# Grounded Research Api Quick Start

**Use case:** 

Quick-start: research a city's population and founding year with a custom JSON output schema.

## Input

```json
{
  "question": "What is the current population of Austin, Texas, and what year was the city founded?",
  "outputSchema": {
    "population": "number, most recent estimate",
    "foundedYear": "number or null if not found",
    "state": "string"
  },
  "context": "",
  "model": "gemini-3.8-flash"
}
```

## Output

```json
{
  "groundingUsed": {
    "label": "Live-grounded?",
    "format": "boolean"
  },
  "model": {
    "label": "Model",
    "format": "string"
  },
  "verifiedAt": {
    "label": "Researched at",
    "format": "string"
  }
}
```

## How it works

### 1. Sign up on Apify or log in

The Grounded Research API — Any Question, Your JSON Schema Actor is ready to run with the inputs already set for "Grounded Research Api Quick Start". [Sign up or log in](https://console.apify.com/create-task-from-example/W0ERIRXvA7FC5i1cp) and you'll land in Apify Console with a copy of this exact task.

### 2. Start the "Grounded Research Api Quick Start" task

The Grounded Research API — Any Question, Your JSON Schema Actor will start running based on the input automatically. You can also change all the input fields, like question / research topic, desired output schema, and more, to match your specific use case.

### 3. Receive the "Grounded Research Api Quick Start" output

Monitor the progress in real time. You will be notified as soon as your dataset is complete and ready for review. Each result includes data such as live-grounded?, model, and researched at.

### 4. Integrate into your workflow

The final output is delivered in JSON, CSV, or Excel format, ready to be plugged into your workflow. You can also [run the "Grounded Research Api Quick Start" task via API](https://apify.com/rumi7911/grounded-research-api.md).

## About this Actor

This example demonstrates how to use [Grounded Research API — Any Question, Your JSON Schema](https://apify.com/rumi7911/grounded-research-api.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/rumi7911/grounded-research-api.md) to learn more, explore other use cases, and run it yourself.


## How to integrate an Actor?

This Task's input is already configured above. Use it as-is rather than inventing a new one.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/rumi7911/grounded-research-api.md

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).