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AI GO
By function

AI for IT Teams

A one-person IT function covers the network, the accounts, ten system integrations — and everyone’s direct messages. AI GO turns repeat requests into tickets and integrations into configuration, giving the time back to the work that matters.

With SLAs
internal requests become measurable
Low-code
integrations configured as flow diagrams
Starters
templates for internal and external apps

What you are probably dealing with

IT is the company’s inbox

Forgotten passwords, printer setup, access requests — all by direct message. Volume means things get missed, and there is no record proving how much you actually handled.

The integration queue never clears

Sales wants the CRM connected to the website, finance wants invoicing connected to the ERP, the plant wants machine data in a report. Each one has to be written and then maintained — impossible for one person.

Every project starts from zero

Each new internal tool means rewriting login, permissions and data access before you get anywhere near the business logic that actually has value.

Your output is invisible

Hundreds of fires put out over a year, and nothing concrete to point at in a review — because none of it was recorded. Arguing for headcount or budget has no evidence behind it.

Before and after

Before

  1. 1Internal requests arrive as direct messages
  2. 2Nothing recorded once resolved, so nothing measurable
  3. 3Integrations written case by case and self-maintained
  4. 4New tools rewritten from login and permissions up
  5. 5Output cannot be quantified, so resourcing is hard to argue

With AI GO

  1. 1Requests enter one queue with category and priority
  2. 2Resolution time and volume become visible data
  3. 3Integrations configured as flow nodes, not bespoke code
  4. 4New apps start from a template with the basics in place
  5. 5IT’s contribution is argued with numbers

Modules involved

The service desk makes requests measurable; automation and starter templates are how you get the time back.

通用 · IT 服務台

IT 服務台雙介面：員工前台線上報修與查進度，IT 後台以拖曳看板派工，並管理硬體資產、軟體授權、機房巡檢與廠商進出。全部資料落在 AI GO 既有的專案／人資／資產模組，不建自訂表。

Operations

通用 · AI GO 自訂管理監控中台

跨部門的營運管理中樞：直接接上 AI GO 既有的專案、任務、簽核、公告、人資、客戶與帳務資料，把管理專案、治理閘門、行動追蹤、簽核監控、資料品質稽核與系統維運集中在同一個工作台，全程零自建資料表。

Operations

內部整合起手式模板

為內部 (Internal) 企業工具設計的標準開發起手式模板。整合 UI 設計規範、側邊欄導覽、與 VFS 資料存取。

Starter

外部應用起手式模板

為外部對外 (External) 應用設計的標準開發起手式模板。包含預置的金流、身份驗證、與資料庫連線等核心架構。

Starter
Browse all modules

Platform capabilities

Internal requests become measurable

The IT service desk turns direct messages into tickets with a category, an owner and a deadline. How many, how long and which type dominates all become data.

Configuration instead of code

The Node-RED automation module expresses data flow between systems as a node graph, so most integration needs no longer mean writing and maintaining another program.

Starter templates end the rebuild

Internal tools begin from the internal starter (UI conventions, sidebar navigation, VFS data access); customer-facing apps begin from the external starter, with payments, authentication and database connectivity already wired.

Permissions and audit come with the platform

Who can see which data and who performed which action is a platform capability, not something every project reimplements.

Labour cost you can recover

For a 100-person company with a two-person IT team at an average loaded rate of NT$500/hour:

Handling repetitive internal requests

Accounts, permissions, device setup

Hours / month
44 hrs
Hourly rate
NT$ 450
Recovered / month
NT$ 19,800

Building and maintaining integrations

Hours / month
36 hrs
Hourly rate
NT$ 600
Recovered / month
NT$ 21,600

Rewriting boilerplate for internal tools

Hours / month
24 hrs
Hourly rate
NT$ 600
Recovered / month
NT$ 14,400

Tracking requests and reporting on them

Hours / month
12 hrs
Hourly rate
NT$ 450
Recovered / month
NT$ 5,400
TotalNT$ 61,200

These figures assume a typical staffing profile. Real numbers depend on your team size and process — we rerun the model with your own data during a consult.

FAQ

Does this replace our IT team?
The opposite. What it replaces is repetitive requests and rebuilding the same foundations — not judgement or architecture. In practice the biggest change after adoption is that IT finally has time for the work that never got scheduled: security, resilience, system replacement.
We can build our own. Do we need a platform?
Teams with development capability usually get more out of it, because what is saved is repetitive groundwork. The starter templates already include login, permissions, data access and payments, so your engineers begin at business logic instead of starting over each project.
Can Node-RED automation replace every integration?
No, and it should not. It suits data movement, format conversion and event triggers. Anything with complex business logic or high performance requirements still belongs in code. A simple test: will this logic change again in six months? If yes, configure it; if it is stable, write it.
How much of our time does adoption take?
Marketplace templates work out of the box and can be trialled the same day. Integrations and customisation are led by a Forward Deployed Engineer — your side mainly supplies system details and signs off, with no dedicated headcount required.

Further reading

企業 AI 導入

台灣中小企業找 FDE 實戰指南：30 天 AI 落地不是夢

你聽說了 FDE 前線部署工程師，但不知道怎麼找、費用多少、能做什麼？本文用台灣真實案例說明，FDE 如何幫中小企業在 30 天內完成 AI 導入。

企業 AI 導入

FDE、傳統顧問、IT 部門：台灣企業 AI 導入該選哪個？

台灣企業導入 AI 有三條路：找傳統管理顧問、靠自己的 IT 部門、或引入 FDE 前線部署工程師。三者差異是什麼？哪種適合你的公司？

企業 AI 導入

FDE 是什麼？前線部署工程師完整指南（2026 台灣版）

FDE（Forward Deployed Engineer，前線部署工程師）是目前台灣最熱門的 AI 職缺，比 AI 科學家還搶手。本文從零解釋 FDE 是什麼、做什麼、為什麼台灣企業現在最需要他。

Other solutions

Office & facilities

Documents, assets, supplies and everything else

Manufacturing

Production lines and supply chain operations

Sales

Proposals, account context, everything before the close

Marketing

Content, campaigns, spend and results

Want to see this run on your own process?

Leave your details and an FDE will walk it through with your data.

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