AI Email Management: Route, Classify, and Monitor Every Message Automatically

What AI email management actually requires

Managing email with AI is not a feature you bolt onto a send API — it is an infrastructure problem. An agent that manages email needs to receive messages as structured data, classify them before deciding what to do, reply inside existing threads, and stay within sending-reputation boundaries it cannot override. Each of those requires a layer below the agent, not a prompt inside it.

Mails.ai provides that layer: inbound parsing, injection scanning, intent classification, per-agent reputation, and a cold-email firewall — so your agents manage email with constraints they cannot circumvent.

Classify and route inbound automatically

Every inbound message is parsed from raw MIME into a structured event and optionally classified by intent and urgency — before your agent sees it. Your routing logic reads typed fields, not raw email:

import Mails from "@mailsai/sdk";
const mails = new Mails({ apiKey: process.env.MAILS_API_KEY });

// Stream classified inbound events
for await (const event of mails.events.stream({ type: "message.received" })) {
  if ((event.injection_score ?? 0) > 0.5) continue;  // skip attacks

  // Route by classified intent — no LLM call needed for routing
  switch (event.intent) {
    case "billing_question":
      await billingAgent.handle(event);
      break;
    case "support_request":
      await supportAgent.handle(event);
      break;
    case "meeting_request":
      await calendarAgent.handle(event);
      break;
    default:
      await triageAgent.handle(event);
  }
}

Intent classification runs on the infrastructure side, so routing decisions are made before your model runs — faster and cheaper than passing every message through an LLM to decide where it goes.

Reply in threads, not new conversations

When an agent replies, the response lands inside the existing conversation in the recipient's mail client. Thread reconstruction is automatic — your code passes the message ID it is replying to, and the API handles Message-ID chains, In-Reply-To headers, and References headers:

// Agent replies in the same thread — threading is automatic
await mails.messages.reply(event.message_id, {
  body_text: generatedReply,
});
// The reply appears in the recipient's existing conversation,
// not as a separate email.

Monitor reputation per agent

In a multi-agent setup, one misbehaving agent should not take down everyone else's deliverability. Mails.ai scores reputation per agent: bounce rates, complaint rates, and send volume are tracked independently. If one agent crosses the 0.3% complaint threshold, it auto-suspends while your other agents keep sending.

Cold and bulk outreach is blocked in the send call itself — an agent that is prompted into prospecting gets a 422 cold_email_prohibited response and nothing is transmitted. This is not configurable, because a shared sending estate only stays deliverable if no agent on it can send unsolicited mail.

Test the full management flow without sending mail

Test keys (mk_test_…) run the entire path — parsing, injection scanning, classification, threading, webhook delivery — and transmit nothing. You can simulate inbound messages to verify your routing logic, test edge cases in classification, and confirm reply threading before any real mail moves.

Pricing

Every plan includes MIME parsing, injection scanning, thread reconstruction, and the per-agent reputation system. Intent classification is included on paid plans at no extra charge. Free covers one agent with 3,000 sends and 3,000 inbound — no card required. Pro is $20/month for five agents, Scale is $99/month for unlimited agents. For the full agent identity and inbox setup, see AI email agent. For the inbound parsing layer in detail, see email parsing API. For building a Python-based email handler, see send email from a Python AI agent. For the broader agent email infrastructure, see email for AI agents.