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Case study
AI search that turned browsers into bookers
- £50m
- a year in additional booking revenue.
Agentic Growth
The demand is already there. Your systems lose it before it converts. Agents turn assets you already own into revenue: your inventory, your demand and your data.
What changes
Your customer has changed how they search, how fast they expect an answer and who does the buying. Your systems have not.
Semantic search across your own live inventory, so a customer describes the thing rather than filtering their way towards it.
The priced reply is drafted and waiting for your team in the morning. That wins back the revenue you currently lose to whoever replies first.
Personas built from synthetic data, and personalisation running on your first party data rather than a rented tool’s view of your customers.
What you get
A customer says what they want in their own words, and the system works out what that means against what you have available right now. It sits in front of your existing journey and hands over to your basket or booking exactly where your current one does.
The enquiry that arrives at nine at night is read as the customer wrote it, priced against live availability and drafted into a reply. It waits for a person to approve, so your desk starts the morning sending rather than reading.
Personas and segments modelled from synthetic data in seconds rather than weeks on a panel, and personalisation that runs on the first party data you already hold. Every campaign result feeds the next model, inside your business rather than inside a vendor’s product.
A growing share of the traffic arriving at your catalogue is an agent acting for someone else, and a site built for browsing is invisible to it. Your inventory gets exposed so machines can read it as well as people can.
It runs in your own cloud accounts under your own security controls. You keep the system, the codebase and the IP, and the data it learns from never leaves your estate.
:quality(75))
Case study
Where it runs
Your cloud, your data. Nothing leaves your estate.
Human approval gates, an audit trail on every run.
Cyber Essentials Plus certified.
You keep the system, the codebase and the IP.
Inside your business alongside the people who do the work.
Senior, sized to the problem.
No handoffs, no timezone gaps.
G-Cloud 15 supplier. Google Cloud Partner.
You do not need to. Search and discovery sit in front of it and hand over at exactly the point your current journey does. The transaction stays where it is, with the people who own it.
It runs as a test against your existing journey before it runs as a replacement. You see the difference on the same traffic in the same weeks, with one variable moving.
Semantic search tolerates messy inventory far better than the filters you run today, because it reads meaning rather than matching fields. The first piece of work tells you how much cleaning is worth doing and how much is not.
When your catalogue is small enough that filters do the job. Also when nobody owns the conversion number, so nobody can act on what the test shows, or when what you want is a chat widget rather than a change to how discovery works.
Keep going
Bring your costliest workflow. Walk out knowing what it could return and what it would take to build.