Saved posts should become plans.

Someone watches a video of a perfect Sunday brunch and saves it. InBetween turns that moment into a real suggestion: this place, or somewhere just as good that suits them, near them.

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@mayaeats

Creator · Food

Saved

Counter pasta night at Barrafina: loud, bright, worth the queue.

Soho · Spanish tapas

Inspired? Find your matchPlan this

Matched to your prefs

Same vibe · quieter · gluten-free near you

The Lantern Room

Modern European · ££ · 11 min

Counter energyGluten-freeQuiet corner
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For social media platforms, creator tools, and content apps

Close the loop between inspiration and going.

Social platforms are extraordinary at generating desire for places: a creator's video, a friend's photo, a saved post promising a perfect evening. What happens next is usually nothing. The save is forgotten, the venue is in another city, or nothing on the menu suits them.

InBetween closes that loop. Content links to structured venue profiles, so a saved post becomes an actionable suggestion, and if the featured spot does not work for this viewer, we find one nearby with the same character that does.

For the platform, a passive save becomes a measurable real-world outcome, which is a story creators, users, and advertisers all care about.

What breaks today

  • Saved posts pile up and are never acted on.
  • A creator's favourite spot may not suit the viewer's diet, budget, or city.
  • Users leave the platform to work out whether a place is actually viable.

What you can ship

  • Saves that convert into visits.
  • Suggestions personalised to the viewer, not just the creator.
  • Measurable offline outcomes from on-platform engagement.

How it works for you

  1. 01

    Link content to real venue data

    Creator posts and videos connect to structured profiles: location, menu, atmosphere, price.

  2. 02

    Adapt the suggestion to the viewer

    The recommendation respects the viewer's diet, budget, and location, not just the creator's.

  3. 03

    Make it easy to go together

    Shareable cards and group matching turn a save into a plan with friends.

Every venue. Every detail.

Precision metadata for apps that help people meet, eat and drink.

Venue intelligence

Ultra detailed venue data

Get detailed information about venues, including menus, pricing, ambiance, and more.
Smart matching

Preference driven

Wow your customers with recommendations and information tailored for them.
Multi-location search

Tools for multiple locations. Find restaurants, bars and cafés based on multiple sets of preferences and locations.

In-app experience

Loyal to you

Keep users inside your app by giving them the info they need to make decisions.
Decision support

Built for decision-making

A suite of tools designed to enable you to answer customer needs directly.

From content to plans

Make saved posts worth saving.

Open up a new world for your users with InBe's preference-aware venue discovery—built for group venue matching, dietary search, and ranked shortlists.

No card required. Full core API access.

Start building for freeExplore the API

Keep exploring

Questions teams ask

Built for developers who connect people to places

Start buildingExplore the API

Connecting users to real-world places shouldn’t mean stitching geocoding, routing, Places search, and ranking yourself. One preference-aware search replaces the pipeline.

api.inbe.us/v1/search200 OK
POST
{
"locations": [
{ "lat": 51.523, "lon": -0.158, "label": "Alex" },
{ "lat": 51.493, "lon": -0.098, "label": "Sam" }
],
"mode": { "mode": "POINT", "maxDistance": 750 },
"preferences": {
"goodFor": ["date", "cocktails", "conversation"],
"catersFilters": ["vegetarian"],
"establishmentFilters": ["servesCocktails"]
}
}
response
{
"centerPoint": { "Lat": 51.508, "Lon": -0.128 },
"radius": 750,
"establishments": [
{
"displayName": "The Lantern Room",
"distanceMeters": 142,
"matchScore": { "total": 0.94 }
},
{
"displayName": "Barrio Soho",
"distanceMeters": 186,
"matchScore": { "total": 0.91 }
}
]
}

Fair middlegrounds

Multi-person locations in one call; we balance travel so you don’t build routing yourself.

Preferences that actually match

Dietary, vibe, good-for, and constraints as first-class inputs, not post-filters on pins.

Pay for the hard parts

Core search and enriched place data stay cheap; you pay where decision intelligence earns its keep.

Tools for user decisions

Ranked shortlists and experience-ready answers so your product keeps users in-flow, not off to a map.

Illustrative scenario

0ms

Ranked shortlist in one call

Preference-aware search returns a decision-ready shortlist without stacking Places, routing, and enrichment calls.

~15× faster vs multi-call pipelinesNot a live benchmark
RESTWorks with any stack
curl -X POST https://api.inbe.us/v1/search \
  -H "API-Key: YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "locations": [
      { "lat": 51.523, "lon": -0.158, "label": "Alex" },
      { "lat": 51.493, "lon": -0.098, "label": "Sam" }
    ],
    "mode": { "mode": "POINT", "maxDistance": 750 },
    "preferences": {
      "goodFor": ["date", "cocktails", "conversation"],
      "catersFilters": ["vegetarian"],
      "establishmentFilters": ["servesCocktails"]
    }
  }'
Full examples in docs

Start in minutes with the knolage you can scale without stress.

Generous free usage to evaluate, startup credits to grow, and a migration path when you are ready to switch from stacked Places pipelines.

Start in minutes

No sales call. Sign in, grab a key, and ship a first search.

Start building

Build — free forever

£10 of usage every month, full core API, no card required.

See Build plan

InBe for Startups

£2,500 usage credit, Grow-level features, and onboarding support.

Startup programme

Switch with confidence

Migration credits from £500, dual-running help, and high-spend matched offers.

Migration programme