Business Intelligence (BI) dashboards are the command center for modern enterprises. They provide a vital, at-a-glance view of KPIs, sales figures, and operational metrics. But what if your dashboards could do more than just report on internal, historical data? What if they could tap into the entire world's information, analyze it, and present timely competitive insights, market trends, and risk analyses in real-time?
The traditional BI workflow has a bottleneck: the human analyst. While tools like Tableau and Power BI are exceptional at visualizing structured data, they can't answer the crucial "why" behind the numbers. Answering that requires hours of manual research—sifting through news articles, competitor websites, and financial reports. This process is slow, expensive, and fundamentally unscalable.
This is where agentic AI workflows change the game. With research.do, you can transform your BI dashboards from static rearview mirrors into dynamic, forward-looking intelligence platforms.
Your data warehouse is a goldmine of information about your business. But your business doesn't operate in a vacuum. To make strategic decisions, you need external context:
Getting these answers and feeding them into a BI tool has always been a manual, labor-intensive process. By the time an analyst synthesizes the information and loads it into a dashboard, it's already on its way to being outdated.
research.do isn't another search engine. It's an AI-powered information retrieval and analysis engine that you can command through a simple API. You don't get a list of links; you get structured, synthesized insights ready for immediate use.
Think of it as deploying autonomous AI agents to perform the cognitive work of a human research team. These agents can:
This is Business-as-Code in action. You can programmatically define a research task and get a comprehensive report back, turning complex analysis into a reliable, automated service.
Integrating the real-time power of research.do into tools like Tableau, Power BI, or Looker is straightforward. It involves setting up a simple data pipeline that automates the research and feeds it into a source your BI tool can read.
Here’s the step-by-step architectural pattern:
Step 1: Define Your Research Query via the API
First, decide what strategic information your dashboard needs. Instead of a simple keyword, think in terms of a research task you'd give an analyst. You can automate this task using the research.do SDK.
Let's say you want to build a dashboard to track the quantum computing market. Your API call might look like this:
import { Do } from '@do-inc/sdk';
const research = new Do('research');
async function getMarketAnalysis(topic: string) {
console.log(`Requesting market analysis for ${topic}...`);
const report = await research.query({
prompt: `Generate a comprehensive market analysis report for ${topic}. Include key players, recent technological breakthroughs, and investment trends.`,
sources: ['web', 'news', 'sec-filings', 'arxiv'],
depth: 'comprehensive',
format: 'json'
});
console.log('Report received:');
console.log(report.summary);
return report; // This is a structured JSON object
}
// Run the analysis
const marketReport = await getMarketAnalysis('Quantum Computing in Finance');
Step 2: Automate and Store the Results
Wrap your API call in a simple script (Python, Node.js) and run it on a schedule using a cron job or a serverless function (like AWS Lambda or Google Cloud Functions). This script will execute your research query—for example, once every 24 hours.
The script then takes the structured JSON response from research.do and writes it to a database that your BI tool can connect to, such as PostgreSQL, BigQuery, Snowflake, or even a cloud-hosted flat file.
Step 3: Connect Your BI Tool and Visualize
This is the final step. Point your BI tool to the database where your research.do insights are now stored. The data is already clean, structured, and ready to be visualized.
You can now build dynamic dashboard components that are powered by live AI research:
Your dashboard is no longer just a reflection of the past. It's a living document that provides the context and foresight needed for smart, proactive decision-making.
Stop limiting your business intelligence to internal data. By integrating research.do into your BI stack, you can automate cutting-edge research and empower your teams with the freshest, most comprehensive insights available. Move beyond static reports and build a true intelligence engine for your business.
Explore the research.do API and start turning research into a service today.
How does research.do work?
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.
What kind of sources can I research?
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.
Is the output just a list of links?
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.
How is this different from a standard search engine?
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.