We’ve all heard the old computing adage: "Garbage In, Garbage Out." It’s a simple, timeless principle—the quality of your output is determined by the quality of your input. In the age of AI, this concept has evolved into a more subtle and dangerous phenomenon: Garbage In, Gospel Out.
Generative AI models can produce incredibly fluent, confident, and detailed answers. The problem is, they can be confidently wrong. When an AI hallucinates a fact, pulls from an outdated source, or misinterprets a query, it still presents the information with an air of authority. This transforms questionable data into seemingly infallible gospel, creating a massive risk for any professional who relies on accurate information for decision-making.
The solution isn't to abandon the incredible power of AI for research. It's to take control of its diet. For high-stakes AI research, information retrieval, and data synthesis, you need to be the master of your sources.
Large-scale AI models are trained on a vast, undifferentiated swath of the public internet. For a casual query, that’s fine. But for professional market analysis or business intelligence, it’s a non-starter. You can't risk your strategy on an AI that might be pulling data from a 2018 blog post, a Reddit comment, or a completely fabricated source.
The core challenges are:
Traditional research isn't much better. Manually sifting through dozens of search engine tabs, cross-referencing PDFs, and compiling notes is a laborious process that AI was meant to solve. The goal isn't a list of links; it's a synthesized, actionable insight.
This is where a new approach to AI research becomes essential. Instead of asking an AI to search the entire internet, what if you could deploy an autonomous agent to perform deep research only within a universe of sources you define and trust?
That’s the exact principle behind research.do. You remain in the driver's seat.
Imagine you need to Analyze Q1 2024 market trends for renewable energy in North America. Instead of a generic web search, you can instruct the AI agent to confine its work to the most authoritative sources.
import { Do } from '@do-inc/sdk';
const researchAgent = new Do('research.do', { apiKey: 'YOUR_API_KEY' });
const report = await researchAgent.run({
query: "Analyze Q1 2024 market trends for renewable energy in North America.",
sources: ["sec.gov", "bloomberg.com", "reuters.com"],
depth: "comprehensive",
format: "markdown_report"
});
console.log(report.result);
In this simple request, you’ve done something revolutionary. You’ve told the AI: "Here is the sandbox you will play in. Every insight, every data point, and every conclusion must be derived only from these trusted domains."
This transforms the AI from an unpredictable black box into a precise, programmatic tool for information retrieval.
By controlling the input, you ensure the output isn't just "gospel"—it's verifiable, relevant, and trustworthy.
research.do goes beyond just fetching information. It employs a multi-agent system that reads, understands, analyzes, and cross-references findings within your specified sources. It synthesizes this complex information into a single, coherent report.
Instead of a dozen links, you get a structured answer. The output can be formatted as you need it—a Markdown report for easy reading, structured JSON for workflow integration, or a simple text summary for a quick overview.
This is the promise of AI research fulfilled: the speed and power of machine intelligence guided by the precision and authority of human curation. It’s how you transform questions into insights without the manual effort or the risk of unreliable data. Don't let your research be a victim of "Garbage-In, Gospel-Out." Control your sources, and trust your results.
Q: What kind of research can research.do perform?
A: Our AI agents can conduct a wide range of research, including market analysis, competitive intelligence, academic literature reviews, financial due diligence, and technology trend reporting. Just define your query, and the agent handles the rest.
Q: How does research.do ensure the quality and accuracy of the information?
A: research.do employs a multi-agent system that cross-references information from multiple user-specified or trusted sources. It analyzes, synthesizes, and cites its findings, providing a transparent and reliable research output.
Q: Can I specify the sources for my research query?
A: Yes. You have full control to limit the research to specific domains, URLs, or document repositories to ensure the information is gathered from your preferred, trusted sources.
Q: What formats are the research results delivered in?
A: You can request results in various formats, including structured JSON, a formatted Markdown report, a simple text summary, or a full-fledged PDF document, making it easy to integrate insights into your existing workflows.
Q: How is research.do different from a standard search engine?
A: While a search engine returns a list of links, research.do provides a synthesized answer. It reads, understands, and consolidates information from numerous sources into a single, coherent report, saving you hours of manual work.