AI-Powered Customer Support Email Automation

I'm looking for an AI solution to automate our emails responses. The AI will need to manage follow-up emails, enquiries, and other customer support-related emails.
I am based in Singapore & wish to have a call to understand how you can assist us.

Problem: Email volume and manual handling is limiting
growth and wasting team capacity
1. Manual, repetitive email work is consuming your team’s time
Your team is spending significant time categorizing, reading, and responding to emails.
Much of this effort could be redirected to higher-value tasks like client engagement,
relationship building, and advisory work.
2. Inconsistency in responses and long turnaround times
Without automation, responses vary between team members and are often delayed. This
inconsistency risks your reputation and may result in missed expectations or
opportunities.
3. Growing workload without scalable processes
As your client base grows and email volume increases, your current way of working will
not scale without adding unnecessary headcount.
4. Missed potential in reusing past knowledge
You have a rich history of replies and documents, but currently lack a system that learns
from and reuses that data to improve response quality and speed.
5. Opportunity to evolve into a product
What you’re building has long-term SaaS potential, either as an internal platform or
white-labelled solution. Starting smart now sets the stage for that evolution.

Proposal: AI-Powered Email Automation
The proposed solution to the above challenges is structured and phased to ensure your business
gets real, immediate results, while laying a strong foundation for future expansion.
1. n8n-Based Automation Layer (AWS-hosted)
We will build and deploy a cloud-hosted n8n environment on AWS that orchestrates the
entire automation pipeline: reading emails, categorizing them, and generating appropriate responses
2. Q&A-Based Categorization and Response Generation
We’ll fine-tune an OpenAI LLM using your internal Q&A dataset and historic email
content. The AI will:
o Categorize incoming emails
o Generate contextual, professional replies (for review to start)
o Automatically reply (once confidence is high)
3. Document-Based Retrieval System (RAG)
We will configure an internal document repository (e.g., Airtable, Supabase, or any
solution already in place) to allow the AI to pull relevant context (e.g., certificates,
invoice formats, attendance lists) and embed this information into the response.
o Example: If a customer requests a certificate or invoice, the system can
automatically fetch the file from storage and send it in the reply.
4. Multi-Stage Automation
o Stage 1: Basic reply automation for predictable questions like course dates,
availability, pricing.
o Stage 2: More complex replies involving document lookups and multi-turn
follow-up.
5. Workflow Expansion Ready
While out of this scope for now, we’re laying the groundwork for future workflows in
email marketing, lead nurturing, and possible SaaS development.

Scope of Work
To create an automated system that fulfills the following:
1. HostGator email integration with n8n
2. Deployment of n8n automation system on AWS
3. Q&A dataset ingestion for email categorization and reply generation
4. Database and document archive setup, connected to a vector database (Qdrant or similar)
for RAG
5. Implementation of automated reply generation for at least 3 categories (e.g., course
enquiries, certificates, pricing)
6. Workflow expansion support for more complex inquiries with internal file access (e.g.,
invoices, course certificates, etc.)
7. Configuration of system for future marketing/email automation scaling
8. Basic UI or access management layer (if required)
9. Documentation and walkthrough of setup