What you are probably dealing with
AI projects stall at compliance
The business wants it; compliance asks where the data goes, who can see it and how you investigate an incident. No answer means the project goes back, and it sits in evaluation for a year.
Producing audit evidence takes two weeks
Records live across different systems, so every audit becomes a company-wide effort — and what comes out still has to be checked by hand for completeness.
Service cannot be automated safely
Nobody will let AI answer anything touching amounts, contracts or entitlements. But human replies are slow, and satisfaction never improves.
Skilled people doing repetitive work
Reconciliation, issuance and case entry consume specialist time, squeezing out the work that actually requires judgement.
Before and after
Before
- 1AI projects parked in evaluation over compliance concerns
- 2Audit records spread across multiple systems
- 3Every customer question answered by a person
- 4Reconciliation and case entry consume specialist time
- 5Access control lives in policy rather than the system
With AI GO
- 1Data flow and access scoped at the system layer
- 2Audit records retrievable directly by period
- 3AI handles factual questions; sensitive ones route to people
- 4Repetitive work automated, specialists left to judge
- 5Permissions written into the system, not remembered
Modules involved
Finance and accounting form the core; service ticketing and judgment search can be added depending on your business.
AIGO 財務會計管理系統
獨立的財務會計與老闆管理報表系統，直接讀取 AIGO 正式帳務，提供真實三大報表、現金預測、帳齡、關帳、例外與會計 AI 影子覆核。
Analytics智能會計
中小企業智能會計系統。涵蓋收支交易、應收應付與暫收暫付、會計傳票、資金帳戶管理、損益／資產負債／現金流量報表、標籤與往來對象管理，並支援 Excel 報表匯出。
Operations藍新金流行動支付
整合藍新金流 (Newebpay) 支付服務。支援信用卡、WebATM、超商代碼與條碼付款，提供金流查詢與退款功能.
Integration客服工單中心
獨立客服工單系統：多管道工單受理、回覆串與結案滿意度、知識庫與常見問題管理、派工規則自動指派，內建 AI 建議回覆（比對 FAQ 與知識庫組 context，敏感議題自動轉人工）。
CRM司法院裁判書
整合司法院資料開放平臺 API，查詢裁判書內容、追蹤異動清單、依法院分類瀏覽，提供法律研究與案件分析支援。
AnalyticsPlatform capabilities
Permissions and audit are platform capabilities
Who can see which field, who changed what and who exported what are built into the platform rather than reimplemented per system. Auditors retrieve rather than reconstruct.
You draw the AI’s boundary
Mark topics AI must never answer and topics that must route to a person. AI answers from the knowledge base you build, with grounds that can be traced — not an unbounded black box.
Data stays where you can account for it
AI features use your own OpenAI key with the knowledge base in your account. Deployment shape can be discussed against your security requirements — there is no single mandated model.
Reconciliation and payments automated
Financial management, smart accounting and NewebPay modules automate routine reconciliation and collection, returning specialist time to work that needs judgement.
Labour cost you can recover
For a mid-sized financial services firm with a five-person back office at an average loaded rate of NT$550/hour:
Routine reconciliation and variance checks
- Hours / month
- 50 hrs
- Hourly rate
- NT$ 550
- Recovered / month
- NT$ 27,500
Retrieving and assembling audit evidence
Requires senior staff
- Hours / month
- 24 hrs
- Hourly rate
- NT$ 650
- Recovered / month
- NT$ 15,600
Answering factual customer enquiries
- Hours / month
- 40 hrs
- Hourly rate
- NT$ 450
- Recovered / month
- NT$ 18,000
Case entry and document filing
- Hours / month
- 32 hrs
- Hourly rate
- NT$ 450
- Recovered / month
- NT$ 14,400
| Work replaced | Hours / month | Hourly rate | Recovered / month |
|---|---|---|---|
| Routine reconciliation and variance checks | 50 hrs | NT$ 550 | NT$ 27,500 |
| Retrieving and assembling audit evidenceRequires senior staff | 24 hrs | NT$ 650 | NT$ 15,600 |
| Answering factual customer enquiries | 40 hrs | NT$ 450 | NT$ 18,000 |
| Case entry and document filing | 32 hrs | NT$ 450 | NT$ 14,400 |
| Total | NT$ 75,500 | ||
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
Can the system meet our regulator’s requirements?
Can customer data stay inside our environment?
Is it really safe to let AI reply to customers?
How long should the verification period be?
Further reading
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
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