Automate Your Customer Support with Slack, AI, and Flask

Introduction

Slack is where internal support happens—so why not automate it? In this guide, you'll learn how to build a customer support assistant using Flask, OpenAI, and Slack's Events API. You'll also see how to train it on your company's knowledge base and escalate unresolved issues.

System Overview

Slack app receives `app_mention` events
Flask backend processes the message and context
OpenAI generates a reply or recommends escalation
Bot responds in the same thread with an answer or tag

Slack Bot Event Handler Setup

from slack_bolt import App
  from slack_bolt.adapter.flask import SlackRequestHandler
  import os
  
  app = App(token=os.environ['SLACK_BOT_TOKEN'], signing_secret=os.environ['SLACK_SIGNING_SECRET'])
  handler = SlackRequestHandler(app)
  
  @app.event("app_mention")
  def handle_mention(body, say):
      user = body['event']['user']
      text = body['event']['text']
      response = generate_ai_response(text)
      say(text=response)

Generating AI Replies with OpenAI

import openai
  openai.api_key = os.getenv("OPENAI_API_KEY")
  
  def generate_ai_response(query):
      messages = [
        {"role": "system", "content": "You are a helpful support bot. Answer questions based on internal knowledge."},
        {"role": "user", "content": query}
      ]
      response = openai.ChatCompletion.create(model="gpt-4", messages=messages)
      return response.choices[0].message['content']

Escalation Logic

You can program fallback behavior by checking for a confidence threshold or a keyword filter, then alert a human.

If AI response includes 'I'm not sure', tag @support
Log unresolved questions to Notion or Airtable
Add to a fine-tuning dataset for future improvement

Why This Saves Teams Time

Answers FAQs instantly, 24/7
Reduces load on human agents
Creates a log of all answered support queries
Improves over time via fine-tuning

Need a Custom Slack Bot?

Whether you need a private Slack assistant trained on internal docs or a customer-facing bot that speaks your product's language, I can help. Let's talk about building a smart, branded assistant for your team.