Web scraping has long been a thorn in the side of AI projects. Generative AI models are incredibly smart, but they’re only as good as the context you give them. For developers and startup founders building AI-driven products, getting that context often means pulling data from company websites – a slow, messy process. Traditional web scraping is rife with challenges: dynamic JavaScript-heavy sites, anti-bot blockers, and the constant hassle of maintaining headless browsers or rotating proxies. These bottlenecks can derail your projects, limiting your model’s knowledge and your application’s capabilities.

Enter Brand.Dev’s AI Website Query API. This newly launched feature is essentially “intelligent, reliable web scraping in an endpoint”. In simple terms, you feed it a website URL and some natural-language questions or data points, and it scrapes the site for you – fast – and returns the answers as structured data. All the nasty complexity of scraping is handled behind the scenes. The result is clean JSON output containing exactly the information you asked for, ready to be plugged into your AI workflows or databases. No more wrestling with HTML parsers or writing one-off scripts for every site. Brand.Dev’s latest API, currently released in beta, aims to eliminate the web scraping headache for good.

What Is the AI Website Query API?

Think of Brand.Dev’s AI Website Query API as a specialized AI-powered web assistant. It allows developers to extract specific information from any company website using natural language prompts – all via a single API call. In the past, answering questions like “What are this company’s main use cases?” or “Who are the founders?” meant painstakingly scraping web pages or searching manually. Now you can ask the API these questions directly. Behind the scenes, Brand.Dev’s infrastructure crawls the website and uses AI (large language models) to understand the content and find your answers. You get back a structured JSON response with the data points you requested, without having to parse a single HTML tag.

In essence, the AI Website Query API gives you an on-demand, intelligent web scraper as a service. Simply provide a domain and describe what data you need, and the API handles the rest. It will fetch relevant pages (handling any JavaScript or dynamic content), interpret them semantically, and extract the information you care about. All the heavy lifting – rendering pages, bypassing bot detection, navigating site structure – is done for you The output is structured data (JSON) that you can immediately integrate into your application or ML pipeline.

Overview of Features

• Query by Data Point: You specify the data you want in plain English (e.g. “mission statement,” “core values,” “CEO name”). The API’s AI will locate that info on the site and return it. This prompt-based approach means no brittle CSS selectors or regex – just describe it like you would to a person.

• Automated Crawling: Point the API at a URL (typically a company’s homepage or domain) and it will intelligently crawl relevant sections of the site to find your answers You don’t have to know which specific page holds the data – the AI will figure it out.

• Structured JSON Results: The response comes back in JSON with each query answered in a { "datapoint_name": ..., "datapoint_value": ... } format. This makes it trivial to feed into your code. No cleaning or parsing required – the data is ready for use in your database, CRM, or ML model.

• Fast and Scalable: Brand.Dev’s infrastructure is optimized for speed. In most cases it scrapes and returns data within seconds, even for content-heavy sites. It’s designed to scale and handle many queries in parallel, which is crucial for production workflows.

Solving Web Scraping Bottlenecks in GenAI Workflows

Why is this API a big deal for GenAI projects? Because it removes a major roadblock: getting real-time business knowledge into your AI. Generative models often need up-to-date context about a company – from what products they offer to their latest case studies or compliance certifications. Previously, developers had to build custom scrapers or manual pipelines to collect this data. That’s time-consuming, error-prone, and doesn’t easily generalize. Brand.Dev’s solution changes the game by offering a universal “website query” endpoint that does it all for you.

Here are some of the key benefits the AI Website Query API brings to AI developers and data engineers:

• No Scraping Infrastructure to Maintain: You no longer need to write and maintain your own web scrapers or headless browser farms. The API handles all of that complexity in the cloud. This frees up your engineering time to focus on your core product.

• Handles Dynamic & JavaScript-heavy Sites: Modern websites often load data via JavaScript (SPA frameworks, etc.), which breaks simple scrapers. Brand.Dev’s service renders pages like a real browser, so you reliably get content even from rich, interactive sites.

• Bypasses Bot Blocks: Getting past anti-scraping measures and CAPTCHAs can be daunting. The API is built with strategies to bypass common bot detection, so your queries won’t get stuck. Say goodbye to constant cat-and-mouse games with anti-bot systems.

