AI Bot / LINE Customer Service
Delegate 80% of repeat CS questions
LINE Official Account AI bots for shops, brands, education, SaaS teams — smart CS, order lookup, automated push, multi-turn conversation design, integrated with ChatGPT / Claude / Gemini and your knowledge base.
Interested in AI Bot / LINE Customer Service?
Drop your situation below. I'll reply within one business day with initial thoughts. Free, no hard sell.
- High CS volume, 80% repeat — let AI handle FAQ
- Subscription / member-style interactive services (virtual idol, AI coach, AI advisor)
- Existing CS system needs LINE integration as unified entry
- Product recommendation, order lookup, booking system as LINE Bot
- Internal team knowledge-base bot (Notion / Drive docs → queryable AI)
- 01/ LINE Messaging API webhook setup
- 02/ Conversation flow design (multi-turn memory, intent recognition)
- 03/ RAG knowledge base integration (PDF / Notion / Google Drive auto-ingest)
- 04/ AI model integration (GPT-4 / Claude / Gemini, budget-aware selection, cost forecast)
- 05/ Admin dashboard (conversation history, user tagging, reply editing)
- 06/ Rich Menu and Flex Message design
- 07/ LIFF integration (when web interaction is needed)
- 08/ Monitoring + cost control (monthly token tracking — avoid budget overruns)
- Designed a virtual-idol LINE Bot at AWS GenAI Hackathon with subscription monetization and personalized messaging
- Deep familiarity with LINE Messaging API, Webhook, Rich Menu, LIFF ecosystem
- RAG implementation experience — I can build a knowledge base from your internal docs
- Not just a 'bot that replies' — a system that reduces CS load and creates measurable business value
- Full cost forecast (OpenAI / Anthropic API monthly) — no post-launch budget surprises
- 14 days of post-launch tuning based on real conversation logs
LINE Messaging API, Webhook, Rich Menu, LIFF, OpenAI / Anthropic / Gemini API, RAG (vector DB)
NT$15,000–40,000
30-min discovery call → scope and pricing → phased delivery → launch handoff
The AWS GenAI Hackathon virtual-idol bot
At AWS GenAI Hackathon I designed a virtual-idol-themed LINE Bot — users could chat with a persona, and the AI responded per character setting, plus:
- Subscription monetization — free tier had message-count limits; paid subscription unlocked unlimited chat plus custom themes.
- Personalized push — based on past conversation context, the bot proactively sent personalized messages (not broadcast).
- Multimedia interaction — Rich Menu + Flex Message design provided a bespoke UI; LIFF for forms or settings flows.
The core wasn’t “will reply” — it was “will retain”. That’s where LINE Bot’s real business value lives.
RAG knowledge base — making it not hallucinate
A lot of LINE Bots wire ChatGPT directly and discover the AI starts making up product prices and specs — because GPT doesn’t know your products.
My approach: your PDF / Notion / Google Drive content runs through a RAG pipeline first (chunking → embedding → vector DB). When the AI answers, it retrieves relevant passages, passes those plus the user question to the LLM, and answers from grounded fact. Even when the AI isn’t sure, it says “I don’t have that info” instead of inventing a plausible-sounding wrong answer.
Cost control isn’t an afterthought
The most common post-launch disaster is “token budget blown by end-of-month”. I bake in before launch:
- Estimate monthly conversation volume based on your current LINE OA traffic.
- Calculate per-conversation token cost (input + output + RAG context).
- Set monthly budget alerts — 80% threshold fires a notification.
- Fallback logic: when budget is exceeded, auto-switch to a cheaper model or fall back to FAQ templates.
14 days of post-launch tuning
Not a “warranty period” — the first two weeks of real conversations reveal edge cases you couldn’t anticipate during design. I review actual logs, find where the AI replies poorly, and adjust prompts or expand the RAG corpus.
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