Research-as-a-Service: The Future of Business Intelligence is On-Demand

In today's data-driven world, the speed and quality of your research can be the difference between leading the market and falling behind. Yet, for most organizations, research remains a fundamentally manual, time-consuming, and expensive process. Teams spend countless hours sifting through web pages, news articles, and dense reports, trying to piece together a coherent picture. The result? Slow-moving projects, decision-making based on incomplete data, and valuable expert time lost to tedious legwork.

But what if you could change that? What if research wasn't a manual task, but an on-demand service, available programmatically? What if you could deploy autonomous AI agents to perform comprehensive research and deliver structured, actionable insights directly into your applications?

This is the promise of Research-as-a-Service (RaaS), a new paradigm powered by agentic AI. And at the forefront of this revolution is research.do, a platform designed to turn research into a utility.

The Bottleneck of Traditional Research

The traditional research workflow is broken. It's a bottleneck that slows down innovation and analysis across every department.

• It's Slow: A single, comprehensive market analysis can take days or weeks of manual effort.
• It's Inconsistent: The quality of research is often dependent on the individual performing it, leading to biases and varying levels of thoroughness.
• It's Unstructured: The output is typically a collection of bookmarks, notes, and documents, making it difficult to integrate into automated workflows or applications.
• It Doesn't Scale: You can't simply "10x" your research capacity without hiring a "10x" larger team.

Modern business runs on APIs. We treat payments, communication, and infrastructure as code. It’s time we did the same for business intelligence and information retrieval.

Enter research.do: Your Research, Automated

research.do transforms the entire research process from a manual chore into a simple API call. Instead of just returning a list of links like a standard search engine, our platform deploys autonomous AI agents that perform the cognitive work of a human researcher.

It works through a powerful, agentic workflow:

1. You Define the Mission: You start with a simple prompt, asking a complex question or requesting a specific report.
2. You Specify the Sources: You tell the agents where to look—the open web, news APIs, financial filings (SEC), academic archives like arXiv, or even your own private document repositories.
3. Agents Execute the Plan: The AI agents autonomously browse, read, analyze, and cross-reference information from the specified sources. They understand context, filter out noise, and identify relevant data points.
4. You Receive Synthesized Intelligence: The platform doesn't just give you raw data. It delivers a structured JSON report containing synthesized summaries, key findings, extracted insights, and fully cited sources. This output is immediately machine-readable and ready for use.

This isn't just a better search engine; it's a fundamental shift in how we access and process information. It's Business-as-Code.

See It in Action: Research Becomes a Function Call

The elegance of Research-as-a-Service lies in its simplicity. You can integrate sophisticated data analysis and information retrieval capabilities into any application with just a few lines of code.

Here's how you could generate a comprehensive market analysis report using the research.do SDK:

import { Do } from '@do-inc/sdk';

const research = new Do('research');

async function getMarketAnalysis(topic: string) {
  const report = await research.query({
    prompt: `Generate a market analysis report for ${topic}. Include key players, market size, and future trends.`,
    sources: ['web', 'news', 'sec-filings'],
    depth: 'comprehensive',
    format: 'json'
  });

  console.log(report.summary);
  // Example output: "The Quantum Computing market in Finance is projected to grow..."
  
  console.log(report.data.key_players);
  // Example output: ["Company A", "Company B", "Company C"]

  return report;
}

getMarketAnalysis('Quantum Computing in Finance');

In this example, a complex research task that would take a human analyst days is completed in minutes via an API call, with the output structured perfectly for ingestion into a dashboard, database, or downstream AI workflow.

Frequently Asked Questions

Q: How does research.do work?

A: You define a research query and specify sources (like the web, academic papers, or internal docs). Our AI agents then execute a plan to find, filter, and synthesize relevant information, returning a structured report via API.

Q: What kind of sources can I research?

A: Our platform can query public web pages, news APIs, academic archives like arXiv and PubMed, financial filings, and even your own private document repositories when granted access.

Q: Is the output just a list of links?

A: No, research.do delivers structured JSON output containing synthesized summaries, key findings, extracted data points, and cited sources, making the information immediately usable in your applications or workflows.

Q: How is this different from a standard search engine?

A: While search engines return ranked documents, research.do performs the cognitive work of reading, understanding, and synthesizing information from multiple sources to directly answer your complex questions, much like a human researcher.

The Future is On-Demand

The era of manual, slow, and siloed research is over. The future of business intelligence, competitive analysis, and data-driven decision-making is automated, integrated, and on-demand. By treating research as a programmable service, organizations can unlock unprecedented speed and scale, embedding powerful insights into the very fabric of their operations.

Ready to stop searching and start knowing?

Visit research.do to learn how you can automate your research workflows and turn insights into a service.