• Structured Data Ready for Integration: Unlike raw HTML or unstructured text, the output here is clean JSON. It’s immediately usable – whether you’re populating a database, injecting facts into an LLM prompt, or displaying results in your app’s UI. This significantly shortens the data preprocessing pipeline for AI workflows.

• Perfect for Automation & Enrichment: The API shines in onboarding automation and data enrichment scenarios. It’s ideal for automatically filling in information about new users or companies in your system. For example, when a customer signs up with their website, you can instantly pull in their company profile, saving manual research.

All these benefits translate to a faster, smarter generative AI pipeline. You can enrich your AI’s knowledge base on the fly with factual, current data from the web, without having to periodically rebuild scrapers or worry about scraping failures. In an era where “the true AI bottleneck is context”, tools that streamline context acquisition are extremely valuable. Brand.Dev’s AI Website Query API is built to be that bridge between the live web and your AI models.

How It Works: Crawling & Semantic Extraction Under the Hood

So, what actually happens when you call the AI Website Query API? Here’s a closer look at the workflow behind a single query:

1. Define Your Query (Natural Language Prompt): You start by defining what you want to extract. Instead of coding a scraper, you create a JSON payload with a list of data_to_extract items. Each item has a datapoint_name (an identifier you choose), and a datapoint_description – a natural language description of the info you need. For example, you might ask for "mission_statement" with description "the company's mission statement" and "team_bios" with "the names of key team members and their bios". Optionally you can provide a datapoint_example to illustrate the kind of answer you expect (this helps the AI understand context). This is essentially your prompt to the system, tailored to the target website.

2. API Crawls the Website: When you send the request (including the target domain), Brand.Dev’s backend kicks in. It will crawl the website starting from the given URL and possibly follow internal links to find content relevant to your queries. Importantly, this isn’t a blind crawl of every page (which would be slow); it’s guided by the semantic clues in your descriptions. For instance, if you asked for “case studies”, the crawler might seek out pages or sections named “Case Studies” or related terms.

3. Intelligent Content Analysis: As the content is fetched, the AI model analyzes the text to locate the specific answers. This is where the “AI” part truly shines. Traditional scrapers might pull raw text and force you to regex out the bits you need. Instead, Brand.Dev’s system uses NLP to understand the context. It knows what a mission statement looks like vs. a product spec or a team bio. It will parse the page (or multiple pages) and extract the snippet of text that best matches each datapoint_description you provided. Essentially, the API is reading the website like a human would, then pulling structured answers for you. (One of the killer capabilities of modern LLMs is exactly this – reformatting and structuring information from any format X to Y).

4. Structured JSON Response: Once the AI has found the answers, the API returns a JSON object containing your domain, which URLs it analyzed, and an array of data_extracted results. Each result has the datapoint_name you specified and the datapoint_value – the answer the AI found. If something couldn’t be found, that value might be empty or an error message. But in most cases, you’ll get a concise answer string or list of items. No post-processing needed – it’s ready to use.

To make this concrete, let’s say we want to extract a couple of facts from OpenAI’s website as a demo.

Technical Walkthrough: Example Query and JSON Output

Imagine you’re building an AI app and need to quickly grab OpenAI’s mission statement and the names of its founders from their website. Using the Brand.Dev API, this is incredibly straightforward. Below is a sample using the Node.js SDK:

import BrandDev from 'brand.dev';

const client = new BrandDev({ apiKey: process.env.BRAND_DEV_API_KEY });

const response = await client.brand.aiQuery({
  domain: 'openai.com',
  data_to_extract: [
    {
      datapoint_name: 'mission_statement',
      datapoint_description: "the company's mission statement",
      datapoint_example: "Our mission is to ensure that artificial general intelligence benefits all of humanity.",
      datapoint_type: 'text'
    },
    {
      datapoint_name: 'founders',
      datapoint_description: "the names of the company's founders",
      datapoint_example: "Sam Altman, Greg Brockman, Ilya Sutskever, Wojciech Zaremba",
      datapoint_type: 'text'
    }
  ]
});

console.log(response.data_extracted);

In the above code, we initialize the Brand.Dev client with our API key, specify the target domain (openai.com), and define two data points to extract. We provided a description and an example for each to guide the AI. When this code runs, the API will go off and fetch OpenAI’s site, look for the mission statement and founders, and return the results.

