trail):

① Intent: Gemini agent via A2A protocol, query: 'Petra, 2 pax, mid-April, ≤$120'

② Offer: List $135/person → Trust score 78 (threshold 60 ✓) → Negotiation: allowed ✓

③ Negotiation: Buyer $100 → Agentforce counter $115 (15%, within 20% ceiling) → Buyer accepted [2 rounds, 0.4s]

④ Agreement: Locked $115 × 2 = $230. Discount 15% < 25% threshold → No escalation

⑤ Commitment: RES-0189 → Inventory_Lock 2 seats DEP-0414 → Hold expires 14:30

⑥ Execution: Payment $230 → ORD-2847 → INV-1204 → Opportunity synced

⑦ Settlement: Policy loaded (>24h = 100% refund, <24h = 50% penalty)

Same Petra tour. The Gemini agent received structured data it can act on. Your Salesforce org recorded every lifecycle stage, every decision, every policy evaluation — including that Agentforce was used only in Stage ③ and everything else ran automatically. Two AI agents transacted. No human was involved. Full governance trail.

Why This Walkthrough Matters

What you're seeing: a Salesforce org responding to an AI buyer agent

This walkthrough shows the 7-stage contract lifecycle of an agent-to-agent transaction: a Gemini buyer agent transacting with a Pardisio-powered Salesforce org. Behind the scenes is a standard Salesforce org running on Sales Cloud — no Commerce Cloud. This is the same architecture Pardisio deploys for customers.

Agentforce for negotiation and complex pricing — Apex for everything else

Routine transactions run automatically — zero AI cost

Every action governed by trust policies you define in Salesforce

Runs on Sales Cloud — no Commerce Cloud required

Interactive demo coming April 2026. Book a guided walkthrough with our team to see these 7 stages applied to your Salesforce data.

WHAT'S YOUR NEXT STEP?

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You've seen the 7-stage lifecycle. Here's how to go further.

Tier 1

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Tier 2

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Tier 3

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