Real-time lead enrichment in Slack with Extruct AI in-thread reply

Name: Real-time lead enrichment in Slack with Extruct AI in-thread reply
Availability: InStock
Rating: 4.5 (17 reviews)
Author: Extruct AI

$20/month : Unlimited workflows

2500 executions/month

Try free

THE #1 IN WEB SCRAPING

Scrape any website without limits

Try free

HOSTINGER 🎉 Early Black Friday Deal
DISCOUNT 20%

Self-hosted n8n

Unlimited workflows - from $4.99/mo

Try free

#1 hub for scraping, AI & automation

6000+ actors - $5 credits/mo

Try free

Automatic lead enrichment in Slack: monitors your Slack channel for new lead emails posted there, extracts each company’s name or domain, sends it to the Extruct API for data enrichment, then posts back a structured Slack card with company name, website, LinkedIn profile, number of employees, industry, recent news, and key contacts.

Who’s it for: Sales teams, SDRs, and marketing ops who capture new lead information in Slack and want instant enrichment without leaving the channel.

How it works: When a lead email is posted into your designated Slack channel, the workflow:

Monitors for any new message containing a company name or domain.
Extracts that company identifier.
Sends it to Extruct API for research.
Waits for enrichment to complete.
Posts back into the same Slack thread a formatted card with:
- Company name
- Website
- LinkedIn profile
- Number of employees
- Industry
- Recent news
- Key contacts

How to set up:

Sign up for Extruct AI
Copy the Extruct table ID
Create & install your Slack app
Configure n8n credentials & channel
Activate & use

Requirements:

Extruct account & API token
Extruct table template
Slack workspace with permission to install apps

Extruct AI

0 workflows

Nodes

set gmail telegram agent google-gemini

Complexity

advanced

Published 12 Jul 2025

Likes 0

View on n8n.io Download Workflow

✨

Share Your Workflow

Have a great workflow to share? Join the n8n Creator Hub and help the community!

Submit Your Template How to Submit

Related Workflows

Capture and schedule HVAC leads with OpenAI, Google Sheets, Slack and SMS

## Who this workflow is for Door-to-door HVAC companies seeking automated lead capture and appointment scheduling. ## What this workflow does AI classifies incoming leads, routes them by service type, logs lead info in Google Sheets, notifies team via Slack, sends confirmations, schedules appointments, and optionally sends SMS reminders. ## How the workflow works 1. Lead submission triggers workflow 2. AI classifies lead 3. Route lead based on service type 4. Log in Google Sheets 5. Notify team via Slack 6. Send confirmation email 7. Schedule appointment in calendar 8. Send SMS reminder (optional) 9. Optional CRM/dispatch integration **Author:** Hyrum Hurst, AI Automation Engineer **Company:** QuarterSmart **Contact:** [email protected]

View

Sync and enrich HubSpot leads from Google Sheets and Telegram with Gemini and Lusha

This workflow automates lead ingestion from Google Sheets and Telegram, leveraging Gemini AI and Lusha for intelligent matching and deep data enrichment. By normalizing incoming data into a standard structure, it uses custom fuzzy logic to identify existing HubSpot records—preventing duplicates and ensuring your CRM stays clean with validated contact and company details. **Key Features:** **Agnostic Intake:** Seamlessly processes leads from structured Google Sheets or raw Telegram messages parsed by Gemini AI. **Intelligent Matching:** Custom JS engine performs two-tier matching (hard & fuzzy) to save Lusha credits and keep CRM data integrity. **Deep Enrichment:** Automatically triggers Lusha API to find missing emails and update firmographic data like revenue and industry. **Automated Sync:** Closes the loop by notifying the team on Telegram and updating the spreadsheet status once a lead is processed. **Setup Instructions:** 1. Connect your HubSpot, Lusha, Gemini, Google Sheets, and Telegram credentials. 2. Input your Spreadsheet ID in the 'Trigger' and 'Acknowledge' nodes. 3. Adjust the similarity threshold in the 'Switch Logic' node (default 80) based on your data needs.

