Will the proposals look generic?

No. Templates are branded to your company, and the content is pulled from real deal data — client name, industry, specific needs. At the scale tier, AI generates custom sections based on each prospect's context.

Can I still customize proposals before sending?

Always. Automation handles the repetitive parts — client details, pricing, standard sections. Your team adds the strategic thinking, custom scope, and personal touches. The goal is 15 minutes of human work instead of 3 hours.

What format are the proposals in?

Google Docs or PDF — whatever your clients expect. We can also integrate with dedicated proposal tools like PandaDoc or Proposify if you prefer.

Accounting & Finance

Engagement letters take days to prepare because your team writes each one from scratch — or worse, copies from the last one and forgets to change the client name.

Accounting firms that prepare engagement letters manually lose billable time and delay client starts. A firm sending 10 engagement letters per month at 2 hours each wastes 20 hours — plus the deals lost to faster competitors who got their letter out the same day.

Three ways to solve this

Pick the tier that matches where your team is today. Each includes a clear workflow, the tools involved, and what you can expect.

Starter

3–5 days

1–10 employees, proposals written from scratch or copy-pasted from old ones, no templates.

Workflow

1Build 2–3 branded proposal templates in Google Docs covering your most common services.
2Connect your CRM or intake form to Make: when a new opportunity is created, a proposal draft is generated automatically from the right template with client details pre-filled.
3Add a notification to Slack: 'Proposal draft ready for [Client Name] — review and send.'
4Team reviews, customizes the key sections (scope, timeline), and sends — total time: 15–20 minutes instead of 3 hours.

Tools

Make Google Workspace Slack

Outcomes

Proposals generated in minutes, not hours.
Every proposal is branded, accurate, and professional — no copy-paste errors.
Team sends proposals the same day the opportunity is created.
Win rate improves because you're consistently first to respond.

Growth

1–2 weeks

10–50 employees, multiple services with different proposal formats, proposals bottleneck at senior staff.

Workflow

1Create a proposal library: templates for every service, with conditional sections that include or exclude based on client needs.
2Build a Make workflow that pulls deal data from HubSpot (client info, service selected, deal size) and assembles the right proposal from modular sections.
3Add pricing logic: based on deal size and service mix, the proposal includes the correct pricing table automatically.
4Track proposal status: sent, viewed, signed — all synced back to HubSpot so reps know when to follow up.

Tools

HubSpot Make Google Workspace

Outcomes

Proposals assembled from modular, pre-approved sections — consistency without rigidity.
Pricing calculated automatically based on deal parameters.
Senior staff review proposals in 5 minutes instead of writing them from scratch.
Proposal-to-close cycle shortened by 40–60%.

Scale

3–6 weeks

50+ employees, high proposal volume, needs AI assistance and approval workflows.

Workflow

1Build an AI-assisted proposal engine: Claude or Gemini API generates custom scope descriptions, timelines, and executive summaries based on deal context and historical win data.
2Implement approval workflows: proposals above a certain value require manager sign-off before sending, routed automatically based on deal size and type.
3Create proposal analytics: track which sections prospects spend time on, which templates have the highest win rates, and where proposals stall in the review process.
4Deploy a self-serve proposal builder for reps: select service, enter client details, customize AI-generated sections, get manager approval, send — all from one interface.