Hospitality intelligence done right

InBetween maintains detailed, continuously updated profiles of restaurants, bars, and cafés: menus, dietary coverage, atmosphere, seating, and the signals that decide whether a place suits an occasion.

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api.inbe.us/v1/search200 OK
POST
{
"locations": [
{ "lat": 51.5072, "lon": -0.1276, "weight": 30 },
{ "lat": 51.5154, "lon": -0.1419, "weight": 40 },
{ "lat": 51.5034, "lon": -0.1195, "weight": 30 }
],
"mode": {
"mode": "POINT"
"maxDistance": 200
},
"preferences": {
"openingConditions": {
"state": "ANY"
"atTime": "2026-08-15T17:53:51.178Z"
},
"goodFor": ["family", "coffee", "date"]
"catersFilters": ["vegetarian", "glutenFree", "vegan"]
"establishmentFilters": ["restaurant"]
}
}

For platforms requiring deep food and drink data

Depth beats breadth where decisions are made.

Generalist POI datasets cover everything a little: a name, a category, coordinates, opening hours. If eating, drinking, or meeting is core to your product, that is not enough to make a recommendation you would stand behind.

Real matching needs real data: structured dietary coverage, menu depth, atmosphere, seating, accessibility. Building and maintaining that yourself means scraping, enrichment pipelines, and a permanent engineering tax.

InBetween exists so you do not have to. We build ultra-detailed profiles of restaurants, bars, and cafés and keep them current, so your product builds on data designed for matching rather than mapping.

What breaks today

  • Generalist datasets are shallow exactly where dining products need depth.
  • In-house enrichment pipelines are a permanent engineering tax.
  • Inconsistent place records produce inconsistent product experiences.

What you can ship

  • A single, reliable source of truth for food and drink.
  • Rich filters and detailed venue pages without extra data pipelines.
  • Data that improves continuously without your involvement.

How it works for you

  1. 01

    Build on profiles made for matching

    Every venue carries structured fields for diet, seating, atmosphere, price band, and operating status.

  2. 02

    Serve every surface from one API

    Search, recommendations, AI tools, and detail pages all draw from the same source of truth.

  3. 03

    Skip the enrichment pipeline

    No scraping, no review parsing, no data team required to keep the records accurate.

Built into the broader InBetween platform

This capability sits alongside the rest of our hospitality venue intelligence—so you can combine filters, search, and decision tools in one product surface.

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.

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.

The food and drink data layer

Build on data made for decisions.

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.

Explore the APIStart building for free

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.

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

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

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

Migration programme