View

Qualify and email literary agents with GPT‑4.1, Gmail and Google Sheets

## Inspiration & Notes This workflow was born out of a very real problem. While writing a book, I found the process of discovering suitable literary agents and managing outreach to be manual, and surprisingly difficult to scale. Researching agents, checking submission rules, personalizing emails, tracking submissions, and staying organized quickly became a full-time job on its own. So instead of doing it manually, I automated it. I built this entire workflow in **3 days** — and the goal of publishing it is to show that you can do the same. With the right structure and intent, complex sales and marketing workflows don’t have to take months to build. --- ## Contact & Collaboration If you have questions, business inquiries, or would like help setting up automation workflows, feel free to reach out: 📩 **[email protected]** I genuinely enjoy designing workflows and automation systems, especially when they support meaningful projects. I work primarily from interest and impact rather than purely financial motivation. Whether I take on a project for **FREE** or paid for the following reasons: - I **LOVE** setting up workflows and automation. - I work for **meaningfulness**, not for money. - **I may do the work for free**, depending on how meaningful the project is. If the problem statement matters, the motivation follows. - **It also depends on the value I bring to the table** -- If I can contribute significant value through system design, I’m more inclined to get involved. If you’re building something thoughtful and need help automating it, I’m always happy to have a conversation. Enjoy~! --- # 0. Overview Automates the end-to-end literary agent outreach pipeline, from data ingestion and eligibility filtering to deep agent research, personalized email generation, submission tracking, and analytics. ## Architecture The system is organized into four logical domains: The system is modular and is divided into four domains: --> Data Engineering --> Marketing & Research --> Sales (Outreach) --> Data Analysis Each domain operates independently and passes structured data downstream. --- ## 1. Data Engineering **Purpose:** Ingest and normalize agent data from multiple sources into a single source of truth. **Inputs** - Google BigQuery - Azure Blob Storage - AWS S3 - Google Sheets - (Optional) HTTP sources **Key Steps** - Scheduled ingestion trigger - Merge and normalize heterogeneous data formats (CSV, tables) - Deduplication and validation - AI-assisted enrichment for missing metadata - Append-only writes to a central Google Sheet **Output** - Clean, normalized agent records ready for eligibility evaluation --- ## 2. Marketing & Research **Purpose:** Decide *who* to contact and *how* to personalize outreach. ### Eligibility Evaluation An AI agent evaluates each record against strict rules: - Email submissions enabled - Not QueryTracker-only or QueryManager-only - Genre fit (e.g. Memoir, Spiritual, Self-help, Psychology, Relationships, Family) **Outputs** - `send_email` (boolean) - `reason` (auditable explanation) ### Deep Research For eligible agents only: - Public research from agency sites, interviews, Manuscript Wish List, and LinkedIn (if public) - Extracts: - Professional background - Editorial interests - Genres represented - Notable clients/books (if publicly listed) - Public statements - Source-backed personalization angles **Strict Rule:** All claims must be explicitly cited; no inference or hallucination is allowed. --- ## 3. Sales (Outreach) **Purpose:** Execute personalized email outreach and maintain clean submission tracking. **Steps** - AI generates agent-specific email copy - Copy is normalized for tone and clarity - Email is sent (e.g. Gmail) - Submission metadata is logged: - `Submission Completed` - `Submission Timestamp` - Channel used **Result** - Consistent, traceable outreach with CRM-style hygiene --- ## 4. Data Analysis **Purpose:** Measure pipeline health and outreach effectiveness. **Features** - Append-only decision and submission logs - QuickChart visualizations for fast validation (e.g. TRUE vs FALSE completion rates) - Optional integration with: - Power BI - Google Analytics 4 **Supports** - Completion rate analysis - Funnel tracking - Source/platform performance - Decision auditing --- ## Design Principles - **Separation of concerns** (ingestion ≠ decision ≠ outreach ≠ analytics) - **AI with hard guardrails** (strict schemas, source-only facts) - **Append-only logging** (analytics-safe, debuggable) - **Modular & extensible** (plug-and-play data sources) - **Human-readable + machine-usable outputs** --- ## Constraints & Notes - Only public, professional information is used - No private or speculative data - HTTP scraping avoided unless necessary - Power BI Embedded is not required - Workflow designed and implemented end-to-end in ~3 days --- ## Use Cases ### Marketing - Audience discovery - Agent segmentation - Personalization at scale - Campaign readiness - Funnel automation ### Sales - Lead qualification - Deduplication - Outreach execution - Status tracking - Pipeline hygiene --- ## Tech Stack - **Automation:** n8n - **AI:** OpenAI (GPT) - **Scripting:** JavaScript - **Data Stores:** Google Sheets - **Email:** Gmail - **Visualization:** QuickChart - **BI (optional):** Power BI, Google Analytics 4 - **Cloud Sources:** AWS S3, Azure Blob, BigQuery --- ## Status This workflow is production-ready, modular, and designed for extension into other sales or marketing domains beyond literary outreach. ---

View

👨‍💻

Need Custom Automation?

N8N Automation Expert

Specialized in N8N automation, I design custom workflows that connect your tools and automate your processes.