Enginuity — Trinity Graph v1.1

Trinity Graph — Enginuity

Three interconnected intelligence layers powering decision-ready recommendations for custom manufacturers

Knowledge

WHAT

35 entities · Quote-to-Cash · Margin Layer

Generative

WHAT IF

AI Recommendations · CFO Intelligence

Enginuity

Decision Intelligence Platform

⚡ The Core Structural Tension

CFO sets Revenue Target

CFO sets Margin Target

→

Sales Rep discounts to close

→

Tradeoff INVISIBLE in real time

→

Enginuity surfaces it

"The revenue vs. margin tradeoff nobody can see."

Enginuity — Decision intelligence for manufacturers who are done guessing.

Clarity

Velocity

Visibility

Reliability

Profitability

Personas, relationships, and structural tensions inside a $10M–$150M custom manufacturer

CFO / Strategy Lead

Primary Buyer · $10M–$150M Custom Manufacturer

Owns

P&L visibility across product lines

Revenue targets (set annually, reviewed quarterly)

Margin governance (floor targets by product/region)

Cash flow forecasting

Financial reporting (board, bank, ownership)

Pain Points

Hit rates unmeasurable — quote duplication

Margin visibility stops at management level

Decisions made on last quarter's pivot table

QBR is annual — needs to be quarterly

Revenue vs. margin tradeoff is invisible

Measures Success By

Revenue growth by region (YoY)

True hit rate — deduplicated

Gross margin by product line + distributor

Forecast accuracy (budget vs. actual)

Ops Manager / Engineering

Secondary Buyer · Phase 2 — Workflow Intelligence

Owns

Work order execution and throughput

BOM accuracy on custom jobs

WIP status and fabrication scheduling

RMA resolution (returns, warranty, rework)

Pain Points

Wrong part numbers in BOM pre-production

Can't modify WIP once in fabrication

Custom order variability breaks standard flow

No PM role in smaller companies

PO visibility gap — parties not notified

Connection to CFO

Ops cost data feeds CFO margin picture

Currently disconnected — Enginuity bridges this

Organizational Dependency Map

      CFO depends on → Sales Team (pipeline + forecast)

      CFO depends on → Ops Manager (labor cost + throughput)

      CFO depends on → Engineering (project cost estimates)

      CFO depends on → Distributors (order patterns + discount behavior)

      Sales Rep incentive → Maximize Revenue (will discount to close)

      Management incentive → Protect Margin (sets floor on gut feel)

      Result: Nobody has the full picture. The tradeoff is never analyzed together.

Knowledge Graph — WHAT

35 entity relationships mapping the full custom manufacturing process — quote to cash to market intelligence

🔴 The Core Data Identity Problem

      Same Opportunity

        ├── Quote v1 → Distributor A

        ├── Quote v2 → Distributor B

        └── New Quote (different number) → Distributor C

      3 records. 1 opportunity.

      Hit rate is UNMEASURABLE without deduplication.

      CFO is forecasting on phantom data.

Core Process Entities

30 relationships

#	Entity A	Relationship	Entity B	Layer
1	Customer	submits	RFQ	Core
2	RFQ	triggers	Quote	Core
3	Quote	created by	Sales Rep / Inside Sales / Outside Sales / Engineering	Core
4	Quote	contains	Line Items	Core
5	Line Item	references	Product / SKU	Core
6	Quote	contains	Distributor + Region + Location	Core
7	Distributor + Region	tied to	Sales Rep Territory	Core
8	Quote	has many	Quote Versions	Core
9	Quote Version	belongs to	Opportunity	Core
10	Opportunity	duplicated as	New Quote	Core
11	Distributor	represents	End Customer	Core
12	Customer	generates	Purchase Order (PO)	Core
13	PO	received by	Customer Service / Inside Sales	Core
14	PO	triggers	Visibility Notification	Core
15	Visibility Notification	sent to	Sales Rep + Engineering + Ops	Core
16	PO	triggers	Order Acknowledgement	Core
17	Order Acknowledgement	confirms	Delivery Date	Core
18	PO	releases	Work Order	Core
19	Work Order	contains	BOM	Core
20	BOM	lists	Part Numbers	Core
21	BOM	contains	Raw Materials + Purchased Components	Core
22	Work Order	tracked through	WIP Status	Core
23	WIP Status	updated by	Ops / Fabrication Team	Core
24	Work Order	completed as	Shipment	Core
25	Shipment	invoiced to	Customer / Distributor	Core
26	Shipment	triggers (if issue)	RMA	Core
27	RMA	classified as	Return / Warranty / Rework	Core
28	RMA	generates	Replacement Work Order	Core
29	Engineering Spec	required before	Project Quote	Core
30	Project	managed by	PM / Technical Services / Engineering	Core

Margin Intelligence Layer

5 relationships

#	Entity A	Relationship	Entity B	Layer
31	Tiered Discount Rate	governed by	Management Margin Target	Margin
32	Management Margin Target	applied to	Pricebook Items + Custom Engineered Products	Margin
33	Historical Sales + Market Data	feeds	Quarterly Business Review (QBR)	Margin
34	Market Tailwinds	contextualizes	Internal Sales Performance	Margin
35	Sales Rep	assigned to	Territory / Region	Margin

Generative Graph — WHAT IF

AI recommendation engine — from raw business data to action-ready intelligence by audience

AI Processing Pipeline

📥

Input Layer

Quote Versions PO Conversions Sales by Region BOM Cost Actuals Historical Sales Market Tailwinds Distributor Data

⚙️

AI Processing

Deduplicates Quotes Calculates True Hit Rates Segments Project vs. Day-to-Day Maps Revenue vs. Margin Tradeoff Connects Discount to Outcomes Contextualizes Market Tailwinds

📊

Output Layer

CFO Recommendations Sales Alerts Marketing Signals Engineering Flags QBR Package

Recommendations by Audience

CFO / Finance

Where is the revenue vs. margin tradeoff breaking down right now?

"Region 3 hit rate is up 12% but margin is down 8% — reps are discounting to win. Intervention needed."

Sales Leadership

Which reps are winning on volume but destroying margin?

"Rep A closes 41% of bids but averages 6% below margin floor — needs pricing guardrails immediately."

Management

Are our margin targets based on real data or last year's gut feel?

"Your Q2 margin target of 34% is 4pts above current market avg — recalibrate or expect to lose bids."

Marketing

Which segments have the best combined hit rate AND margin?

"Distributor B in the Southeast wins 58% at list price — prioritize this channel heading into Q3."

Engineering

Which custom jobs are being underquoted on labor?

"Custom weldments running 18% over estimated hours — spec process needs tightening before next bid cycle."

Operations

Where are throughput bottlenecks tied to order mix?

"High project volume in Q3 historically causes WIP bottlenecks — flag for capacity planning now."

The Contrarian Edge

      Most manufacturing software solves for process.

      Enginuity solves for decisions.

      Process tools tell you what happened.

      Enginuity tells you what to do next.