Proposal Automation

Build an AI Proposal Generator with Google Docs and HubSpot

Build an AI agent that reads your HubSpot deal data, writes a complete sales proposal — problem statement, ROI table, pricing section, and case studies — creates it in Google Docs, and emails it to the prospect. Proposal prep goes from hours to minutes.

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Deploy in under 10 minutes
No code required
Production-ready from day one
Works With
HubSpot
Google Docs
Gmail
How It Works

Five Steps From Deal to Delivered Proposal

The agent reads your HubSpot deal, generates a tailored proposal using AI, creates the document in Google Docs, and sends it — all without opening a blank page or copy-pasting a single field.

HubSpot → Google Docs Proposal Pipeline

Fetch deal → generate content → create doc → personalise → email to prospect

HubSpot Google Docs Gmail
1

Fetch Deal Data

Agent pulls contact info, deal size, stage, and notes from HubSpot

Deal Lookup via HubSpot
2

Generate Content

AI writes problem statement, ROI table, pricing section, and relevant case studies

AI Content Generation
3

Create Google Doc

Full proposal document created in Google Docs from structured markdown

Doc Creation via Google Docs
4

Personalise Doc

Prospect name, company, deal terms, and custom fields replaced throughout the document

Text Replacement via Google Docs
5

Email to Prospect

Proposal link sent via Gmail to the prospect with a personalised cover message

Email Delivery via Gmail
Input
HubSpot deal ID or trigger on stage change
AI Output
Problem statement, ROI table, pricing, case studies
Document
Structured Google Doc, shareable link generated
Personalised
All placeholders replaced with deal-specific data
Delivered
Email sent to prospect with doc link attached
What You Get

Everything a Proposal Needs — Written by AI

The agent handles every part of proposal creation — from pulling the right deal data out of HubSpot to writing each section, formatting the document, and getting it in the prospect's inbox.

Auto-Populated Proposals

Every field in the proposal is pulled directly from HubSpot — company name, deal value, contact name, product tier, and close date. No blank pages, no copy-paste, no wrong numbers.

AI-Written Sections

The AI writes the problem statement using the prospect's industry and pain points, constructs the ROI table from deal data, drafts the pricing section, and selects the most relevant case studies from your knowledge base.

One-Click Delivery

Once the doc is created, Gmail sends the proposal to the prospect with a personalised cover message. The link, the contact details, and the body copy are all generated automatically — no drafting required.

Deal-Aware Pricing

Pricing tables are generated from the deal's line items and tier in HubSpot — the right package, the right price, the right discount. Proposal numbers always match what the rep agreed in conversation.

Template Customisation

Define your proposal structure once — section order, tone, brand language, headers — and the agent follows it every time. Update the template in Google Docs and every future proposal inherits the change immediately.

Consistent Branding

Every proposal follows the same structure, language, and formatting. No more variation between reps — the agent uses your approved template, tone guide, and case study library every single time.

The Difference

Manual Proposals vs AI-Generated

THE OLD WAY
Manual Proposal Writing
Built by your sales rep, one deal at a time
2–4h
Per Proposal
~60%
Same Template
~25%
Data Errors
Proposals per rep per week (target: 10)
0~2–3 proposals per rep per week10
Open HubSpot, copy contact name, deal value, and company — paste into a Word doc or slide deck and hope nothing is wrong
Write problem statement from scratch — or reuse last quarter's version with a different company name
Search through a case study folder for something vaguely relevant — pick the most recent one regardless of fit
Proposal arrives 2 days after the meeting — prospect has already talked to a competitor
VS
THE ARCHITECT WAY
AI Agent-Powered
Full proposal generated while the rep is still on the call
<5 min
Per Proposal
100%
Deal-Specific
Zero
Copy-Paste Errors
Proposals per rep per week (target: 10)
010+ proposals per rep — limited only by pipeline10+
HubSpot deal data fetched automatically — company, contact, deal value, stage, and product tier pulled in seconds
AI writes each section from scratch — problem statement, ROI table, pricing, and the most relevant case studies for this prospect's industry
Google Doc created, formatted, and shared — rep gets a link to review before it goes out, or auto-sends on trigger
Proposal in the prospect's inbox within minutes of the call ending — strike while the conversation is still fresh
95%
Reduction in proposal prep time
More proposals sent per rep per week
Zero
Wrong numbers or stale data
<5 min
From deal trigger to prospect inbox
<5 min
From HubSpot deal to proposal in the prospect's inbox
100%
Deal-specific — every section written for that prospect
More proposals sent per rep without extra hours
Zero
Copy-paste errors — all data pulled directly from HubSpot
Technical Details

HubSpot + Google Docs Integration Deep Dive

How the agent connects HubSpot's CRM data with Google Docs' document API to produce a production-ready proposal pipeline with zero manual steps.

