Lead Enrichment AI Agent with Browser Automation

What This Agent Does

This intelligent lead enrichment workflow transforms basic contact information into comprehensive, qualified lead profiles automatically. When a new lead is submitted through a form, the agent springs into action: it searches LinkedIn to gather detailed company information, uses AI to qualify the lead based on your criteria, formats all the enriched data, logs it to Google Sheets for your records, and sends smart notifications to Slack—with special alerts for hot leads that need immediate attention.

Key benefits: Save 15-20 minutes per lead on manual research and data entry, ensure consistent lead qualification criteria across your team, never miss a high-priority opportunity with instant hot lead alerts, and build a rich database of qualified prospects automatically. This workflow eliminates the tedious copy-paste work that slows down sales teams and lets your reps focus on what they do best—closing deals.

Perfect for: Sales teams processing inbound leads, marketing teams qualifying campaign responses, business development professionals researching prospects, and any organization that needs to enrich and prioritize leads at scale.

Who Is It For

This workflow is designed for sales and marketing professionals who receive leads through forms, landing pages, or CRM systems and need to quickly assess their quality and potential. It's particularly valuable for:

• Sales Development Representatives (SDRs) who need to prioritize which leads to contact first based on company size, industry, and fit
• Marketing teams running campaigns who want to automatically segment and qualify incoming leads without manual research
• Business development managers who need comprehensive company intelligence before reaching out to prospects
• Small business owners who wear multiple hats and can't afford to spend hours researching every potential customer
• Revenue operations teams building scalable lead management processes that maintain data quality

If you're currently spending significant time manually looking up companies on LinkedIn, copying information into spreadsheets, and deciding which leads deserve immediate attention, this workflow will transform your process.

Required Integrations

Browser Automation

Why it's needed: This integration powers the LinkedIn company research by controlling a real browser to search for and extract company information automatically, just like a human would but much faster.

Setup steps:

1. Navigate to the Integrations section in your TaskAGI dashboard
2. Search for "Browser Automation" and click Connect
3. The browser automation service is typically built into TaskAGI, so no external API key is required
4. Verify the connection status shows as Active
5. Ensure your TaskAGI plan includes browser automation credits (check your usage limits in account settings)

Configuration in TaskAGI: Once connected, the browser automation nodes will automatically use this integration. You may want to configure timeout settings (recommended: 30 seconds) and whether to run browsers in headless mode (recommended: enabled for faster execution).

OpenAI

Why it's needed: The AI Lead Qualification node uses OpenAI's GPT-4o model to intelligently analyze lead information and make qualification decisions based on your specific criteria, providing consistent and nuanced lead scoring.

Setup steps:

1. Create an OpenAI account at https://platform.openai.com if you don't have one
2. Navigate to API Keys in your OpenAI dashboard
3. Click Create new secret key and give it a descriptive name like "TaskAGI Lead Enrichment"
4. Copy the API key immediately (it won't be shown again)
5. In TaskAGI, go to Integrations → OpenAI → Connect
6. Paste your API key in the provided field
7. Click Test Connection to verify it works
8. Save the integration

Important: OpenAI charges per token used. GPT-4o costs approximately $0.005 per lead qualification. Monitor your usage in the OpenAI dashboard and set up billing alerts.

Google Sheets

Why it's needed: This integration logs all enriched lead data to a centralized spreadsheet, creating a searchable database of qualified leads with complete company information that your entire team can access.

Setup steps:

1. Go to Integrations → Google Sheets in TaskAGI
2. Click Connect with Google
3. Select the Google account that has access to your lead tracking spreadsheet
4. Grant TaskAGI permission to read and write to your Google Sheets
5. Create a new Google Sheet or prepare an existing one with these column headers: Timestamp, Name, Email, Company, Title, Phone, Company Size, Industry, LinkedIn URL, Qualification Score, Qualification Reason, Status
6. Copy the full URL of your Google Sheet
7. You'll paste this URL in the workflow configuration later

Pro tip: Create a dedicated Google account or use a team account for this integration rather than a personal account to ensure continuity if team members leave.

Slack

Why it's needed: Slack notifications ensure your team is immediately alerted when leads are enriched, with special high-priority alerts for hot leads that meet your qualification criteria, enabling rapid response times.

Setup steps:

1. In your Slack workspace, create a dedicated channel for lead notifications (e.g., #new-leads)
2. Create another channel for hot leads (e.g., #hot-leads-urgent)
3. In TaskAGI, navigate to Integrations → Slack → Connect
4. Click Connect to Slack and authorize TaskAGI to access your workspace
5. Select which channels TaskAGI can post to (include both channels you created)
6. Complete the authorization process
7. Test by sending a test message to verify the connection

Channel setup recommendation: Set different notification preferences for each channel—standard notifications for #new-leads and @channel or @here mentions for #hot-leads-urgent to ensure immediate visibility.

