Live web search, grounded answers

Web Search API for real-time, grounded answers

Let your AI agents search, browse, and answer questions from the live web. Ask a natural-language question, get a structured answer with citations in seconds — no stale training data.

No credit card500 free requestsNo-code friendly

Web Search API playground

Ask a question. Inspect structured JSON.

Live web search

What is the latest news about OpenAI?

Ask a question to run a live search. This endpoint browses live pages, so it can take up to ~30 seconds — and automatically retries once if the first attempt comes back empty.

JSON structured data

{
  "task": "What is the latest news about OpenAI?",
  "answer": null,
  "sources": []
}

Developer experience

Ask a question. Get a grounded answer.

One request — a natural-language task, optionally a JSON schema — and the Answers endpoint searches the live web, browses pages, and returns a validated answer with citations.

REST APIAPI key authenticationJSON responsesLive web browsingCited sourcesNo stale training data

Read the docs

curl --request POST \
  --url https://api.olostep.com/v1/answers \
  --header 'Authorization: Bearer YOUR_API_KEY' \
  --header 'Content-Type: application/json' \
  --data '{
    "task": "What is the latest news about OpenAI?"
  }'

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The problem

Search results aren't answers

Links aren't answers

A search API hands back a page of URLs — someone still has to open them, read them, and decide what's true.

Training data goes stale

An LLM's own knowledge is frozen at its training cutoff, so it can't answer questions about today.

Trust requires sources

A confident-sounding answer with no citation can't be verified — and can't be trusted in production.

Structured, cited answers

Turn a question into a grounded response

Ask in plain language, optionally shape the output with a JSON schema, and get back a synthesized answer with the sources it came from.

Natural-language questionsOptional JSON schemaCited sourcesNOT_FOUND on low confidenceLive web browsingNo training-data cutoff

{
  "task": "Who is the CEO of Stripe?",
  "result": {
    "json_content": "{\"result\":\"Patrick Collison\"}",
    "sources": [
      "https://stripe.com/newsroom",
      "https://en.wikipedia.org/wiki/Patrick_Collison"
    ]
  }
}

Capabilities

Built for agents that need current, trustworthy answers

Live web browsing

The agent searches the web and reads relevant pages before answering — not a lookup against stale training data.

Structured JSON

Optionally define a JSON schema and get the answer back in exactly that shape, ready to store or pass downstream.

Cited sources

Every answer includes the URLs it was built from, so results can be verified rather than trusted blindly.

Hallucination-safe

Low-confidence fields return NOT_FOUND instead of a fabricated guess.

Real-time answers

Ask about today's news, prices, or events — the agent searches live, not a cached index.

Batch-ready workflows

Run recurring lookups to enrich spreadsheets, CRM records, or research pipelines at scale.

Use cases

Ground your product in live web facts

AI agents

Ground chat and research agents in live web facts instead of a frozen training cutoff.

Fact-checking

Verify claims, statistics, or generated text against real, citable sources.

Lead & data enrichment

Fill in missing fields — titles, funding rounds, news, pricing — for people and companies.

Market research

Pull current competitor moves, pricing, and announcements on demand.

Content & SEO

Check what's currently ranking or being said about a topic before publishing.

Research pipelines

Automate recurring question-answering over large lists of inputs.

How it works

From question to grounded answer

Ask a question

Send a natural-language task, optionally with a JSON schema for the shape you want back.

The agent searches and reads

Olostep searches the live web, browses relevant pages, and synthesizes an answer.

Use the response

Get a validated answer with cited sources — pass it into your agent, database, or dashboard.

Comparison

Build a search-and-synthesize pipeline or use an API?

Requirement

Build internally

Use the API

Web search

Integrate a search API

Built in

Page reading

Scrape and clean each result

Handled automatically

Answer synthesis

Wire up your own LLM call

Returned in the response

Source verification

Track URLs yourself

sources array included

Confidence handling

Detect hallucinations yourself

NOT_FOUND on low confidence

Developer time

High ongoing cost

One request

Give AI agents live web access, not just training data

Pass current, cited facts into research assistants, RAG pipelines, chat agents, and enrichment tools — grounded in what's actually on the web right now.

Pricing

Web Search API pricing

Start with 500 free requests, then scale search-and-answer workflows as volume grows.

Starter

$9/ month

For testing, prototypes, and small workflows.

Everything in Free
5,000 successful requests
150 concurrent requests

Standard

$99/ month

For agents and recurring research workflows.

Everything in Starter
200K successful requests
500 concurrent requests

Scale

$399/ month

For high-volume platforms and enterprise workflows.

Everything in Standard
1 million successful requests
AI-powered browser automations

Frequently asked questions

Product & Capabilities

What is a Web Search API?

A Web Search API lets you ask a natural-language question and get back a synthesized, cited answer — built by searching the live web and reading the pages that come back, rather than returning a list of links for you to parse yourself.

How is this different from a SERP API?

A SERP API returns the raw elements of a search results page — organic links, ads, snippets. This endpoint goes a step further: it searches, reads the pages, and returns a synthesized answer with sources.

Does it work for questions about recent events?

Yes. Because it searches the live web on every request, it isn't limited by an LLM's training cutoff — it can answer questions about things that happened today.

Usage & Automation

Can I get a structured JSON response instead of plain text?

Yes. Pass a json parameter describing the fields you want, and the response is returned in that exact shape instead of free text.

What happens if the agent can't find a confident answer?

Fields it isn't confident about come back as NOT_FOUND rather than a fabricated guess, so you can distinguish a real answer from a miss.

Are sources included?

Yes. Every response includes a sources array listing the URLs the answer was built from, so it can be independently verified.

Pricing & Plans

Can I use it for AI agents?

Yes. This endpoint is designed to ground research assistants, RAG pipelines, and chat agents in real, current web data instead of static training data.

Do I need to build my own search + scrape pipeline?

No. Searching, page-reading, and answer synthesis all happen in one request — no separate search API plus scraper plus LLM call to wire together.

How do I start?

Create an API key, run a sample question, inspect the structured response, and connect the result to your product, database, or AI workflow.

Ground your product in the live web without building search infrastructure

Start with one question and connect grounded, cited answers to AI, research, enrichment, or product workflows.