Enterprise Email Orchestration

Every business deals with the same problem: emails arrive, humans triage them, and critical information eventually makes its way into the CRM or ERP—sometimes hours or days later. This manual process is slow, error-prone, and doesn't scale.

For this client, manual email triage was a massive productivity drain. Staff spent hours reading and routing emails, leading to delayed lead capture and inconsistent prioritization. They needed a way to automate this flow without losing accuracy.

The Solution

We built an automated pipeline that ingests emails from any source (Gmail, Office 365, IMAP), classifies them using an LLM to determine intent and priority, and routes them to the appropriate system (CRM, ERP, or Helpdesk).

graph LR
    subgraph Ingestion
      A[Email Inbox] -->|Trigger| B(Workflow Engine)
    end

    subgraph Intelligence
      B -->|Content| C[AI Classifier]
      C -->|Analysis| D{Intent Router}
    end

    subgraph Actions
      D -->|Lead| E[CRM: Create Lead]
      D -->|Order| F[ERP: Create Order]
      D -->|Support| G[Helpdesk: Create Ticket]
      D -->|Spam| H[Archive]
    end

    %% All actions log to audit
    E & F & G --> I[Audit Log]

    classDef plain fill:#fff,stroke:#333,stroke-width:1px;
    classDef accent fill:#f0f9ff,stroke:#3b82f6,stroke-width:2px;
    classDef v-large font-size:24px,font-weight:bold;

    class C,D accent;
    class A,B,E,F,G,H,I plain;
    class A,B,C,D,E,F,G,H,I v-large;

The core of the system is the AI Classification Layer. We configured an LLM to act as an intelligent triage assistant, extracting key fields like Intent (Lead, Order, Support), Priority (High, Medium, Low), and Entity (for multi-entity routing).

This architecture allows for real-time processing. As soon as an email hits the inbox, it's processed and routed. If the AI is unsure (low confidence), it routes the email to a manual review queue, ensuring no critical message is lost.