Generate LinkedIn Leads with Devi AI & n8n

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In today's fast-paced business world, efficient lead generation can determine whether your company thrives or struggles to keep up. For many decision-makers and business owners, LinkedIn remains a goldmine of potential clients - but manually identifying high-quality leads can be tedious, time-consuming, and prone to missed opportunities. This is where advanced AI-driven solutions like Devi AI and workflow automation tools such as n8n come into play.

This article breaks down how to create a LinkedIn lead-generation machine using Devi AI for intent-based lead discovery and n8n for automating the flow of enriched data. We'll explore how this system eliminates redundancy, improves accuracy, and saves valuable time for businesses. Whether you’re a marketing manager or a tech-savvy entrepreneur, this guide provides actionable insights into integrating these tools seamlessly.

Introduction to the Workflow: From Intent to Enrichment

Traditional approaches to LinkedIn lead generation often rely on scraping random data or starting with vague search parameters - methods that might yield quantity but lack quality. By contrast, the workflow discussed here focuses on intent-based discovery of potential leads and their subsequent enrichment with detailed information. This approach ensures you're targeting individuals who are genuinely interested in services like yours.

At the heart of this setup are three core components:

Devi AI for identifying LinkedIn users with purchase intent based on specific keywords.
n8n, a workflow automation tool, to process and structure this data.
Bright Data, an enrichment API, to gather in-depth information about each lead.

In the following sections, we'll dive into the process step-by-step, from setting up the tools to automating lead enrichment and outreach preparation.

Step 1: Capturing High-Quality Leads with Devi AI

Devi AI

Understanding Devi AI’s Intent-Based Model

Devi AI revolutionizes lead generation by monitoring social networks for buying intent signals based on user-specified keywords. This means that instead of cold leads, your list comprises LinkedIn professionals actively seeking solutions in your domain. For example, keywords like "AI automation", "workflow optimization", or "manual operations" could flag posts or profiles of individuals interested in your services.

Setting Up Devi AI and Configuring Webhooks

To begin, configure Devi AI by specifying the keywords relevant to your business. Once these criteria are set, leads can be automatically sent to your workflow using webhooks. A webhook acts as a communication bridge between Devi AI and n8n, allowing real-time data transfer.

Setup Summary:
- Navigate to Devi AI's webhook settings.
- Select LinkedIn as your source for leads (deselect any other platforms if unnecessary).
- Configure the webhook to send data directly to n8n for further processing.

This initial step ensures a steady flow of intent-driven LinkedIn leads into your automation pipeline.

Step 2: Automating Data Handling with n8n

n8n

Structuring the Workflow in n8n

Once the LinkedIn leads are captured, n8n takes over to organize and process the data systematically. The workflow starts by receiving raw lead data via the webhook and then splits the information into individual records using n8n's Split Out Node. This ensures each lead is ready for subsequent processing.

Storing Lead Data in a Google Sheet

Google Sheet

To maintain an organized database, the leads are stored in a Google Sheet with the following information:

URL of the LinkedIn profile.
Snapshot ID (if available).
Buying intent score (calculated later).
Flags for "Needs Outreach" and "Needs Enrichment."

These flags act as indicators for the next steps:

Leads flagged for "needs enrichment" proceed to additional data gathering.
Outreach activities are delayed until all necessary data points are collected.

Filtering Leads by Buying Intent

Not all leads are equal. A critical part of this workflow is filtering out profiles with low buying intent. To achieve this, the workflow integrates a basic large language model (LLM), which evaluates LinkedIn posts and assigns a buying intent score from 1 to 10. Business owners can adjust the threshold, for instance, targeting only those with a score of 7 or higher for outreach.

This filtering mechanism ensures your team focuses on the most promising leads, saving time and maximizing conversion potential.

Step 3: Enriching Leads with Bright Data

Bright Data

Bright Data API: Unlocking Comprehensive Lead Information

The next step is enriching the leads using Bright Data’s API. This tool provides a treasure trove of additional details about LinkedIn profiles, such as:

Name, location, and company.
Job title and employment history.
Recent posts and interaction activity.

Bright Data helps you move beyond surface-level information to gain insights into a lead’s professional background, current interests, and even personality traits based on recent activity.

Handling Real-Time Data Retrieval

Bright Data often scrapes information in real time, but there are instances when it requires additional processing time. In such cases, the system assigns a snapshot ID to the lead, which can later be used to retrieve the enriched data once available.

Key steps include:

Filtering rows marked as "Needs Enrichment."
Passing LinkedIn profile URLs to Bright Data for scraping.
Handling cases where Bright Data returns a snapshot ID instead of immediate results.
Updating the Google Sheet with enriched data once the snapshot is processed.

Leveraging Enriched Data for Outreach Preparation

Once the data is enriched, the system compiles it into a structured format in the Google Sheet. This includes:

Latest posts and their content.
Links to posts the lead has interacted with (liked, commented on, or shared).
Other insights, such as the lead’s tone and engagement patterns, which can be analyzed further using AI for more personalized outreach strategies.

Key Takeaways

Intent-Based Targeting: Devi AI identifies LinkedIn leads who are actively seeking services like yours, reducing wasted effort on unqualified prospects.
Automated Workflow: n8n streamlines the handling of lead data, from receiving raw information to filtering and organizing it in a Google Sheet.
Buying Intent Scoring: Using AI to score leads ensures you focus on prospects with the highest likelihood of conversion.
Comprehensive Enrichment: Bright Data’s API provides detailed lead insights, enabling more tailored and effective outreach.
Error Handling: Mechanisms like snapshot IDs ensure the workflow handles delays or incomplete data without interruptions.
Scalability: With minimal manual intervention, this system can be scaled to handle large volumes of leads efficiently.

Conclusion: Transform Your Lead Generation Process with Intelligent Automation

Integrating tools like Devi AI and n8n into your lead generation strategy can revolutionize how your business identifies and connects with potential clients on LinkedIn. By leveraging intent-based search, automation, and enriched data, you’ll not only save time but significantly improve the quality and ROI of your outreach campaigns.

This workflow isn’t just about technology - it’s about empowering businesses to focus on what matters most: building meaningful, high-value relationships with the right clients. Take steps to evaluate your current processes and consider how modern automation tools can elevate your lead generation efforts. With the right strategy, the possibilities are limitless.

Source: "How to Get Buying-Intent LinkedIn Leads with Devi AI & Enrich with n8n (BrightData API Outreach)" - Valerian Valkin | 2V Automation AI, YouTube, Jul 15, 2025 - https://www.youtube.com/watch?v=R3vBvp_boyQ

Use: Embedded for reference. Brief quotes used for commentary/review.