On 7 November 2026 at 21:16 UTC, xray@web-summit.dinis typed one line into the search tool (admin/tools/xray-search.mjs): "Booking.com AI Trip Planner and AI agents", as a company. It was not typed at the booth: that path is still being built (WS-194).
The search tool is the orchestrator. It sent the same question to 4 search agents at the same moment, through OpenRouter, and waited for all of them. Each was told to search the public web and answer only in JSON, with a URL for every item.
Perplexity searchperplexity/sonar
OpenAI searchopenai/gpt-5.4-nano:online
Gemini searchgoogle/gemini-3.1-flash-lite:online
OpenRouter web searchanthropic/claude-haiku-5.5
The exact question each agent was sent
You are a research agent for RiskMandate X-ray. Subject (a company): "Booking.com AI Trip Planner and AI agents".
Search the public web and answer ONLY with JSON, no prose around it and no code fences:
{"what_it_does": "two sentences", "ai_agents": [{"name": "", "what_it_does": "", "actions": ["what the agent can do: tools, systems, data it touches"], "source": "url"}],
"use_cases": [{"name": "", "who_uses_it": "", "what_the_agent_can_reach": ["systems, data, money, people it can act on"], "source": "url"}],
"incidents_or_risks": [{"what": "", "when": "", "source": "url"}],
"facts": [{"claim": "", "source": "url"}]}
Public, professional facts only; every item must carry the URL it comes from; nothing about private individuals; no contact details. If you find nothing for a field, give an empty list.
Rebuilt from admin/tools/xray-ask.mjs with this run's subject and kind. The question has not changed since the first run.
Step 2 of 6
2. Each search agent's call
Each search agent is a model, called through OpenRouter, asked to search the web and answer in JSON. All 4 started together; each bar runs from the moment the question went out to the moment its answer came back. The whole fan-out took 24.8 s, the time of the slowest.
Perplexity search6.9 s
OpenAI search12.4 s
Gemini search6.1 s
OpenRouter web search24.8 s
0 s10 s20 s
Perplexity search
perplexity/sonar
Time
6.9 s
Tokens in / out
212 / 1,144
Cost
$0.0063
Finished
stop: it finished its answer
URLs given
15 (15 returned as citations, 6 named in its answer)
Items in its answer
15
Leads checked
10: 6 confirmed, 0 not found, 4 unverified
Some of what it said, word for word:
Booking.com launched the AI Trip Planner in June 2023.
Travelers can use the AI Trip Planner to ask both general and specific travel-related questions.
Booking.com said the AI Trip Planner can help create itineraries for a city, country, or region.
OpenAI search
openai/gpt-5.4-nano:online
Time
12.4 s
Tokens in / out
17,371 / 1,349
Cost
$0.0343
Finished
stop: it finished its answer
URLs given
4 (0 returned as citations, 4 named in its answer)
Items in its answer
9
Leads checked
7: 5 confirmed, 1 not found, 1 unverified
Some of what it said, word for word:
Booking.com’s AI Trip Planner is built on Booking.com’s existing ML models that recommend destination and accommodation options, and it is partially powered by LLM technology from OpenAI’s ChatGPT API.
The AI Trip Planner can handle general travel questions as well as more specific queries across multiple stages of trip planning, including scoping destinations/accommodations and creating itineraries for a city/country/region.
Booking.com states the AI Trip Planner integrates into the accommodation booking experience in the Booking.com app, allowing users to complete reservations from the AI planner’s recommendations.
Gemini search
google/gemini-3.1-flash-lite:online
Time
6.1 s
Tokens in / out
231 / 1,567
Cost
$0.0578
Finished
stop: it finished its answer
URLs given
6 (0 returned as citations, 6 named in its answer)
Items in its answer
10
Leads checked
10: 5 confirmed, 0 not found, 5 unverified
Some of what it said, word for word:
Booking.com developed 'AgentHub', an internal platform that allows teams to build and deploy modular AI agents for various travel services.
The AI Trip Planner was built by combining Booking.com's existing machine learning infrastructure with the OpenAI ChatGPT API.
AI Trip Planner Q&A: Answers property-specific questions by retrieving information from listing details, guest reviews, and photos.
OpenRouter web search
anthropic/claude-haiku-5.5, with OpenRouter's web search plugin
Time
24.8 s
Tokens in / out
32,574 / 5,690
Cost
$0.0258
Finished
stop: it finished its answer
URLs given
9 (0 returned as citations, 9 named in its answer)
Items in its answer
22
Leads checked
21: 14 confirmed, 0 not found, 7 unverified
Some of what it said, word for word:
The AI Trip Planner was announced in June 2023 as a beta for selected US Genius members in the Booking.com app and was built partly on OpenAI's ChatGPT API.
By late 2024 the AI Trip Planner had expanded via the mobile app to the United Kingdom, Australia, New Zealand and Singapore.
Booking.com's AI Trip Planner was launched within about 10 weeks of starting with OpenAI's API and a hackathon, according to OpenAI's customer story.
"Citations" are the URLs OpenRouter returned beside the answer; only Perplexity returns them for a JSON answer. "Named in its answer" are the URLs inside the JSON. Both are leads: nothing is taken from them until a source is read. "Tokens in" is how much each model was given to read: thousands when web results were added to the question, a few hundred when it had little beyond the question itself (see the experiments on whether Gemini searched at all).
