[Notion Doc, Deck]

This workflow is an AI-assisted customer support automation built in n8n. It monitors incoming customer emails from Gmail, analyzes the message using AI, classifies the issue type, detects sentiment and priority, generates a professional draft response, logs the ticket in Google Sheets, and alerts the support team on Slack when urgent attention is required. 

[Notion Doc, Deck]

This workflow is an AI-assisted lead qualification automation built in n8n. It captures inbound leads from a Typeform submission, normalizes the form data, scores each lead using a combination of rule-based logic and AI analysis, classifies the lead as Hot, Warm, or Cold, stores the qualified lead in Airtable CRM, sends personalized follow-up emails, and notifies the sales team on Slack when a high-value lead is detected. 

The goal of this workflow is to automate the early-stage sales qualification process so that sales teams can prioritize the most promising leads faster, while still maintaining structured CRM records and personalized outreach. 

[Notion Doc, Deck]

The Credence Creator Search and Scoring Agent powers the discovery and ranking stage of the product. In the current prototype, the Credence frontend sends a campaign brief and a list of candidate creator profiles to an n8n webhook. The workflow then evaluates each creator against campaign requirements such as target audience, industry, geography, language, campaign objective, and preferred creator type. The present workflow ranks supplied creator candidates rather than independently querying LinkedIn or an external creator database; database-backed search is part of the broader product roadmap. 

[Notion Doc, Deck]

The Outreach Draft Agent automates the final stage of Credence’s brand-side creator discovery workflow. After a brand shortlists a creator, the Credence frontend sends the campaign brief and selected creator profile to an n8n webhook. The workflow then validates and standardizes fields such as the brand name, campaign objective, target audience, region, language, budget, collaboration format, creator expertise, audience profile, match rationale, and recommended use case. This allows the agent to handle slightly different request formats without breaking. 

[Notion Doc]

The Lumen Main Chat Response Agent is the backend chat workflow that powers Lumen’s core AI response experience.

It receives a chat request from the frontend, converts the user’s selected mode, memories, recent messages, and prompt-builder fields into a structured model prompt, sends the request to OpenRouter, and returns a normalized JSON response to the app.

This workflow is designed for Lumen’s positioning as an AI workspace. Instead of treating every chat as a plain message, the agent makes the response context-aware through modes, memory selection, prompt-builder metadata, and short-term conversation history.