AI Research Assistant Email Agent

The problem

Research often requires information that is not published. Datasets behind paywalls, proprietary benchmarks, clarifications on methodology, pricing details from vendors, or expert opinions on niche topics. Getting this information means emailing people — authors, founders, engineers, analysts — and waiting for replies.

This is tedious and time-consuming. You draft dozens of personalized outreach emails, track who has responded, send follow-ups to those who have not, and synthesize the information as it trickles in. It is exactly the kind of repetitive, structured work that an AI agent excels at — but only if the agent can actually send and receive email.

Existing tools make this difficult. Gmail APIs require OAuth scopes and per-user credentials. Transactional email services are send-only. Building a mail server is a project in itself. What you need is an email address your agent can use programmatically, with full send, receive, and threading support.

How an AI agent solves this

A research assistant agent takes a brief — a topic, a list of questions, and a set of contacts — and executes the outreach campaign autonomously. It crafts personalized emails based on each contact's background, sends them from a real address, processes incoming replies, extracts relevant information, and follows up when clarification is needed.

• Sends personalized outreach referencing the recipient's specific work or expertise
• Processes replies to extract answers, data links, and attachments
• Sends follow-up questions in the same thread when clarification is needed
• Tracks which contacts have responded and which need a reminder
• Compiles findings into a structured report for the researcher

How it works with Robotomail

Robotomail gives your research agent its own email identity with full send and receive capability. Provision a mailbox, set up a webhook for incoming replies, and your agent handles the rest — from initial outreach to follow-up conversations.

Step 1: Send outreach emails. Your agent calls POST /v1/mailboxes/{mailbox_id}/messages for each contact, with content tailored to their background and the specific information you need.

curl -X POST https://api.robotomail.com/v1/mailboxes/{mailbox_id}/messages \
  -H "Authorization: Bearer rm_live_..." \
  -H "Content-Type: application/json" \
  -d '{
    "to": ["[email protected]"],
    "subject": "Question about your 2025 paper on multi-agent systems",
    "bodyHtml": "<p>Dear Dr. Chen,</p><p>I am researching coordination protocols in multi-agent systems and found your paper \"Emergent Cooperation in LLM Swarms\" particularly relevant. Could you share the dataset used in Section 4, or point me to a public repository?</p><p>Thank you,<br/>Research Agent — Acme Labs</p>"
  }'

Step 2: Receive and parse replies. When a contact responds, Robotomail delivers the full message to your webhook. The payload includes the text body, any attachments (stored in R2 with download URLs), and the thread ID for context.

{
  "event": "message.received",
  "mailboxId": "mbx_research_01",
  "message": {
    "from": { "email": "[email protected]", "name": "Dr. Chen" },
    "subject": "Re: Question about your 2025 paper on multi-agent systems",
    "textBody": "Thanks for your interest. The dataset is available at github.com/chen-lab/lm-swarms-data. Let me know if you need the preprocessing scripts as well.",
    "threadId": "thd_research_789",
    "attachments": []
  }
}

Step 3: Follow up in the same thread. If the agent needs more detail, it sends a follow-up using the inReplyTo field to keep the conversation organized. The contact sees a single, coherent thread in their inbox.

curl -X POST https://api.robotomail.com/v1/mailboxes/{mailbox_id}/messages \
  -H "Authorization: Bearer rm_live_..." \
  -H "Content-Type: application/json" \
  -d '{
    "to": ["[email protected]"],
    "subject": "Re: Question about your 2025 paper on multi-agent systems",
    "bodyHtml": "<p>Thank you, Dr. Chen. The preprocessing scripts would be very helpful — could you share those as well?</p>",
    "inReplyTo": "<[email protected]>"
  }'

Your agent can use the threads API to retrieve full conversation history for any contact, making it easy to build summaries and track which questions remain unanswered. Start with a platform mailbox like [email protected] or add your organization's domain.

Key benefits

• Parallel outreach: Contact dozens of sources simultaneously instead of emailing one at a time
• Context-aware follow-up: The agent uses thread history to ask intelligent follow-up questions
• Attachment handling: Datasets, papers, and files sent by contacts are automatically stored and accessible via API
• Professional identity: Send from a real address with proper DNS authentication — recipients see a legitimate sender, not a bot
• Get started quickly: Check the API docs and introductory post to build your first research agent

Create a free account and start gathering information in minutes. The free tier includes 50 sends per day and webhook delivery — no credit card required.