AI Email Automation

Executive summary

An assistant that reads inbound email, detects priority and intent, drafts context-aware replies, summarizes long threads, schedules meetings, and creates tasks. It keeps the inbox under control and turns email into structured action.

Business problem

Email is a firehose. Important messages get buried, replies are slow, and staff spend hours triaging, summarizing threads, and copying action items into other tools by hand.

Architecture

AWS services

Data flow

1. 1

   Inbound email hits an SES receipt rule and lands in S3, triggering Lambda.

2. 2

   Bedrock detects priority and intent and summarizes the thread.

3. 3

   For actionable mail, Lambda drafts a reply, proposes meeting times, or creates a task via EventBridge.

4. 4

   High-priority items are surfaced immediately; routine ones are handled or queued.

5. 5

   Approved drafts are sent via SES; state is tracked in DynamoDB.

Security considerations

• Email content encrypted at rest; least-privilege access.
• Human-approval mode for outbound replies until trust is established.
• Sender authentication (SPF/DKIM/DMARC) for deliverability and anti-spoofing.
• Configurable retention and redaction of sensitive content.

Cost considerations

• SES is inexpensive (fractions of a cent per email).
• Bedrock inference for triage/drafting is the main variable cost.
• Serverless components idle at ~$0.

Scalability

• Scales with mailbox volume via serverless fan-out.
• Per-user and per-team routing rules.
• Add channels (shared inboxes, support aliases) without redesign.

Deployment roadmap

Future enhancements

• Calendar integration for real availability.
• Auto-labeling and folder organization.
• CRM logging of every customer email.
• Sentiment-based escalation to a human.