A hotel search usually begins with dates. An evening out begins with a less obedient question: what are we in the mood for? Somewhere between “something good” and a confirmed reservation, the person making the plans acquires several browser tabs and an unpaid administrative job. Lola wants that job.
- Free AI planning and booking, with paid membership benefits.
- Founded by KAYAK’s Steve Hafner and Paul English; owned by Booking Holdings.
- A staged launch: hotels and restaurants first, with more categories following.
The company made its public debut on September 29, 2026. Its proposition is deceptively ordinary: describe what you want, refine the suggestions, and arrange the pieces in a conversation. The customer is someone choosing a restaurant, a hotel or an experience. The ambition is to keep that person from becoming the switchboard between separate services.
The question before the search
Hafner and English previously co-founded KAYAK, where travelers could compare options. Lola moves earlier in the decision. Before choosing a hotel, perhaps you need to decide whether this weekend deserves a hotel at all. Before searching for a table, you need an idea for dinner. A comparison engine assumes you know the category. An assistant can help you choose it.
In launch interviews, Hafner emphasized people’s local markets. That choice matters. Holidays are occasional; evenings arrive with tiresome regularity. A service that helps at home has more chances to learn someone’s preferences than one summoned only before an annual trip. This is the strategic logic of Lola’s pitch, rather than evidence that the habit has already formed.
A familiar name, a fresh company
There is a trap in the name. English’s earlier Lola travel business dates to 2015. During the pandemic, corporate travel was badly disrupted; its American Express Global Business Travel partnership ended in 2021. That October, Capital One acquired the team and technology as the service wound down. Those events belong to the older business.
The current Lola is a 2026 venture owned by Booking Holdings. Launch reporting described roughly 20 employees working across New York and Cambridge, Massachusetts, after about five months of building. Booking Holdings chief Glenn Fogel gave Hafner a mandate to start fresh. The distinction is consequential: an old funding total does not become a new company’s war chest because the domain is familiar.
Starting fresh also changes the design question. A conventional booking site has categories and filters to preserve. Lola starts with a conversation and connects it to services that already exist. The founders bring experience in online travel; the parent brings a network. The small team does not have to manufacture every room or restaurant relationship itself.
The expensive part is getting in
A fluent recommendation costs the reader little effort. A usable reservation asks more of the supplier. Lola’s launch network includes Booking.com, Priceline, Agoda, OpenTable and KAYAK, alongside outside partners. This is where its proposition differs from asking a general chatbot for an itinerary: suggestions have a route toward current availability and a transaction.
ResX offers a particularly revealing example. Its platform passes reservations from people who cannot use them to people who can. Lola’s partnership starts in New York and London. Plus members are promised two days of advance access; VIP members get five. Scarcity is being addressed through an inventory relationship, rather than a more persuasive sentence.
Then comes the human. Ten Group supplies concierge support for paid members, including complex itineraries and special occasions. Plus receives quarterly access; VIP receives multiple consultations each quarter. The arrangement admits that some tasks still require judgment, coordination and a person with a telephone.
“AI is incredibly powerful, but there are moments when nothing replaces an experienced human who knows exactly who to call.”
Steve Hafner · Lola co-founder and CEO
On October 1, Ten identified Lola as the client behind a multi-year Americas contract. It initially expects the agreement to sit in its Medium category: £250,000 to £2 million in annualized client fees. That range is not Lola’s exact bill, but it gives the human layer a visible economic dimension. Concierge help has a cost behind the chat window.
The membership arithmetic
Basic membership is free. Advertised Plus pricing is $5 a month and VIP is $25, each with a twelve-month commitment: $60 and $300 a year. The model resembles premium loyalty programs, charging for rates and benefits around the booking experience. Lola also says recommendations exclude advertising and paid placements.
$600 × 10% = $60
$2,000 × 15% = $300
Illustrative qualifying hotel spend to offset the annual fee through savings alone. Discounts, eligible inventory and benefits vary; these are calculations, not guaranteed returns.
A frequent user might value savings and concierge access together. An occasional diner may find the free plan sufficient. A discount matters only against the price you would otherwise pay, on something you wanted anyway. Buying a benefit is easy; arranging enough life around it to recover the fee is the less glamorous calculation.
Memory, with a price attached
Lola’s other promise is continuity. It remembers preferences so the next request can begin with context. Its privacy notice distinguishes saved facts from an AI-generated preference layer. Members can correct that memory. Connecting email or a calendar supplies additional itinerary and scheduling information; personalization therefore involves deciding how much context to share.
The practical boundaries deserve equal attention. The website describes invitations going out in waves and general availability later in the fall. Flight coverage is still forthcoming. Launch reporting puts direct hotel and restaurant booking ahead of additional event categories. A partnership announcement describes access being built; it does not make every advertised possibility immediately bookable.
For someone trying Lola, the useful starting point is a specific request: location, date, budget and preferences. Review the actual availability and cancellation terms before approving a purchase. Lola’s privacy notice says bookings require that approval. For anyone building a similar service, the lesson is equally concrete: attach recommendations to inventory, remember useful context, and provide help when the request becomes awkward. The evening still belongs to the customer.