Add business-benefit section + hire CTA to DigiKedai post (EN+ZH)
Deploy / build (push) Successful in 22s

This commit is contained in:
2026-09-06 07:47:25 +08:00
parent 184395695f
commit e5ec418b9f
2 changed files with 55 additions and 0 deletions
@@ -16,6 +16,27 @@ and can even hand out free-trial accounts without a human in the loop.
This is the story of how it went together — the architecture, the LLM wiring,
and the bugs that ate an afternoon each.
## Why a business needs a bot like this
Before the architecture, the *why*. A support bot isn't a gimmick — it changes
the economics of a small business:
- **Saves money on staff.** Every routine question a bot answers is one your
team doesn't have to. Digi Kedai gets the equivalent of a round-the-clock
support agent for a fraction of the cost of hiring one.
- **Answers instantly, 24/7.** Customers ask at midnight and on weekends. A bot
replies in seconds, in their language — no queues, no "we'll get back to you".
- **Converts browsers into buyers.** The bot doesn't just answer — it *upsells*.
A "does this have a free trial?" question turns into a claimed trial account
in a couple of taps, with no human in the loop.
- **Never forgets a customer.** Long-term memory means repeat customers are
greeted like regulars, not strangers.
- **Scales with your catalogue.** Add a product and the bot already knows it —
no retraining, no new FAQ pages.
For a one-person business like Digi Kedai, that's the difference between losing
sales at 2 a.m. and closing them.
## The stack
- **TypeScript + Node 20** running as a single container on my Synology NAS.
@@ -159,3 +180,15 @@ If you're building your own Telegram bot backed by an LLM, the lesson is the
boring one: the model is the easy part. The webhook lifecycle, the payload
contract, and the idempotency of your provisioning are where it actually breaks —
design those first.
---
## Want a bot like this for your business?
I build custom Telegram/WhatsApp AI bots, websites, and self-hosted
infrastructure for businesses. If a bot like this could save you time and
money — or you'd like to hire me — I'd love to talk:
- 📱 **WhatsApp:** [+60 12-797 2969](https://wa.me/60127972969)
- 📧 **Email:** [[email protected]](mailto:[email protected])
- 🌐 **Website:** [hoelee.com](https://hoelee.com)
@@ -10,6 +10,18 @@ Digi Kedai 销售数字产品——在线课程、电子书、模板——每一
这篇讲的是它是怎么搭起来的——架构、LLM 接线,以及那些各自吃掉我一整个下午的 bug。
## 为什么企业需要一个这样的机器人
讲架构之前,先说*为什么*。客服机器人不是噱头——它改变了小生意的经济学:
- **省钱省人力。** 机器人每回答一个常规问题,你的团队就少答一个。Digi Kedai 用雇一个客服几分之一的成本,就得到了一个全天候的客服专员。
- **全天候即时响应。** 顾客会在半夜和周末提问。机器人几秒钟内用他们的语言回复——没有排队,没有「我们稍后回复」。
- **把浏览者变成买家。** 机器人不只是回答——它还会*向上销售*。一句「有免费试用吗?」几下点击就变成一个已领取的试用账号,全程无需人工。
- **永远记得顾客。** 长期记忆让回头客被当作熟客问候,而不是陌生人。
- **随商品目录扩展。** 加一个商品,机器人就已经认识它了——无需重新训练,无需新的 FAQ 页面。
对 Digi Kedai 这样一个人的生意来说,这就是在凌晨两点丢单和成交之间的差别。
## 技术栈
- **TypeScript + Node 20**,作为单个容器跑在我的 Synology NAS 上。
@@ -88,3 +100,13 @@ LLM 擅长开放式问题,却很不擅长*状态*。所以那些需要可靠
[git.hoelee.com/hoelee/digikedai-bot](https://git.hoelee.com/hoelee/digikedai-bot)。
如果你也在打造一个 LLM 驱动的 Telegram 机器人,教训其实很朴素:模型是最容易的部分。webhook 生命周期、payload 契约、以及开通流程的幂等性才是真正会出问题的地方——先设计好这些。
---
## 想为你的生意做一个这样的机器人吗?
我为企业定制 Telegram/WhatsApp AI 机器人、网站,以及自托管基础设施。如果一个这样的机器人能为你省时省钱——或者你想雇佣我——我非常乐意交流:
- 📱 **WhatsApp** [+60 12-797 2969](https://wa.me/60127972969)
- 📧 **邮箱:** [[email protected]](mailto:[email protected])
- 🌐 **网站:** [hoelee.com](https://hoelee.com)