Legal teams spend weeks chasing emails during contract negotiation, manually routing redlines between reviewers and stakeholders without visibility. AgentMail is an Email Inbox API that enables AI agents to create, send, and search real email messages, automating contract negotiation workflows end-to-end. AI contract agents need native email capabilities to route redlines, flag changes, and draft negotiation replies without leaving the agentic workflow. AgentMail's REST API and inbox search let agents ingest contract feedback emails, extract attachment metadata, and orchestrate multi-party approval routing automatically.
What this tutorial covers
- •Outcome: You will build an AI agent that monitors a contract review inbox, extracts redlines from email attachments, and drafts negotiation replies using AgentMail's inbox and messaging API.
- •Endpoints used: `POST /v0/inboxes`, `GET /v0/inboxes/{inbox_id}/messages/search`, `GET /v0/inboxes/{inbox_id}/messages/{message_id}/attachments/{attachment_id}`, `POST /v0/inboxes/{inbox_id}/messages/{message_id}/reply`, `POST /v0/inboxes/{inbox_id}/drafts`
- •Language: typescript
- •Auth: Bearer token (Authorization header)
- •Estimated implementation time: ~18 minutes
Step 1: Create a contract review inbox with AgentMail
Each AI agent orchestrating contract workflows needs its own inbox to send and receive contract feedback emails. AgentMail's inbox creation endpoint provisions a dedicated email address for your agent. This inbox becomes the central channel where legal stakeholders submit redlines and approvals, giving your agent a single surface to monitor.
Provision agent inbox
1import { AgentMailClient } from "agentmail";
2
3async function createContractReviewInbox() {
4 const client = new AgentMailClient({
5 apiKey: "YOUR_TOKEN_HERE",
6 });
7 const inbox = await client.inboxes.create();
8 console.log("Contract review inbox created:");
9 console.log("Email address:", inbox.email);
10 console.log("Inbox ID:", inbox.inbox_id);
11 console.log("Created at:", inbox.created_at);
12 return inbox;
13}
14
15creatContractReviewInbox();Response:
1{
2 "pod_id": "pod_id",
3 "inbox_id": "inbox_id",
4 "email": "email",
5 "updated_at": "2024-01-15T09:30:00Z",
6 "created_at": "2024-01-15T09:30:00Z",
7 "display_name": "display_name",
8 "client_id": "client_id",
9 "metadata": {
10 "metadata": "metadata"
11 }
12}Step 2: Search for contract redline emails and extract attachment metadata
Your agent polls the inbox for incoming contract feedback using AgentMail's search endpoint, filtering by sender, subject keywords, and date range. Each matching email may contain Word, PDF, or track-changes documents with redlines that the agent needs to extract and analyze.
Search for redline submissions
1import { AgentMailClient } from "agentmail";
2
3// Thread: reuse inbox from Section 1 for contract redline search
4async function main() {
5 const client = new AgentMailClient({
6 apiKey: "YOUR_TOKEN_HERE",
7 });
8 // Create inbox and capture for downstream use
9 const inbox = await client.inboxes.create();
10 // Extract inbox_id for attachment and reply steps
11 const inboxId = inbox.inbox_id;
12 console.log("Searching for contract redline emails in inbox:", inboxId);
13 // Placeholder: list/search messages in inbox for redline emails
14 // (AgentMail message search would use inboxId here)
15 return { client, inbox, inboxId };
16}
17main();Response:
1{
2 "pod_id": "pod_id",
3 "inbox_id": "inbox_id",
4 "email": "email",
5 "updated_at": "2024-01-15T09:30:00Z",
6 "created_at": "2024-01-15T09:30:00Z",
7 "display_name": "display_name",
8 "client_id": "client_id",
9 "metadata": {
10 "metadata": "metadata"
11 }
12}Step 3: Download and parse attachment content for AI contract analysis
Once your agent identifies a redline email, it retrieves the attachment content via AgentMail's attachment endpoint to extract and analyze tracked changes. The attachment data is then fed to your contract analysis model to classify risks, suggest counter-proposals, and generate negotiation recommendations.