Suppose the request succeeds (HTTP 200). The structure of the JSON response will look like this:

{
  "domain": "openai.com",
  "urls_analyzed": [
    "https://openai.com/about/"
  ],
  "data_extracted": [
    {
      "datapoint_name": "mission_statement",
      "datapoint_value": "OpenAI's mission is to ensure that artificial general intelligence benefits all of humanity."
    },
    {
      "datapoint_name": "founders",
      "datapoint_value": "OpenAI was co-founded by Sam Altman, Greg Brockman, Ilya Sutskever, John Schulman, and Wojciech Zaremba."
    }
  ]
}

In this output, the API indicates it crawled the About page (likely where the info was found) and it returns the mission statement and founders as requested. The datapoint_name fields match what we asked for, making it easy to pair responses to queries. This JSON can now be fed directly into your application – for example, to display on a dashboard, or as part of an LLM prompt that generates a summary about OpenAI. The urls_analyzed array is also useful, as it tells you which pages the AI ended up using to find the info.

From a developer’s perspective, using this API is a huge win. In a few lines of code, we accomplished something that would normally require writing a custom scraper or integration. The example above used Brand.Dev’s Node.js SDK, but you can call the API with any language – it’s just a REST endpoint under the hood. For completeness, here’s what the same request might look like using curl (no SDK needed):

curl -X POST "https://api.brand.dev/brand/ai/query" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
        "domain": "openai.com",
        "data_to_extract": [
          {
            "datapoint_name": "mission_statement",
            "datapoint_description": "the company'\''s mission statement",
            "datapoint_example": "Our mission is to ensure that artificial general intelligence benefits all of humanity.",
            "datapoint_type": "text"
          },
          {
            "datapoint_name": "founders",
            "datapoint_description": "the names of the company'\''s founders",
            "datapoint_example": "Sam Altman, Greg Brockman, Ilya Sutskever, Wojciech Zaremba",
            "datapoint_type": "text"
          }
        ]
      }'

This would yield the same JSON result as above. You can see how the natural language descriptions are included directly in the JSON payload – effectively turning our query into a prompt that the AI understands.

Developer Interface and SDK Support

Brand.Dev has made it easy to get started with the AI Query API. The feature is live in the Brand.Dev Developer Dashboard, which includes an interactive API explorer. You can log in to the dashboard and try the “Query website with AI” endpoint in a friendly interface – essentially an API playground where you input a domain and your data point prompts, and see the JSON output in real time. This is great for tinkering and verifying that you’ve formulated your queries correctly before integrating into code.

For integration into your application, Brand.Dev provides SDKs in multiple languages, all of which support the new AI query endpoint out-of-the-box. As of this launch, official SDKs are available for:

• Node.js/TypeScript – via the brand.dev package on npm (v2.x).

• Python – via the brand.dev package on PyPI.

• Ruby – via the brand.dev Ruby gem.

• PHP, Java, Go, etc. – the REST API can be used directly, and code examples for these languages are provided in the docs.

This broad SDK support means you can integrate the API into whichever environment you’re using with minimal effort. For instance, in Python it’s just a few lines to install the package and make the same aiQuery call as shown above. All SDKs abstract away the HTTP calls and provide a clean method interface. And if you prefer not to use an SDK, you can always call the REST endpoint directly as shown with cURL or using your favorite HTTP client.

Interface Preview: If you’re curious about how it looks, the Brand.Dev docs site offers a “Try It” console for the AI Query API. You can enter a domain and sample data points, and execute the call right from your browser (with your API key). The response JSON will be displayed, giving you a quick feel for the output structure and content.

(The developer portal was also recently revamped with a modern UI, making it even easier to navigate the documentation and test endpoints. Whether through the portal or via API calls, the experience is designed to be developer-friendly.)

