Draft AI customer support replies using your email and ERP data

AI reads support emails or chats, pulls context from your records, and drafts a reply for your review.

How the work actually flows

It branches. Every path runs; all paths must finish before it continues; a person has to approve before it continues.

Pattern: Parallel Split (2) ยท Synchronisation (3)

flowchart TD trig>"support request arrives"]:::trig s0["analyze sentiment and urgency"]:::task s1["pull context from records"]:::task s2["draft ai reply"]:::svc s3(("agent reviews draft")):::human trig --> s0 s1 --> s2 hg(("agent approves reply")):::human s2 --> hg hg -->|"approved"| s3 hg -. "sent back" .-> s2 gx{"+ which records to check"}:::gate s0 --> gx p00["check manuals"]:::task gx -->|"product manuals"| p00 p10["check order history"]:::task gx -->|"order records"| p10 p20["check past tickets"]:::task gx -->|"support history"| p20 jn{"+ context combined"}:::gate p00 --> jn p10 --> jn p20 --> jn jn --> s1 out[/"approved reply ready to send"/]:::out pay{{"faster informed replies less research"}}:::pay s3 --> out out --> pay classDef task fill:#e7f6fe,stroke:#34b8f0,color:#2c2a29 classDef svc fill:#f6f8fa,stroke:#7c8795,color:#2c2a29 classDef mi fill:#e7f6fe,stroke:#0079a8,color:#2c2a29,stroke-width:2px classDef human fill:#fff,stroke:#0079a8,color:#0079a8 classDef store fill:#f6f8fa,stroke:#0079a8,color:#2c2a29 classDef trig fill:#00a4eb,stroke:#0079a8,color:#fff,font-weight:bold classDef trigtime fill:#00a4eb,stroke:#0079a8,color:#fff,font-weight:bold classDef trigdata fill:#8ad4f5,stroke:#0079a8,color:#06314c,font-weight:bold classDef gate fill:#fff,stroke:#e8a23d,color:#6b4708,font-weight:bold classDef out fill:#1f9d6b,stroke:#167a53,color:#fff,font-weight:bold classDef pay fill:#06314c,stroke:#021f33,color:#fff
Starts itA stepAn outside serviceA personEvery pathWaits for allResultPayoff
Build size
Advanced

A larger build with multiple systems, AI reasoning, and custom rules.

Business functions
AI Chatbots & AssistantsEmail AutomationDocument Processing & OCRSpreadsheet & Database OpsFile & Cloud StorageCustomer Support & Ticketing
Connects
GmailGoogle SheetsGoogle DriveOpenAI
Featured in

The problem it solves

Support requests come in by email or chat, and answering each one well means digging through product manuals, past tickets, and order data before you can even start typing a reply. That research eats up time you could spend actually helping customers.

Who it fits

Support teams who need faster, well-informed replies without losing the human review step.

How it works

  1. A customer support request arrives by email or chat
  2. AI reads the message to judge sentiment, urgency, and topic
  3. It pulls relevant context from your product manuals, order records, and past support history
  4. A draft reply is generated for a support agent to review before sending
What you get

Replies drafted and ready for a quick review

Every support message gets a well-researched draft reply pulled from your manuals and records, ready for your team to send.

What you get

A draft reply, backed by your own business data, ready for an agent to approve.

What you need

A Gmail account, Google Sheets and Drive, access to your order or ERP data, and an OpenAI API key.

We can build this. But should you?

The hard question is not how to build it. It is whether this is the right thing to build first.

That is what a Fractional Chief AI Officer figures out with you, before anyone writes a line of code.

Let's Talk Strategy

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