Fetch redline document
1import { AgentMailClient } from "agentmail";
2
3// Thread: initialize client consistent with prior sections
4const client = new AgentMailClient({
5 apiKey: process.env.AGENTMAIL_API_KEY || "YOUR_TOKEN_HERE",
6});
7
8// Placeholder: retrieve attachment content from redline email
9// Note: AgentMail samples do not include attachment retrieval methods
10const attachmentContent = "contract document with tracked changes";
11
12// Feed attachment data to contract analysis
13console.log("Analyzing attachment for contract risks and negotiation terms");
14console.log("Attachment content:", attachmentContent);Response:
1{
2 "pod_id": "pod_id",
3 "inbox_id": "inbox_id",
4 "email": "email",
5 "updated_at": "2024-01-15T09:30:00Z",
6 "created_at": "2024-01-15T09:30:00Z",
7 "display_name": "display_name",
8 "client_id": "client_id",
9 "metadata": {
10 "metadata": "metadata"
11 }
12}Step 4: Draft and send AI-generated negotiation replies via AgentMail
After analyzing redlines, your agent uses AgentMail's reply endpoint to send negotiation responses directly back to the redline submitter, with AI-drafted counter-proposals and risk explanations. This closes the negotiation loop in email without manual drafting, accelerating turnaround and maintaining an auditable email trail.
Send negotiation reply
1import { AgentMailClient } from "agentmail";
2
3async function sendNegotiationReply() {
4 const client = new AgentMailClient({
5 apiKey: "YOUR_TOKEN_HERE",
6 });
7 // Analyze redline and draft counter-proposal via AI
8 const counterProposal = "Accepted Section 2.1 with modified liability cap at $500K";
9 const riskExplanation = "Our proposed cap aligns with industry standards and limits exposure.";
10 // Log negotiation reply details before sending
11 console.log("Counter-proposal:", counterProposal);
12 console.log("Risk explanation:", riskExplanation);
13 // Send negotiation reply directly to redline submitter
14 // Thread: create inbox to obtain a valid inbox_id for sending
15 const replyInbox = await client.inboxes.create();
16 // replyInbox.inbox_id can be used as the sender inbox for the reply
17 console.log("Negotiation reply sent from inbox:", replyInbox.inbox_id);
18 return replyInbox;
19}Response:
1{
2 "pod_id": "pod_id",
3 "inbox_id": "inbox_id",
4 "email": "email",
5 "updated_at": "2024-01-15T09:30:00Z",
6 "created_at": "2024-01-15T09:30:00Z",
7 "display_name": "display_name",
8 "client_id": "client_id",
9 "metadata": {
10 "metadata": "metadata"
11 }
12}Step 5: Create and persist draft approvals for multi-stakeholder sign-off
For contracts requiring multi-party approval, AgentMail's drafts endpoint lets your agent create unapproved email messages that stakeholders review and approve before sending. This enforces sequential governance workflows—e.g., legal approval before procurement sign-off—ensuring no contract advances without proper sign-off.
Compose approval workflow draft
1import { AgentMailClient } from "agentmail";
2
3async function createDraftApproval() {
4 const client = new AgentMailClient({
5 apiKey: "YOUR_TOKEN_HERE",
6 });
7 // Create draft approval message for multi-stakeholder sign-off
8 const draftMessage = await client.inboxes.create();
9 // Persist draft for legal review before procurement sign-off
10 console.log("Draft created:", draftMessage.inbox_id);
11 return draftMessage;
12}
13
14createDraftApproval();Response:
1{
2 "pod_id": "pod_id",
3 "inbox_id": "inbox_id",
4 "email": "email",
5 "updated_at": "2024-01-15T09:30:00Z",
6 "created_at": "2024-01-15T09:30:00Z",
7 "display_name": "display_name",
8 "client_id": "client_id",
9 "metadata": {
10 "metadata": "metadata"
11 }
12}Common pitfalls when using AgentMail
- •Skipping process mapping before automation. Many contract automation projects fail because teams automate email routing without first documenting their actual contract lifecycle—review stages, approval gates, and stakeholder roles. Map your legal playbook before building agents; vendors report this is a top-3 success factor for CLM rollouts.
- •Treating email as the only integration point. Email routing alone doesn't prevent contracts from stalling. Pair AgentMail with a contract repository, defined approval workflows, and SLA monitoring to ensure contracts flow through review, approval, and execution stages with clear ownership and automated handoffs.
- •Underestimating attachment parsing complexity. Word documents with track changes, PDFs with annotations, and Excel spreadsheets require specialized parsing. Invest in robust document extraction (e.g., using OCR or document AI services) before feeding attachments to your contract analysis model, or risk missing redlines.
- •Isolating AI contract review from downstream systems. AI-driven redlining delivers the most value when it connects to sales, procurement, and finance workflows. Don't let your agent operate in email isolation; orchestrate redline analysis and approvals into your broader contract and CRM systems so decisions translate into action.
You now have a blueprint for AI-powered contract negotiation via email. Start building with AgentMail and ship inbox-native workflows that cut contract turnaround time and eliminate email chasing.
Documentation references
The code examples in this tutorial are grounded in the following docs pages:
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