HubSpot Data Fetching

Contact lookup and deal listing via HubSpot pull all relevant fields — company, deal value, product, stage, and custom properties. Runs on deal stage trigger or manual invocation.

Google Docs Creation

Document creation via Google Docs API from structured markdown — headings, tables, bullet lists, and formatted sections all generated correctly. Shareable link returned immediately after creation.

Text Replacement

All placeholder tokens in the base template replaced with deal-specific values — company name, contact name, pricing figures, dates, and product details — applied globally across the entire document in one pass.

Gmail Sending Logic

Email delivery via Gmail sends the proposal link to the prospect with a personalised cover message referencing the conversation. Rate limiting and retry logic handles temporary failures automatically.

Error Handling

Missing HubSpot fields, incomplete deal data, and Google Docs API errors are all caught gracefully. Agent logs the issue, notifies the rep, and retries automatically rather than failing silently.

Security & Auth

All credentials stored encrypted. OAuth2 for HubSpot and Gmail with automatic token refresh. Google Docs access scoped to agent-created documents only — no access to existing Drive files.

Agent Prompt
Build an AI agent that generates sales proposals in Google Docs from HubSpot deal data:

1. Deal Data Fetch — When a deal reaches a specified stage in HubSpot (or on manual trigger), fetch the full deal record: contact name, company, deal value, product tier, close date, and any custom fields.

2. AI Content Generation — Using the deal data, generate the full proposal content:
   - Executive summary and problem statement tailored to the prospect's industry
   - ROI table with projected value based on deal size and product
   - Pricing section matching the deal's line items and tier
   - 2–3 relevant case studies selected from the knowledge base by industry fit

3. Google Doc Creation — Create a new Google Doc from the AI-generated content using structured markdown. Apply the company's standard proposal template structure and formatting.

4. Personalisation — Replace all placeholder tokens throughout the document with deal-specific values: {ProspectName}, {CompanyName}, {DealValue}, {ProductTier}, {CloseDate}, and any custom fields.

5. Email Delivery — Send the Google Doc shareable link to the prospect via Gmail with a personalised cover message referencing the specific conversation or meeting.

Integrations: HubSpot (deal & contact data), Google Docs (document creation & editing), Gmail (email delivery).
Frequently Asked Questions

Common Questions

What HubSpot data does the agent use to build the proposal?
The agent fetches the deal record and associated contact from HubSpot — company name, contact name and role, deal value, product tier, close date, deal stage, and any custom properties you define. It also reads deal notes and activity history to give the AI richer context for writing the problem statement and ROI section. You control which fields are used via the agent configuration.
Can I control what goes in each section of the proposal?
Yes. You define the proposal structure once — which sections to include, the order, the tone, and what each section should focus on. The AI follows your structure and uses your approved language for things like company description and product positioning. You can also lock specific sections (like legal terms or standard pricing language) so the AI fills around them rather than rewriting them.
How does case study selection work?
You provide a knowledge base of case studies — a Google Doc, Notion page, or structured text file — tagged by industry, company size, and use case. The AI reads the prospect's industry and deal context from HubSpot, then selects the 2–3 most relevant case studies. Selection is based on semantic similarity, not keyword matching, so it handles industry variation well.
Can a rep review the proposal before it's sent?
Yes — the default workflow creates the Google Doc and notifies the rep with a review link before sending. The rep can edit directly in Google Docs, then approve the send. You can also configure the agent to auto-send without review for lower-value deals, or always require approval above a certain deal size threshold.
What triggers the agent to generate a proposal?
You can trigger the agent in three ways: automatically when a deal moves to a specific HubSpot pipeline stage (e.g., "Proposal Requested"), on a scheduled basis for all deals in a given stage, or manually by the rep for any individual deal. The trigger method is set during configuration and can be changed without redeploying the agent.
Does it work with existing Google Docs proposal templates?
Yes. You can point the agent at an existing Google Docs template with placeholder tokens. The agent uses your template as the base, replaces all tokens with deal data, and fills AI-written content into the designated sections. If you prefer to start fresh, the agent can also create the document from scratch using your defined structure without a base template.
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