From sign-up to first search in minutes.

A clean REST API, typed clients, low-latency search, and documentation that respects your time. No sales call required.

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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": "2026-08-16T17:53:51.178Z"
},
"goodFor": ["family", "coffee", "date"]
"catersFilters": ["vegetarian", "glutenFree", "vegan"]
"establishmentFilters": ["restaurant"]
}
}

For product engineers evaluating venue search APIs

Good developer experience is mostly restraint.

Most location APIs accumulated their interfaces over a decade. The payloads are verbose, the docs assume history you do not have, and getting a key involves talking to someone.

InBetween is newer, and it shows in the right ways: self-serve keys, logical schemas, typed clients, and endpoints fast enough to sit behind an autocomplete field.

Whether you are adding a search bar or building multi-person matching, the integration should be the easy part. We work hard to keep it that way.

What breaks today

  • Verbose legacy payloads make simple integrations feel heavy.
  • Documentation written for enterprise buyers, not the engineer integrating it.
  • Response times too slow to sit behind an interactive search box.

What you can ship

  • A live integration on day one, not week three.
  • Type safety across your whole stack.
  • Search fast enough to feel native in your interface.

How it works for you

  1. 01

    Get a key without a sales call

    Sign in, generate a key, and make your first request on the free tier.

  2. 02

    Work with typed, predictable schemas

    Official clients ship with full TypeScript definitions for every request and response.

  3. 03

    Build responsive interfaces

    Search latency is low enough for live autocomplete and interactive result views.

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.

Built for the integrating engineer

Generate a key and make your first search.

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.

Keep exploring

Questions teams ask

Built for developers who connect people to places

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"]
    }
  }'

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.