WEB SEARCH

Built‑in web search for every model

Backboard gives you fast, production‑ready web search that works with any model you call through our API. No separate search provider, no tool‑calling support required, and no extra charge.

WEB SEARCH

Built‑in web search for every model

Backboard gives you fast, production‑ready web search that works with any model you call through our API. No separate search provider, no tool‑calling support required, and no extra charge.

Web search without extra infra

What is Backboard web search?

Backboard web search lets your apps pull in fresh, high‑quality information from the internet on demand. Instead of wiring a separate search API and teaching each model how to call it, you:

Web search without extra infra

What is Backboard web search?

Backboard web search lets your apps pull in fresh, high‑quality information from the internet on demand. Instead of wiring a separate search API and teaching each model how to call it, you:

Turn web search on with a simple flag

No API integrations, no tool schema, no per-model wiring. Enable it in your existing call.

Let Backboard handle querying, result ranking, and formatting

Backboard does the heavy lifting: running the search, selecting relevant snippets, and formatting them for the model.

Feed the results into any model, even if it does not support tool calling

Web search works at the API level, not as a tool call, so every model in the catalog benefits.

WEB SEARCH

Why engineers use Backboard web search

From zero-infra search to adaptive context budgeting — all built into one stateful API call.

WEB SEARCH

Why engineers use Backboard web search

From zero-infra search to adaptive context budgeting — all built into one stateful API call.

WEB SEARCH

Why engineers use Backboard web search

From zero-infra search to adaptive context budgeting — all built into one stateful API call.

Works with any model

No extra cost

Integrated with state, memory, and RAG

Adaptive context aware

Production‑ready answers

HOW IT WORKS

How Backboard web search works

You enable web search as part of the same msg call you already use:

1. Your app sends a user message

The same message shape you already use — no new endpoint, no schema changes.

1. Your app sends a user message

The same message shape you already use — no new endpoint, no schema changes.

2. You set web_search: true in the tools/options

One flag. That's all it takes to attach live web results to the call.

2. You set web_search: true in the tools/options

One flag. That's all it takes to attach live web results to the call.

3. Backboard runs a web search, selects relevant snippets, and injects them into the model context

Backboard handles the search, picks the most relevant results, and formats them for the model automatically.

3. Backboard runs a web search, selects relevant snippets, and injects them into the model context

Backboard handles the search, picks the most relevant results, and formats them for the model automatically.

4. Adaptive Context Management fits web results alongside state, memory, and RAG

Backboard budgets the context window automatically so web results don't crowd out memory, state, or your system prompt.

4. Adaptive Context Management fits web results alongside state, memory, and RAG

Backboard budgets the context window automatically so web results don't crowd out memory, state, or your system prompt.

USE CASES

Web search patterns you can implement

Common patterns teams build once they have live web results available on every model call.

News‑aware assistants

Answer questions about recent releases, benchmarks, and ecosystem changes.

Hybrid knowledge bots

Use memory + RAG for your internal data and web search for public context.

Research workflows

Pull in external references, compare sources, and summarize long articles.

Safety and validation

Cross‑check model claims against current information on the web.

COMPARISON

Why not just bolt on a search API?

Doing it yourself means choosing infra, stitching systems, and managing context budgets manually. Backboard handles all of it.

Doing it yourself usually means:

Choosing and integrating a third‑party search provider

Designing result formatting for each model

Handling rate limits, errors, and different relevance formats

Backboard gives you:

Web search integrated into the same unified, stateful API

Free usage as part of the platform — no per‑query fees or separate search bill.

Automatic context budgeting alongside routing, memory, and RAG

You toggle a flag instead of building another subsystem. Backboard fits web results into the context window automatically, alongside everything else.

PLATFORM

Included in Backboard, not a separate product

Web search is a first‑class, free feature of Backboard.

No separate search bill or per‑query line item

Works with any model, with or without tool‑calling capabilities

Ships alongside routing, memory, RAG, state management, and Adaptive Context

Give every model live access to the web

Wire Backboard once and add reliable web search to your entire AI stack, at no extra cost.

Give every model live access to the web

Wire Backboard once and add reliable web search to your entire AI stack, at no extra cost.

Give every model live access to the web

Wire Backboard once and add reliable web search to your entire AI stack, at no extra cost.