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Quote Request Assistant

Capture quote requests from forms and emails, extract requirements, and draft initial quote responses or scope documents.

quotessalesintakescope

What you need to build this

Connect these tools, give the AI this data, expect these outputs.

1

Connect

APIs & tools to set up

OAuth, API keys, or webhooks depending on the tool.

3

Give to AI

Inputs per run

  • Raw quote request (form fields or email body)
  • Service catalog with pricing guidelines
  • Past quote examples for similar requests
  • Qualification criteria (minimum project size, service area, etc.)
4

Expect

AI outputs

  • Structured requirements summary: scope, timeline, budget signals, location
  • Qualification score: fit vs. not-fit with reasons
  • Draft acknowledgment email with clarifying questions
  • New row in quote tracker spreadsheet/CRM
BeginnerSemi-automatedHigh value3 no-code · 2 low-code · 4 custom options

Business problem

Quote requests arrive via website forms, email, and phone messages in inconsistent formats. Staff spend 20–30 minutes per request just organizing requirements before they can price anything.

Expected outcome

Each quote request is automatically logged, requirements extracted into a structured format, and a draft scope/acknowledgment email sent within 1 hour of receipt.

Who it's for: Businesses receiving 5–30 quote requests per week where each quote requires understanding scope before pricing — contractors, agencies, custom manufacturers.

Required data sources

What data goes into the AI

  • Raw quote request (form fields or email body)
  • Service catalog with pricing guidelines
  • Past quote examples for similar requests
  • Qualification criteria (minimum project size, service area, etc.)

What the AI should output

  • Structured requirements summary: scope, timeline, budget signals, location
  • Qualification score: fit vs. not-fit with reasons
  • Draft acknowledgment email with clarifying questions
  • New row in quote tracker spreadsheet/CRM

APIs needed to automate this

System behavior

  • Triggered on each new form submission or labeled email
  • Extracts and structures requirements — does not generate final pricing
  • Flags unqualified requests with reason (out of area, too small, etc.)
  • Creates tracker row and acknowledgment draft within 1 hour
  • Escalates complex or high-value requests to owner immediately

No-code vs low-code vs custom

No-code

Lowest effort

Non-technical owners, quick validation, under 50 runs/day

3 options listed

Low-code

Medium effort

Operators comfortable with Zapier/n8n, need more control

2 options listed

Custom build

Highest effort

High volume, custom logic, or strict data privacy requirements

4 options listed

No-code optionsLow-code optionsCustom build stack
Zapier: form submit → ChatGPT extract → Sheets row + Gmail draftn8n: form webhook → OpenAI structured extraction → CRM + emailWebhook for form submissions + Gmail label trigger for email quotes
Typeform + OpenAI integrationMake.com with form parser and GPT modulesOpenAI structured JSON output for requirement extraction
HubSpot form + AI enrichmentSheets/CRM API for tracker update
Gmail API for acknowledgment draft

Start with no-code to validate the workflow. Move to low-code when you hit rate limits or need branching logic. Custom build when volume, privacy, or integration depth requires it.

Step-by-step implementation

  1. 1Define quote tracker columns and qualification criteria
  2. 2Connect form and email intake channels
  3. 3Build extraction prompt with 5–10 past quote examples
  4. 4Set up auto-acknowledgment draft with clarifying questions
  5. 5Run in review mode: AI extracts and logs, human reviews before sending
  6. 6Track quote-to-close rate and refine qualification criteria quarterly

Risks and limitations

  • AI may miss critical requirements leading to under-quoted projects
  • Auto-acknowledgment with wrong clarifying questions looks unprofessional
  • Qualification AI may reject good leads with non-standard requests
  • Pricing guidelines in prompts could leak through draft emails

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