AI RFQ analysis for metal fabrication

Turn messy RFQs into structured, estimator-ready quotes.

QuotePilot AI extracts manufacturing requirements, flags missing information and quotation risks, generates customer clarification questions, and helps estimate a recommended quote using company-specific rates.

Evidence-backed extractionEvery populated requirement is tied to source text.
Risk & gap detectionFlags contradictions, missing data and timeline dependencies.
Estimator questionsGenerates customer-ready clarification questions.
Preliminary costingUses real company rates — it does not invent prices.

What QuotePilot does

Built for small and mid-sized fabrication teams that want a lightweight quoting copilot instead of a large ERP-style system.

RFQ requirement extraction

Customer, quantities, materials, dimensions, tolerances, processes, certifications, delivery and quality requirements.

Missing information

Finds quote-critical gaps and creates ready-to-send questions for the customer.

Contradiction checks

Detects conflicting specifications and surfaces the exact evidence that caused the issue.

Risk checks

Highlights schedule dependencies, approval timing and other RFQ-specific quotation risks.

Costing module

Material, machine time, bending, drilling, welding, coating, packaging, QA, transport, overhead and contingency.

Exports

Download analysis as TXT/JSON and costing data as CSV.

Workflow

01
Upload RFQ
02
Extract requirements
03
Review gaps & risks
04
Enter company rates
05
Calculate quote

Product screenshots

A complete walkthrough from RFQ intake to preliminary costing.

RFQ analysis dashboard
RFQ analysis status, completeness, missing items and risk checks.
Extracted RFQ requirements
Structured RFQ requirements with confidence and source evidence.
Missing information
Missing information with customer-ready clarification questions.
Risks and checks
Evidence-backed quotation risks and recommended actions.
Customer questions and estimator notes
Customer questions and estimator notes prepared automatically.
Preliminary costing inputs
Company-specific rates and manufacturing assumptions.
Costing results
Order cost basis, quote per part, recommended quote and detailed cost breakdown.

Tech stack

Python Streamlit OpenAI API PyPDF python-dotenv JSON / CSV exports
QuotePilot AI is a functional MVP. It currently supports TXT and text-based PDF RFQs. Scanned PDF OCR, CAD/STEP parsing, user accounts, persistent databases, ERP integrations and billing are logical next steps. Human review is required before a commercial quotation is sent.