Configuration Steps

Step 1: Configure the Lead Input Form (Trigger)

This form node captures the initial lead information that kicks off the entire workflow.

1. Click on the Lead Input Form node
2. Configure the form fields to collect:
   • Name (text field, required)
   • Email (email field, required)
   • Company (text field, required)
   • Title (text field, optional)
   • Phone (text field, optional)
3. Customize the form title: "New Lead Submission"
4. Add a success message: "Thank you! We're processing your information and will be in touch soon."
5. Copy the form URL provided—this is what you'll embed on your website or share with lead sources

Pro tip: Enable form validation to ensure email addresses are properly formatted and required fields aren't empty.

Step 2: Set Up Browser AI LinkedIn Scraping

This node performs the intelligent company research on LinkedIn.

1. Select the Browser AI: Scrape LinkedIn Company node
2. In the Prompt field, verify it reads: Search for "[[nodes.3571.company]] LinkedIn company page" and extract: company name, employee count, industry, description, and LinkedIn URL
3. Configure these settings:
   • Timeout: 30 seconds
   • Wait for page load: true
   • Screenshot on completion: false (unless you want visual records)
4. The node automatically references [[nodes.3571.company]] which pulls the company name from your form submission

Important: This node creates a browser session that must be properly closed to avoid consuming unnecessary resources.

Step 3: Configure End Browser Session

This cleanup node ensures browser resources are released.

1. Click the End Browser Session node
2. Verify the Session ID field contains: [[nodes.3572.sessionId]]
3. No other configuration needed—this node simply closes the browser opened in the previous step

Step 4: Set Up Parse Company Data

This node structures the raw data scraped from LinkedIn into usable fields.

1. Select the Parse Company Data node
2. Configure the parsing rules to extract:
   • company_name: Extract company name
   • employee_count: Extract number of employees
   • industry: Extract industry/sector
   • description: Extract company description
   • linkedin_url: Extract LinkedIn profile URL
3. Set the Input data field to: [[nodes.3573.sessionId]]
4. Enable Strict parsing: false (to handle variations in LinkedIn page structures)

Step 5: Configure AI Lead Qualification

This is where the intelligent qualification happens using GPT-4o.

1. Click the AI Lead Qualification node
2. Verify the Model is set to: gpt-4o
3. Review and customize the Prompt:

Qualify this lead:

Contact:
- Name: [[nodes.3571.name]]
- Email: [[nodes.3571.email]]
- Title: [[nodes.3571.title]]
- Phone: [[nodes.3571.phone]]

Company:
- Name: [[nodes.3574.company_name]]
- Size: [[nodes.3574.employee_count]]
- Industry: [[nodes.3574.industry]]
- Description: [[nodes.3574.description]]

Provide:
1. Qualification score (1-10)
2. Brief reason for score
3. Recommended action (Hot Lead, Warm Lead, or Cold Lead)

Format as JSON: {"score": X, "reason": "...", "status": "..."}

4. Set Temperature: 0.3 (lower = more consistent scoring)
5. Set Max tokens: 200
6. Enable JSON mode: true for structured output

Customization tip: Modify the qualification criteria in the prompt to match your ideal customer profile. For example, add "Prioritize companies with 50-500 employees in the SaaS industry."

Step 6: Configure Format Enriched Lead

This node combines all gathered data into a clean, structured format.

1. Select the Format Enriched Lead node
2. Map the output fields:
   • timestamp: [[nodes.3571.submittedAt]]
   • name: [[nodes.3571.name]]
   • email: [[nodes.3571.email]]
   • company: [[nodes.3574.company_name]]
   • title: [[nodes.3571.title]]
   • phone: [[nodes.3571.phone]]
   • company_size: [[nodes.3574.employee_count]]
   • industry: [[nodes.3574.industry]]
   • linkedin_url: [[nodes.3574.linkedin_url]]
   • score: [[nodes.3575.content.score]]
   • qualification_reason: [[nodes.3575.content.reason]]
   • status: [[nodes.3575.content.status]]

Step 7: Configure Google Sheets Logging

This node records every enriched lead in your spreadsheet.

1. Click the Log to Google Sheets node
2. Paste your Google Sheet URL in the sheet_url field
3. Set Append to sheet: Sheet name (usually "Sheet1")
4. Map the data fields to match your spreadsheet columns using: [[nodes.3576._dynamic]]
5. Enable Create headers if missing: true (for first-time setup)

Step 8: Set Up the Hot Lead Condition

This decision node determines which Slack channel receives the notification.

