In today's fast-paced digital landscape, the speed at which you can gather, analyze, and act on information is a critical competitive advantage. Yet, for many organizations, market research remains a bottleneck. It's a manual, time-consuming process of sifting through endless search results, news articles, and financial reports, hoping to piece together a coherent picture.
What if you could treat research not as a manual task, but as a utility? What if you could programmatically request deep, synthesized insights and have them delivered directly into your applications?
This is the promise of AI-driven information retrieval. It's about moving from endless searching to direct answering. Welcome to the world of research-as-a-service.
Traditional market research is broken. It involves:
This manual process is not just inefficient; it’s a barrier to agility. By the time a report is complete, the market may have already shifted.
Imagine deploying autonomous AI agents to perform this cognitive work for you. That's the core idea behind research.do. Instead of just returning a list of ranked documents like a search engine, these agents execute a complete research workflow:
This is the future of Business-as-Code, where complex business functions like research are automated and integrated via a simple API.
Talk is cheap. Let's see how simple it is to turn a complex research request into a single API call.
Suppose you're a strategist or developer tasked with understanding the impact of quantum computing on the financial sector. With research.do, you don't need to start with a search engine. You start with code.
import { Do } from '@do-inc/sdk';
const research = new Do('research');
async function getMarketAnalysis(topic: string) {
const report = await research.query({
prompt: `Generate a comprehensive market analysis report for ${topic}. Include key players, market size, recent innovations, and potential challenges.`,
sources: ['web', 'news', 'sec-filings', 'arxiv'],
depth: 'comprehensive',
format: 'json'
});
console.log(report.summary);
// Example Output: "The quantum computing market in finance is projected to reach $X.X billion by 2030, driven by applications in risk analysis and algorithmic trading. Key players include..."
console.log(report.data.key_players);
// Example Output: ["Company A", "Company B", "Startup C"]
return report;
}
getMarketAnalysis('Quantum Computing in Finance');
In this agentic workflow:
The result is a rich object containing a synthesized summary, extracted data points, and more—delivered in seconds, not weeks.
How is this different from a standard search engine?
While search engines are phenomenal tools for document retrieval, research.do performs the next step: the cognitive work. It reads and understands the documents to provide a synthesized answer to your question, saving you from doing the manual analysis yourself.
What kind of sources can I research?
Our platform can connect to a vast array of information sources, including public web pages, news APIs, academic archives like arXiv and PubMed, financial filings, and even your own private document repositories (when granted secure access).
Is the output just a list of links?
Absolutely not. You get structured JSON output containing synthesized summaries, key findings, extracted data points, and fully cited sources. This makes the information immediately usable for powering dashboards, generating reports, or feeding into other AI models.
The ability to programmatically query the world's information and receive structured, synthesized insights is a superpower. It enables businesses to build smarter applications, automate competitive intelligence, accelerate R&D, and make strategic decisions with unprecedented speed and depth.
Stop searching. Start knowing.
Ready to turn research into a service? Explore the research.do platform and start building the future of information retrieval today.