Four supplier records. One mapping network.
Sophisticated AI processing resolves every supplier record into a single identity in the ApiXV mapping network — grounded against Google CID business identifiers and fully geocoded.
How it works
Matching, grounding, geocoding.
Deduplication is not string comparison. It is a pipeline, and the last two stages are what make the result trustworthy.
AI-driven resolution
Sophisticated AI processing compares supplier records across name, address, geography and content signals to decide which describe the same property — work that defeats string matching.
One mapping network
Every matched record resolves to a single identity in the ApiXV mapping network, exposed as one hotel_uid regardless of how many suppliers sent it.
98.8% Google CID match
The mapping network is grounded against Google CID legal-entity business identifiers, with a 98.8% match rate — an external anchor rather than an internal score.
Full geocoding
Country, area, state and city, plus geographic coordinates and Google Plus Codes on every property in the network.
Grounding
98.8% matched to Google CID.
The mapping network is grounded against Google CID legal-entity business identifiers. That means a property in the network is anchored to a real, externally verifiable business — not just to our own view of it.
Grounding against an external identifier is what separates a mapping network from a mapping table. A table records what you decided; a grounded network can be checked against something outside itself.
of properties in the mapping network are matched to a Google CID legal-entity business identifier.
Geocoding
Located precisely, not approximately.
Every property in the mapping network carries a full geographic hierarchy alongside coordinates and a Google Plus Code.
Geography is also a matching signal. Coordinates and Plus Codes let the AI separate genuinely distinct properties that share a name from the same property described four different ways.
Why it matters
Aggregation creates duplicates.
Connecting suppliers is the easy half. Deciding which records describe the same property is where the engineering is.
Duplicate results
The same hotel appears four times at four prices because four suppliers sent it. Conversion drops and users lose trust.
Mapping tables that never finish
Properties open, close, merge and rebrand continuously. Maintaining your own mapping is a permanent staffing commitment.
No external ground truth
Matching against your own catalogue only proves you are self-consistent. It says nothing about whether the property is real.
HTL-88213123456745821MP-0042AXH-qCzrQmMQvRPa- Grounded to Google CID · 98.8% match
- Fully geocoded, including Plus Code
- Supplier resolved from the UID
External codes
Bring the identifiers you already have.
The mapping network resolves GIATA and Expedia property codes in-API. If you already run a hotel business, you do not have to discard the catalogue you built.
Code resolution is available since release 0.10.x. Batching several external codes into one lookup is on the roadmap; content requests already accept multiple UIDs.
Identifiers
One UID scheme.
hotel_uidAXH-…One identity in the mapping network, across every supplier
option_uidAXO-…One availability option for a hotel and room type
quote_uidAXQ-…A confirmed quote, priced and ready to book
booking_uidAXB-…A created booking
cancellation_uidAXC-…A booking cancellation
UIDs are temporary. They are not intended for long-term storage or external caching. Resolve them against the mapping network as part of your request flow rather than persisting them.
Stop maintaining a mapping table.
Get a sandbox key and resolve your first external code this week.