In today's fast-paced business environment, staying informed isn't just an advantage; it's a necessity. Market signals, competitor movements, and emerging industry trends can change overnight. The challenge? Traditional business intelligence (BI) relies on manual data gathering, a process that is slow, laborious, and often delivers insights that are already out of date.
What if you could automate this entire process? Imagine a BI dashboard that doesn't just display historical data but actively scans the horizon, pulling in fresh intelligence and updating itself automatically. This isn't science fiction. By combining the power of scheduled functions with AI research agents, you can build a dynamic, self-updating intelligence system.
Enter research.do, the AI-powered information retrieval service that transforms your most complex questions into structured, actionable insights.
For many analysts, a typical Monday morning involves a marathon of manual research. You open dozens of tabs: news sites, competitor press release pages, regulatory filing portals, and tech blogs. You sift through mountains of text, copy-pasting key sentences, and painstakingly compiling a summary report.
This workflow is fundamentally broken:
To win, businesses need to move from being reactive to proactive. You need answers on demand.
This is where research.do changes the game. It's not another search engine that just gives you a list of links to sift through. research.do deploys autonomous AI agents that perform deep research on your behalf. These agents read, understand, analyze, and consolidate information from sources you specify into a single, coherent report.
You can programmatically task an AI agent to conduct in-depth research with a simple API call.
Here’s how easy it is to launch a comprehensive research query using the research.do SDK:
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);
With just a few lines of code, you've tasked an AI to perform hours of research, synthesize its findings from trusted sources, and deliver a formatted report directly into your workflow.
Now, let's connect this power to a BI dashboard. The goal is to create a system that automatically executes research queries on a schedule, stores the results, and visualizes them.
First, identify the key areas you need to monitor. A typical business might track:
For each vector, you'll create a specific query. The key here is to request the output in json format, which makes it easy to parse and store in a database.
Let's set up a few queries:
// For tracking competitors
const competitorQuery = {
query: "Summarize recent news, product launches, and executive changes at CompetitorX and CompetitorY in the last 7 days.",
sources: ["competitorX.com/news", "competitorY.com/blog", "techcrunch.com"],
format: "json"
};
// For tracking market trends
const marketQuery = {
query: "What are the latest developments and analyst sentiments on the generative AI market this week?",
sources: ["venturebeat.com", "reuters.com/technology"],
format: "json"
};
You can create as many of these targeted queries as you need, each with its own set of trusted sources.
This is where the "self-updating" magic happens. Use a scheduler like a Vercel Cron Job, AWS Lambda Scheduled Event, or a simple Node.js process with node-cron to run your research jobs automatically.
Here's a conceptual example of a serverless function that runs once a day:
// /api/cron/update-bi-data.js
import { Do } from '@do-inc/sdk';
import { db } from './your-database-client'; // e.g., Supabase, PlanetScale, Firestore
export default async function handler(request, response) {
const researchAgent = new Do('research.do', { apiKey: process.env.DO_API_KEY });
// Define our queries
const queries = {
market_trends: { /* ... marketQuery from above ... */ },
competitor_news: { /* ... competitorQuery from above ... */ }
};
for (const [key, q] of Object.entries(queries)) {
console.log(`Running research for: ${key}`);
const report = await researchAgent.run(q);
// Save the structured JSON result to our database
await db.saveReport({
type: key,
data: report.result, // Contains the structured JSON
createdAt: new Date(),
});
}
response.status(200).send('BI Data Updated Successfully!');
}
Now, every day (or every week), your system will automatically run these deep research tasks and populate your database with fresh, structured insights.
With the synthesized data flowing into your database, the final step is to visualize it. Connect your database to any modern BI tool (like Tableau, Looker, Power BI) or build a custom dashboard with a frontend framework (like React or Vue).
Because research.do provided the data in a clean json format, you can easily create components like:
Building a self-updating BI dashboard with research.do fundamentally transforms how you gather and act on information.
Ready to stop chasing information and start getting answers on demand? Visit research.do to see how you can programmatically research and retrieve information for your business and AI workflows.
What kind of research can research.do perform?
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.
How does research.do ensure the quality and accuracy of the information?
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.
Can I specify the sources for my research query?
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.
What formats are the research results delivered in?
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.
How is research.do different from a standard search engine?
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.