Automating Competitive Analysis with AI-Powered Agentic Workflows

In today's fast-paced market, staying ahead of the competition isn't a luxury—it's a necessity. But traditional competitive analysis is broken. It's a manual, time-consuming process of sifting through news articles, press releases, and websites. By the time you compile your findings into a comprehensive report, the data is already stale.

What if you could change the game? What if you could transform competitive analysis from a periodic chore into a continuous, real-time intelligence stream?

This is the promise of agentic workflows, a new paradigm in AI that's redefining how businesses gather and process information. By deploying autonomous AI agents, you can automate complex research tasks and get structured insights on-demand, delivered directly into your applications.

From Manual Search to Autonomous Research

The fundamental difference between a standard search engine and an AI research agent lies in the cognitive workload.

• A search engine returns a list of ranked documents, leaving the heavy lifting of reading, filtering, understanding, and synthesizing the information to you.
• An AI agent, powered by a platform like research.do, takes your high-level objective and executes a multi-step plan to achieve it. It performs the cognitive work for you, much like a human researcher.

This is the core of an agentic workflow: you don't just ask for links, you ask for answers. You turn research into a service.

Building Your Automated Competitor Analyst with research.do

Let's walk through how you can build a powerful, automated workflow to monitor your competition using the research.do API. The goal is to continuously monitor a competitor, analyze their market positioning, and deliver real-time strategic intelligence.

Step 1: Define the Mission

First, define what you want the AI agent to accomplish. Instead of a simple keyword, you provide a detailed prompt that outlines the research objective.

Prompt: Generate a competitive analysis report on InnovateCorp's launch and marketing strategy for their new product, 'QuantumLeap CRM'. Focus on key messaging, identified target audience, and media reception.

Step 2: Specify the Intelligence Sources

Next, tell the agent where to look. research.do can query a vast array of sources simultaneously, ensuring comprehensive coverage that a human team could never match in the same timeframe.

Sources: ['web', 'news', 'press-releases', 'sec-filings']

Step 3: Deploy the Agent & Synthesize Insights

With the mission and sources defined, you deploy the agent. Using the research.do SDK, this is as simple as making an API call.

The platform's autonomous agents get to work:

1. Planning: The main agent breaks down the prompt into a series of sub-queries and tasks.
2. Gathering: It dispatches other agents to query the specified sources for relevant information.
3. Analyzing: The agents read and understand the content, extracting key data points, quotes, and themes.
4. Synthesizing: The findings are compiled and synthesized into a coherent, structured report.

Step 4: Integrate Actionable Intelligence

The final output is not a list of links. It's a structured JSON object containing synthesized summaries, key findings, and cited sources, making the information immediately usable. You get the intelligence, not just the data.

Here’s what that looks like in code:

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

const research = new Do('research');

async function trackCompetitor(companyName: string, product: string) {
  console.log(`🚀 Deploying AI agent to analyze ${companyName}...`);

  const intelligenceReport = await research.query({
    prompt: `Generate a competitive analysis report on ${companyName}'s launch and marketing strategy for their new product, ${product}. Focus on key messaging, target audience, and media reception.`,
    sources: ['web', 'news', 'press-releases'],
    depth: 'comprehensive',
    format: 'json'
  });

  // The report contains a summary and structured data
  console.log("\n--- EXECUTIVE SUMMARY ---");
  console.log(intelligenceReport.summary);

  // Example of accessing structured data
  // console.log("\n--- KEY MESSAGES ---");
  // console.log(intelligenceReport.data.keyMessages);

  return intelligenceReport;
}

trackCompetitor('InnovateCorp', 'QuantumLeap CRM');

This isn't just a one-off report. You can run this workflow on a schedule (daily, weekly) to continuously feed a BI dashboard, trigger Slack alerts for significant news, or update internal battle cards automatically. This is "Business-as-Code" in action.

The Agentic Advantage

Adopting an AI-powered agentic workflow for competitive analysis provides immediate, tangible benefits:

• Real-Time Awareness: Move from quarterly reports to a live pulse on the market.
• Deep Scalability: Analyze ten competitors as easily as you analyze one.
• Reduced Manual Effort: Free up your strategic teams to focus on decision-making, not data-gathering.
• Actionable Output: Get structured, API-first data that integrates directly into the tools you already use.

Stop reacting to outdated information. Start anticipating market moves with automated intelligence.

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.

Ready to turn competitive research into a service? Explore the research.do platform and discover how autonomous AI agents can become your most valuable analysts.