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An autonomous “digital employee” that monitors Gmail, WhatsApp and file drops, reasons about each incoming task, and writes a step-by-step action plan.
Every plan goes to an Approval Center first, so a human approves or rejects it before anything happens. Once approved, the system executes the actions: creating invoices in Odoo ERP, posting to LinkedIn, Facebook, Instagram and X, sending emails, and generating CEO briefings.
Key features:
Gmail, WhatsApp and filesystem watchers
AI reasoning loop that creates action plans
Human-in-the-loop approval workflow
Odoo invoicing and social media posting via browser automation
Full audit logging of every action
Dashboard to monitor and run everything
Tech Stack: Python, MCP Servers, Playwright, Odoo ERP, and AI Agents.
The network for creativity
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I'm building MorningAI — an AI automation platform designed to help businesses save time and work smarter.
I'm deciding on the website's visual direction, and I'd love your opinion!
🅰️ Design A: Light, clean & professional
🅱️ Design B: Dark, futuristic & premium
Which design should I choose for MorningAI — A or B?
Drop your choice in the comments! 👇
4 voted
57%
3 voted
43%
7 votes
Closed
Most inbound bottlenecks aren't caused by low lead volume—they happen during triage.
When inquiries roll into a Google Sheet or CRM, operations teams often waste 10–15 minutes per submission reading through messy paragraphs, deciphering budget mismatch, and manually deciding who gets an immediate call vs. a standard rate sheet.
Instead of adding a bulky CRM add-on, I documented a lightweight 3-step automation pipeline built inside Make:
Intake & Extraction: An active listener triggers immediately upon a new submission, extracting core variables: client scope, target deliverables, timeline, and stated budget.
Context-Aware Evaluation (Gemini 2.5 Flash): The payload passes through an AI evaluation node with strict guardrails:
Evaluates budget against minimum agency criteria.
Assigns a triage score: Hot (immediate priority), Warm (nurture), or Cold (disqualified/template reply).
Generates a strict 15-word operational summary—no long paragraphs.
Determines an automated next step (e.g., routing to an account lead or flagging for asynchronous follow-up).
Data Return & Clean Pipeline: Appends the structured classification directly back to the master operational tracker, keeping the sheet filterable and clean.
The outcome: The sales and operations team can filter the entire board by priority status in two clicks, cutting first-touch response time to minutes without manually reading every single submission.
I’ve documented the full scenario map, execution logic, and data schemas below.
Curious how other agency operators and automation leads here handle their lead enrichment layer—are you doing AI scoring at the form level, or later in the CRM pipeline?:
For the budget gate, I'd keep an unstated budget separate from one explicitly below your minimum. Does the Make route ask for clarification when the amount or currency is missing, so a potentially suitable lead doesn't fall into Cold by default?
An automated n8n workflow that receives incoming leads via webhook, validates them, qualifies them with AI (Google Gemini), scores them, and syncs the result to Airtable without creating duplicates.
really optimized workflow