1. Select the Hot Lead? node
2. Configure the condition:
   • Field to check: [[nodes.3575.content.status]]
   • Condition: equals
   • Value: Hot Lead
3. This creates two paths: true_path (hot leads) and false_path (all other leads)

Step 9: Configure Slack Hot Lead Alert

This sends urgent notifications for high-priority leads.

1. Click the Slack Hot Lead Alert node
2. Select your Channel: #hot-leads-urgent
3. Customize the message template:

🔥 **HOT LEAD ALERT** 🔥

**Contact:** [[nodes.3571.name]] ([[nodes.3571.title]])
**Company:** [[nodes.3574.company_name]] ([[nodes.3574.employee_count]] employees)
**Industry:** [[nodes.3574.industry]]
**Score:** [[nodes.3575.content.score]]/10

**Why it's hot:** [[nodes.3575.content.reason]]

**Contact info:**
📧 [[nodes.3571.email]]
📱 [[nodes.3571.phone]]
🔗 [[nodes.3574.linkedin_url]]

@channel - Someone should reach out ASAP!

4. Enable Link names: true (to activate @channel mentions)

Step 10: Configure Slack Lead Enriched Notification

This sends standard notifications for all enriched leads.

1. Select the Slack Lead Enriched node
2. Choose Channel: #new-leads
3. Set up the message:

✅ **New Lead Enriched**

**Contact:** [[nodes.3571.name]] - [[nodes.3571.title]]
**Company:** [[nodes.3574.company_name]]
**Status:** [[nodes.3575.content.status]] (Score: [[nodes.3575.content.score]]/10)

View full details in Google Sheets

Testing Your Agent

Running Your First Test

1. Click the Test Workflow button in the top-right corner of the workflow editor
2. Fill out the test form with sample data:
   • Name: "John Smith"
   • Email: "john.smith@example.com"
   • Company: "Salesforce"
   • Title: "VP of Sales"
   • Phone: "+1-555-0123"
3. Click Submit and watch the workflow execution in real-time

Verification Checklist

After the Browser AI node completes:

• ✅ Verify company data was successfully scraped (check the node output)
• ✅ Confirm the browser session shows a valid session ID
• ✅ Check that employee count, industry, and description are populated

After the AI Qualification node:

• ✅ Review the qualification score (should be 1-10)
• ✅ Read the qualification reason to ensure it makes sense
• ✅ Verify the status is one of: "Hot Lead", "Warm Lead", or "Cold Lead"

After the Google Sheets node:

• ✅ Open your Google Sheet and confirm a new row was added
• ✅ Verify all columns are populated correctly
• ✅ Check that the timestamp matches the submission time

After the Slack notifications:

• ✅ Check the appropriate Slack channel for the notification
• ✅ Verify all data fields display correctly (no "undefined" or error messages)
• ✅ Confirm hot leads go to the urgent channel and others to the standard channel

Expected Results

A successful execution should complete in 25-40 seconds and show all nodes with green checkmarks. You should see:

• One new row in your Google Sheet with complete lead information
• One Slack notification in the appropriate channel
• No error messages in any node outputs

Troubleshooting

"Browser timeout error" on LinkedIn Scraping

Cause: LinkedIn's page took too long to load or the search didn't find results quickly.

Solutions:

• Increase the timeout setting to 45 seconds
• Check that the company name is spelled correctly in your test
• Verify your TaskAGI account has available browser automation credits
• Try using the company's official name (e.g., "International Business Machines" instead of "IBM")

"OpenAI API error: Invalid API key"

Cause: The API key is incorrect, expired, or hasn't been properly saved.

Solutions:

• Go to Integrations → OpenAI and re-enter your API key
• Generate a new API key from OpenAI's platform
• Check that your OpenAI account has available credits
• Verify there are no extra spaces before or after the API key

"Google Sheets: Permission denied"

Cause: TaskAGI doesn't have write access to your spreadsheet.

Solutions:

• Re-authenticate the Google Sheets integration
• Ensure the Google account connected to TaskAGI owns the spreadsheet or has edit permissions
• Check that the sheet URL is correct and the sheet isn't deleted
• Make sure the sheet isn't protected with restricted editing permissions

"Slack message failed to send"

Cause: The Slack integration lost authorization or the channel doesn't exist.

Solutions:

• Reconnect the Slack integration in TaskAGI
• Verify the channel names are spelled correctly (including the # symbol)
• Check that the TaskAGI app is still installed in your Slack workspace
• Ensure the channels are public or TaskAGI has been invited to private channels

AI Qualification Returns Inconsistent Scores

**