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Related posts
Really liked how these designs turned out!
Explored a concept for AI SaaS product, focusing on a clean interface and a simple, intuitive chat experience.
Tried two different layout variation for the hero section.
Which would you like?
13 voted
57%
10 voted
43%
23 votes
Closed
Really clean concept! 👏
I like the second layout more — the headline "Your ideas deserve an intelligent partner" + the chat preview below makes the AI feel real and easy to use immediately. The first one is also clean, but this one sells the product faster.
I also design SaaS...
AI for the masses, craft for the rich. What do you think about this? 👀
When anyone can generate “perfect” in seconds, the human touch becomes the distinctive thing.
Is AI becoming the look of mass market, while craft becomes the new luxury? 🤔
AI Customer Support Agent for Web Form, Gmail & WhatsApp
An AI support agent that answers customer questions across a web form, Gmail and WhatsApp, and hands off to a human team when it should. Load-tested with 200+ messages and no lost messages.
I built an AI customer support agent as a demo for a fictional SaaS company called Flowmint. Customers can write through a web form, Gmail or WhatsApp. The agent finds the answer in a knowledge base, replies on the same channel, and passes the conversation to a human team (Billing, Sales, Support) for refunds, special pricing, or when a customer asks for a person.
One agent for three channels, with replies formatted for each (a clean HTML email, a short WhatsApp message, a private web tracking page)
Safety rules written in code: it can only quote approved prices, and refunds always go to a human
Remembers returning customers on email and WhatsApp
Private ticket tracking page with a secret tracking code
If the AI service is busy, it switches to backup AI models, and to a knowledge-base answer if all are limited
I load-tested the agent for 24 hours with 200+ messages across all three channels, using simulated customers plus real emails and WhatsApp messages I sent myself.
212 messages in, 212 replies out, none lost
Only 3.3% needed a human
Areas I’m improving: faster replies with a paid AI plan, and spam protection for the web form.
Tech stack: Python, FastAPI, OpenAI Agents SDK, Kafka, PostgreSQL, Next.js, Docker, Gmail API, WhatsApp Cloud API.
Writing the safety rules in code, not in the prompt, is the part I like most: approved prices only, and refunds always go to a human. My RAG demo also passes the question to a person when the guide has no answer. How does your agent decide that a customer "asks for a person": a fixed list of phrases, or does the model decide?