Real-World Use Cases and Examples

What kinds of things can you do with the AI Website Query API? The possibilities are broad wherever you need to ingest or analyze company-specific information. Here are some real-world use cases where this API can be a game-changer:

• 🔍 CRM Enrichment & Lead Onboarding: When a new user or business signs up for your service, you likely want to gather their company info to personalize their experience. With this API, simply use their website domain to pull in key details automatically – e.g. company description, industry, size indicators, key people, etc. You can populate their profile in your database or CRM in seconds, without any manual research. This streamlines onboarding and gives your sales/customer success team instant context on the client. (For example, SaaS platforms can auto-fill a new customer’s profile with their mission statement and product offerings to tailor the dashboard content.)

• 🤖 Knowledge Base for AI Assistants: If you’re building an AI-powered assistant (say a chatbot that answers questions about various companies or a sales intelligence tool), current and factual data is gold. Instead of hardcoding information or relying on outdated data, your AI agent can call the Brand.Dev API on-the-fly to ask a company’s website about itself. For instance, an AI sales coach could query a prospect’s site for recent case studies or compliance info right before a meeting, and use that to generate talking points. This is essentially retrieval-augmented generation – your LLM gets fresh knowledge retrieved via the API, then uses it to produce more informed responses.

• 📊 Market Research & Competitor Analysis: Startup founders and analysts can use the API to quickly collect structured insights from competitors’ websites. Imagine generating a comparative table of features or pricing by querying each competitor’s site for specific data. Or automatically summarizing each competitor’s value proposition and target use cases. What used to involve lots of copy-pasting from web pages can now be automated. The API can fetch things like “What services does Company X offer?” or “What’s their mission or tagline?” so you can focus on analysis rather than data gathering.

• 🔬 Content Generation and Personalization: If your product involves generating content (emails, landing pages, reports) about or for other companies, you can make that content far more tailored by injecting real company info. For example, an AI marketing tool could use the query API to pull a company’s recent success story and then have an LLM incorporate it into a personalized case study or sales email. Similarly, a job matching platform could retrieve a company’s culture values from their site and use it to personalize recruitment messages. The key benefit is that the content your GenAI produces stays grounded in facts pulled from the company’s own website, increasing relevance and trust.

• ✅ Compliance and Due Diligence: Need to check if a vendor or partner meets certain criteria? Instead of manually hunting through their site for clues, let the AI query API do it. For instance, you could ask “Does Company Y mention GDPR or SOC2 compliance anywhere?” and get a quick answer with relevant text. This can accelerate background checks and compliance workflows by extracting the important details (like certifications, legal disclaimers, or privacy policy info) automatically.

These examples just scratch the surface. Developers are likely to come up with many creative ways to leverage an AI-powered website query. Essentially, any scenario where you think “If only I could quickly get X info from their site…” is now a candidate for automation. And importantly, you get the data in a structured form that’s easy to feed into your own systems or into further AI processing.

Get Started: Try the AI Website Query API Today

Web scraping doesn’t have to be the blocker it once was for your AI project. With Brand.Dev’s AI Website Query API, you have a powerful tool to instantly unlock website data and feed it into your generative AI workflows. This means your applications can be more dynamic, informed, and personalized — all without the months of effort it used to take to build reliable scrapers.

Ready to eliminate scraping headaches and turbocharge your GenAI app? It’s easy to get started:

• Explore the API Playground: Head over to the AI Query API documentation & playground to test-drive queries on live websites. You can input any domain and some example data points to see real results in action. It’s a great way to experiment and understand the outputs.

• Sign Up for Free: If you’re new to Brand.Dev, you can sign up for a free API key and get started in minutes. There’s a generous free tier, so you can prototype without upfront costs. No credit card is required to try it out.

• Integrate into Your Project: With your API key, use one of the SDKs (Node, Python, etc.) or direct REST calls to integrate the AI Website Query API into your application. Check out the code snippets in the docs and this article – a few lines of code are all you need to begin extracting intelligent data.

  
  

We’re excited to see how developers and founders will use this capability in the wild. Whether you’re building the next AI-powered CRM, a smart research assistant, or anything in between, Brand.Dev’s AI Website Query API can serve as a trusty sidekick – fetching exactly the web data you need, when you need it, with minimal fuss. It removes the rote task of scraping and opens up new possibilities for feature innovation.

Try it out and let us know your feedback. Happy coding, and here’s to a future without scrapers!