Component Hardware - Scoping Session 1

RFQ/Quote Acceleration
Platform Scoping

Transforming 2-4 week quote cycles into 3-day structured, AI-assisted workflows

Today's Goal: Understand your as-is process & validate our proposed approach
Session 1 Agenda

What We'll Cover Today

60-minute structured discussion

  • 1. ForgeWorks' scoping process overview 5 min
  • 2. Business goals and urgency discussion 10 min
  • 3. As-is RFQ workflow walkthrough 25 min
  • 4. Data sources and systems mapping 10 min
  • 5. Stakeholder identification & next steps 5 min
  • 6. Q&A and scheduling Sessions 2-3 5 min
Recording Note: This session will be recorded for transcript processing. Speak freely - we'll structure insights later.
Session Overview

2-Week Timeline

Session 1 - TODAY
Business context & as-is process understanding
Session 2 - Week 2
Workflow deep dive with engineers (Marty, Mike Hartman, Eric, Steven)
Session 3 - Week 2
User reality check (engineers only - unfiltered truth)
Session 4 - End of Week 2
Solution alignment, mockup walkthrough, scope sign-off
Deliverable: Scoping Document + UX Mockups + 30-Day Build Plan
Then you see exactly what you're buying before signing
How It Works

Our Scoping Process

We front-load understanding so we can compress the building

1
Business Context
Define goals, urgency, and as-is workflow
2
Workflow Deep Dive
Map step-by-step process and data flows
3
User Reality
Surface hidden pain and tribal knowledge
4
Solution Alignment
Validate scope and sign off on approach
Week 1-2
4 Scoping Sessions
→
You See
Mockups & Scope
→
30 Days
Working Software
Our Understanding

The Real Problem: Engineering Bottleneck

Based on conversations with Steve, Max, and your team

250+
Active Projects in Pipeline
20
RFQs per Month
2-4 wks
Current Quote Turnaround
Current Pain Points
  • Capacity crisis: Engineers overwhelmed managing existing work while new RFQs pile up
  • Lost opportunities: Small projects ($20K-$50K) forgotten in the shuffle
  • Email chaos: No structured workflow, manual vendor spreadsheets
  • Tribal knowledge: Historical drawings (back to 1997) inaccessible
  • Quote velocity: "Our ability to turn around a budgetary quote in a week is very difficult" - Steve
Success Target
3 weeks → 3 days

Reduce RFQ turnaround from weeks to days for orders $50,000 and below

Focus Areas:
  • 80% reduction in engineer administrative time
  • Process more RFQs without adding headcount
  • Capture institutional knowledge from departing engineers
  • Enable small projects to be economically viable
Already Demonstrated to Steve & Max

AI Drawing Review Capabilities

What we showed in our previous demos

Intelligent Email Triage
Automatically captures and triages inbound RFQ emails, extracts drawings and specifications
Gap Detection
AI identifies missing specifications by comparing against historical data and successful quotes
Similarity Searching
Searches 1997+ historical drawing database to find precedent projects and reference pricing
Automated Email Drafting
Generates customer clarification emails for missing info (with BDM approval before sending)
Vendor Matching
Suggests appropriate suppliers based on capabilities and historical performance data
Human-in-the-Loop
AI suggests, human approves. All recommendations flagged for engineer review before advancing
Key Principle: "AI makes your people more efficient. We're not taking engineers out - we're making them 10x more productive." - Justin
Implementation Strategy

Phased Delivery: Value First, AI Second

Incremental value without "boiling the ocean"

Phase 1: Workflow Foundation
Days 0-60: Structure replaces chaos
  • Centralized RFQ inbox: Email capture, artifact management, project ID tracking
  • Four-stage Kanban: Inbound → Triage → Vendor Quotes → Ready for Sales
  • Vendor portal: Standardized quote submission (eliminates Excel spreadsheet chaos)
  • Dashboard visibility: Pipeline value, aging, owner assignments, SLA tracking
Value: Even without AI, you gain massive process improvement
Phase 2: AI Enhancement
Days 61-120: AI amplifies engineering expertise
  • RAG backend: Vector store of 1997+ historical drawings for similarity matching
  • Intelligent triage: AI pre-analyzes completeness, flags missing specs
  • Automated communication: Drafts customer clarification emails (human-approved)
  • Knowledge capture: Institutional knowledge becomes searchable asset (survives engineer departures)
  • Pricing guidance: Historical pricing reference for similar parts
Outcome: 80% reduction in engineer administrative time
Phase 3: Deep Integration (Future)
  • Outlook email auto-capture and routing
  • Microsoft Dynamics ERP sync (API token connection)
  • External data sources (material pricing, tariff data)
  • Automated quote generation for simple orders