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nstallers lose jobs because enquiries sit unanswered for days. I built a system that captures every lead and makes sure someone acts on it.
Leads from website forms, trade-show forms and voice notes, all in one Postgres database
Each lead pops up on Telegram as a card with status buttons (called, quote sent, won, lost)
Automatic follow-up emails, an AI step that reads customer replies, a morning summary of who to call
Duplicate detection, nightly backups, self-hosted on my own server (n8n, Docker, Caddy)
Video walkthrough and details: cautomations.com
leads popping up on telegram as cards with status buttons is a really nice way to do it. how are you finding the installers who need this
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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
TITAN Nexus — Enterprise AI Automation Platform
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Our Mission
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Built by Shubham Tripathi
TITAN Nexus — Smarter Workflows. Greater Control. Intelligent Automation.
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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?