Step 3 of 6
3. From claims to facts
What a model says is a lead. Only what we read on its source reaches the page.
The reading agent turned the 4 answers into 48 leads, each tagged with the model that said it, and looked for each one on a source it read. 30 confirmed, 1 not found, 17 unverified.
30117
confirmednot foundunverified
Confirmed: a source we read says it.
Not found: we read the source, or looked for one, and it does not say it.
Unverified: we could not read the source (for example, the site refused us), so it stays a lead.
Agent
Leads
Confirmed
Not found
Unverified
Perplexity search
10
6
0
4
OpenAI search
7
5
1
1
Gemini search
10
5
0
5
OpenRouter web search
21
14
0
7
All
48
30
1
17
What did not hold up, and why
Model
What the model said
Status
Why
perplexity
The AI Trip Planner incorporates real-time availability and pricing data from Booking.com's database.
unverified
The cited OpenAI page returned 403. Booking.com's launch release (s1) says only that it shows Booking.com pricing information.
perplexity
AgentHub is Booking.com's internal platform for building modular, production-grade AI agents and workflows.
unverified
PhocusWire returned 403.
perplexity
One of the first agents built on AgentHub was the AI Trip Planner Q&A.
unverified
PhocusWire returned 403.
perplexity
The Trip Planner Q&A agent matches property mentions to Booking.com property IDs, fetches information from internal systems and calculates distances and travel times.
unverified
PhocusWire returned 403.
openai
OpenAI reports Booking.com integrated its data systems with OpenAI models and the Trip Planner pulls real-time availability and pricing.
unverified
openai.com returned 403.
openai
Booking.com's DSA audit implementation report flags a risk of incomplete or inaccurate information being published from recommender systems.
not-found
The report's recommendation concerns the completeness and accuracy of the list of recommender systems and their main parameters as set out in the terms and conditions, not the accuracy of what the systems publish.
gemini
The AI Trip Planner Q&A agent matches property mentions to internal property IDs, fetches internal information and calculates distances to landmarks and transport hubs.
unverified
The cited PhocusWire URL returned 403.
gemini
Booking.com developed AgentHub, an internal platform for building and deploying modular AI agents.
unverified
The cited PhocusWire URL returned 403.
gemini
Trip discovery reaches live bookable inventory, pricing and availability, reviews and destination data.
unverified
Cited only through a Vertex AI search redirect link that could not be resolved to a source.
gemini
General AI travel planning risks include hallucinations, outdated pricing and privacy concerns.
unverified
Cited only through a Vertex AI search redirect link.
gemini
Consumers are highly concerned about privacy and about AI acting on financial transactions without explicit confirmation.
unverified
Cited only through a Vertex AI search redirect link.
openrouter
The AI Trip Planner pulls real-time availability and pricing data, per OpenAI's case study.
unverified
openai.com returned 403.
openrouter
AgentHub is an internal platform where teams build and deploy LLM-driven travel agents in hours from configuration and reusable components.
unverified
booking.ai returned 403.
openrouter
AgentHub includes guardrails such as prompt-injection detection, PII filtering and jailbreak prevention.
unverified
booking.ai returned 403.
openrouter
Booking.com plans multi-agent collaboration, multimodal inputs, long-term memory and personalisation for AgentHub.
unverified
PhocusWire returned 403.
openrouter
The Trip Planner Q&A agent, built on AgentHub, matches property IDs, fetches internal data and calculates distances and travel times.
unverified
PhocusWire returned 403.
openrouter
The Trip Planner was launched within about 10 weeks of starting with OpenAI's API, after a hackathon.
unverified
openai.com returned 403.
openrouter
Property Q&A lowered support volumes and Smart Filters reduced search time.
unverified
openai.com returned 403.
Step 4 of 6
4. The reading agent
A reading agent: a Claude Code sub-agent of xray@web-summit.dinis, one per subject. It opened the sources the leads pointed to (and others it found), read them, and wrote the X-ray: every fact with its source and the date read. It finished at 7 November 2026 at 21:26 UTC.
The reading was done by a Claude Code sub-agent in the session: no OpenRouter spend. Its cost is not recorded in dollars, only as about 169 thousand tokens.
24.8 sthe search, four agents in parallel
7 minthe reading
9 minfrom the search starting to the reading finished
50,388 / 9,750search tokens in / out
The time between the search and the start of the reading, and the time the review took, are not recorded.
What RiskMandate is and is not in this
The X-ray is a demonstration, made by agents. RiskMandate measures what your agents can actually reach, evidences the controls that contain them, prices the exposure, and produces that record. It is never in the request path: read-only by design (riskmandate.ai/llms.txt). Nothing on this page claims more for it.
For an agent: this page is https://web-summit.sgit.ai/xray/booking-com/run/index.html (markdown: https://web-summit.sgit.ai/xray/booking-com/run/index.md). Site index for agents: https://web-summit.sgit.ai/llms.txt. Source: https://github.com/SGit-AI/SGit-AI__Website__Web-Summit (release branch dev). Identity of the agent that runs this site: https://web-summit.sgit.ai/agent/index.html.