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    <title>DEV Community: Osama</title>
    <description>The latest articles on DEV Community by Osama (@osamatech786).</description>
    <link>https://dev.to/osamatech786</link>
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      <title>DEV Community: Osama</title>
      <link>https://dev.to/osamatech786</link>
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      <title>How I Built a 4-Agent Orchestrator to Automate B2B Sales Research in 15 Seconds</title>
      <dc:creator>Osama</dc:creator>
      <pubDate>Sun, 09 Aug 2026 20:39:31 +0000</pubDate>
      <link>https://dev.to/osamatech786/how-i-built-a-4-agent-orchestrator-to-automate-b2b-sales-research-in-15-seconds-1l60</link>
      <guid>https://dev.to/osamatech786/how-i-built-a-4-agent-orchestrator-to-automate-b2b-sales-research-in-15-seconds-1l60</guid>
      <description>&lt;p&gt;Personalizing B2B cold outreach is a massive time sink. It usually takes 20 minutes of manual research per lead to write an email that doesn't sound like a robot. I wanted to see if I could automate the research phase using agentic composition, so I built a multi-agent orchestrator using Python and OpenRouter.&lt;/p&gt;

&lt;p&gt;Here is the breakdown of the architecture and how I routed the data.&lt;/p&gt;

&lt;h3&gt;
  
  
  The Problem
&lt;/h3&gt;

&lt;p&gt;If you just ask an LLM to "write a sales email", it hallucinates or sounds generic. It needs grounded context. We needed a system that could read live web pages, run searches for recent news, and synthesize it all before drafting.&lt;/p&gt;

&lt;h3&gt;
  
  
  The Agent Stack
&lt;/h3&gt;

&lt;p&gt;I deployed specialized tools using OpenRouter as the underlying engine:&lt;/p&gt;

&lt;ul&gt;
&lt;li&gt;  &lt;strong&gt;URLReaderAgent:&lt;/strong&gt; Scrapes the prospect's primary domain and extracts the core value proposition.&lt;/li&gt;
&lt;li&gt;  &lt;strong&gt;SearchAgent:&lt;/strong&gt; Hits the web for recent news, funding announcements, or executive moves to find a "trigger event."&lt;/li&gt;
&lt;li&gt;  &lt;strong&gt;CodeAgent:&lt;/strong&gt; Handles unstructured data to infer the exact industry vertical.&lt;/li&gt;
&lt;li&gt;  &lt;strong&gt;SalesOrchestratorAgent:&lt;/strong&gt; Takes the JSON payload from the first three agents and uses a strict system prompt to draft a highly constrained, 3-sentence pitch.&lt;/li&gt;
&lt;/ul&gt;

&lt;h3&gt;
  
  
  The Result
&lt;/h3&gt;

&lt;p&gt;The system completes an end-to-end run in about 11.4 seconds.&lt;br&gt;
&lt;/p&gt;

&lt;div class="highlight js-code-highlight"&gt;
&lt;pre class="highlight plaintext"&gt;&lt;code&gt;┌───────────────────────────┐
│ 4-Agent Orchestrator      │
│ Free Tier OpenRouter Mode │
└───────────────────────────┘
Type 'exit' to quit.

Enter Target Company URL (e.g., https://example.com): https://anthropic.com
 Initializing research loop...
  &amp;gt;  Fetching https://anthropic.com...
  &amp;gt;  Searching web for: Anthropic recent news funding 2024 2025...
  &amp;gt;  Inferring industry vertical...
  &amp;gt;  Drafting pitch... done
&lt;/code&gt;&lt;/pre&gt;

&lt;/div&gt;



&lt;p&gt;The orchestrator pattern is highly transferable. The exact same shape works for inbound lead triage or support escalations. &lt;/p&gt;

&lt;p&gt;I've open-sourced the base architecture so you can run it locally for free. Check out the repository here: &lt;a href="https://github.com/osamatech786/AI-Sales-Agent" rel="noopener noreferrer"&gt;https://github.com/osamatech786/AI-Sales-Agent&lt;/a&gt;. &lt;/p&gt;

&lt;p&gt;If you want to see how I scale this for production with pgvector and custom knowledge bases, I break down my full enterprise stack on my portfolio: &lt;a href="https://osamatech786.github.io" rel="noopener noreferrer"&gt;https://osamatech786.github.io&lt;/a&gt;.&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;Let's Connect:&lt;/strong&gt;&lt;/p&gt;

&lt;ul&gt;
&lt;li&gt;  &lt;strong&gt;LinkedIn:&lt;/strong&gt; &lt;a href="https://www.linkedin.com/in/osamatech786" rel="noopener noreferrer"&gt;Connect with me on LinkedIn&lt;/a&gt;
&lt;/li&gt;
&lt;li&gt;  &lt;strong&gt;Email:&lt;/strong&gt; &lt;a href="mailto:osamatech786@gmail.com"&gt;osamatech786@gmail.com&lt;/a&gt;
&lt;/li&gt;
&lt;/ul&gt;

&lt;p&gt;Let me know in the comments if you have questions about the implementation!&lt;br&gt;
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