From Messy Multi-Tab Planning to One Guided AI Flow | 6 Specialist Agents | Human-Controlled Bookings
In March 2025, Skift reported that Google had indefinitely shelved its AI trip planner.
The biggest technology company in the world looked at the problem of AI-powered travel planning and said: "We can't solve this."
That's not a dead end. That's a product opportunity.
Here's what the current travel planning experience looks like for most people:
Tab 1: Google Flights (price check)
Tab 2: MakeMyTrip (booking)
Tab 3: TripAdvisor (reviews)
Tab 4: Google Maps (distances)
Tab 5: Currency converter
Tab 6: Weather forecast
Tab 7: Visa requirements
Tab 8: Hotel comparison
...12 tabs later, decision fatigue sets in
Real users. Real frustration. Real reviews:
"The itinerary designed by MMT was extremely poorly planned. Hotel checkout was at 11 AM but our return flight was at 11:30 PM — we were forced to sit at the airport for the entire day." — ConsumerAffairs, Feb 2026
"They have some trick coding. Whenever you click back to adjust something, the original discount is gone." — ConsumerAffairs, Nov 2024
"Many smaller or independent hotels I see on Google end up not being connected to the pricing databases." — Rick Steves Travel Forum, 2024
TripPilot's thesis: The problem isn't information. The problem is that no platform connects research, budget, booking, and context into a single intelligent flow — with AI that actually understands the relationships between all the moving parts.
"Help me confidently plan and book a trip that fits my time, budget and preferences — without stress."
That's it. Everything in TripPilot's design flows from this one sentence.
USER INPUTS
Dates · Budget · Preferences · Constraints · Companions
↓
ORCHESTRATOR
Controls which agent runs, in what order
Manages guardrails and human control gates
↓
┌───────────────────────────────────────┐
│ │
│ 🔍 RESEARCH AGENT │
│ Fetches flights, hotels, activities │
│ Clean untracked sessions → real │
│ prices (no dynamic pricing bias) │
│ Aggregates OTAs + direct APIs │
│ │
│ 💰 BUDGET AGENT │
│ Locks TRUE total cost upfront │
│ Fees + taxes + transfers + baggage │
│ No hidden charges at checkout │
│ │
│ 📅 BOOKING AGENT ← HUMAN GATE 🔴 │
│ User reviews & approves before │
│ any booking is confirmed │
│ Live confirmation verification │
│ │
│ 🗺️ ITINERARY AGENT │
│ Cross-checks checkout vs flight │
│ times, transfer durations, crowds │
│ Builds conflict-free schedule │
│ │
│ 📍 CONTEXT AGENT │
│ Hyperlocal recommendations │
│ Real addresses, not vague areas │
│ Weather · Safety · Local events │
│ │
│ 🔔 MONITOR AGENT │
│ Pre-trip alerts (24hr before) │
│ Price drops · Cancellation risks │
│ Rebooking suggestions │
│ │
└───────────────────────────────────────┘
↓
OUTPUTS TO USER
Itinerary · Booking links · Budget dashboard · Alerts
The Booking Agent never books without explicit user approval. This is hardcoded — not configurable. One accidental booking on a non-refundable hotel is a trust-destroying experience. The AI recommends. The human confirms.
Searching 20 flight combinations, comparing 15 hotels, calculating true total costs including transfer fees — all of this happens automatically. This is where AI earns its place.
Every recommendation comes with a "Why this?" rationale. "I chose this hotel because it's 8 minutes from your first activity, within your budget, and has free cancellation until 48 hours before arrival." The AI shows its work.
What other platforms show: ₹40
What TripPilot shows: ₹40 base
+ ₹180 convenience fee
+ ₹240 GST
+ ₹140 airport transfer
= ₹600 TRUE TOTAL
This product was grounded in real user pain, not assumptions. Every pain point sourced from real consumer reviews.
| # | App | Pain Point | TripPilot Solution |
|---|---|---|---|
| M1 | MakeMyTrip | Hotel checkout 11am, flight 11:30pm — 12 hours stranded | Itinerary Agent cross-checks all time conflicts |
| M2 | MakeMyTrip | Discounts disappear when you click back | Budget Agent locks price at point of search |
| M3 | MakeMyTrip | Hotel had no record of confirmed booking | Booking Agent verifies directly with hotel API |
| M4 | MakeMyTrip | ₹40 shown, ₹600 charged at checkout | True total cost shown upfront — always |
| T1 | TripAdvisor | Last-minute hotel cancellation, no resolution | Monitor Agent tracks booking status pre-trip |
| T2 | TripAdvisor | Restaurant recommendation had wrong address | Context Agent delivers precise hyperlocal data |
| T3 | TripAdvisor | Wrong tour booked — non-refundable, no help | Human control gate before every booking |
| G1 | Google Flights | Prices inflate based on browsing history | Research Agent fetches in clean untracked sessions |
| G2 | Google Flights | Independent hotels not in database | Research Agent aggregates across OTAs + direct APIs |
| G3 | AI trip planner shelved indefinitely | TripPilot fills the market gap Google left open |
| Action | What We Do |
|---|---|
| Eliminate | Tab switching · Repeated data entry · Hidden fee surprises · Booking confirmation anxiety |
| Reduce | Time-to-plan · Decision fatigue · Price comparison effort · Post-booking uncertainty |
| Raise | Price transparency · Booking confidence · Itinerary coherence · "Why this?" explainability |
| Create | Single guided flow: plan → optimize → book · True total cost · Pre-trip monitoring · Budget reverse-search |
| Method | Idea Applied |
|---|---|
| Substitute | Replace manual search with Research Agent summaries |
| Combine | Merge booking + itinerary + budget into single "trip cart" |
| Adapt | Shopping cart holds — bundle flight + stay + activities together |
| Modify | Show true total cost (fees + transfers + baggage) upfront |
| Put to Use | Use itinerary during travel: live alerts, rebooking, local tips |
| Eliminate | Remove repeated data entry with persistent traveler profiles |
| Reverse | Start from budget → suggest destinations that fit the number |
| File | Description |
|---|---|
TripPilot_MultiAgent_Travel_Planning.pptx |
Full product deck — problem, architecture, ERRC, SCAMPER, KPIs |
TripPilot_Pain_Points_Ashok_Ankalla.docx |
10 validated user pain points with real consumer sources |
| KPI | Definition | Target |
|---|---|---|
| Time-to-Plan | Minutes from first input to confirmed itinerary | < 15 min (vs 2-4 hours today) |
| Price Accuracy | % match between shown price and final checkout price | > 99% |
| Booking Trust Score | User confidence rating pre-checkout (1-5) | > 4.2 / 5 |
| Conflict-Free Rate | % itineraries with zero time/transfer conflicts | > 98% |
| Agent Alignment Rate | % AI recommendations user accepts without change | > 75% |
"The market gap isn't information. It's orchestration."
- Users don't need more travel data — they need something that connects the data intelligently
- The booking step is where trust collapses — human control gates are non-negotiable
- "True total cost" is a trust feature, not a pricing feature — it's about honesty, not math
- Google shelving its planner validated the thesis: this problem is hard enough to be worth solving
Built as part of BITSoM Executive Program — Product Management with Generative & Agentic AI · 2026 Author: Ashok Ankalla — Enterprise Data & AI Transformation Leader