Private deployments for manufacturers, OEMs, and buyers

Turn production evidence into customer trust.

Connect purchase orders, specifications, production checks, quality evidence, corrective actions, and shipment records in one controlled customer journey.

Illustrative interface · Sample operational data
How It Works

From Camera Feed to Corrective Action in Three Steps

LIVE FEEDS

CAM-01

Grinding · Line 3

24fps

CAM-02

Polish · Line 1

30fps

CAM-03

Assembly · Line 2

24fps
Frames today1,247,832
INFERENCE
Confidence97.2%
Edge resolved · 18ms
Illustrative interface · Sample operational data

Built for private production and customer workflows where evidence, access, and accountability matter.

Current customer and program context

Asia One
NVIDIA Inception Program

IntelFactor is helping Asia One strengthen QA visibility and speed up evidence review across print-production workflows. Visit asiaone.com.hk

Deployment and rollout planning

Start Small. Expand on Evidence.

Begin with one private workflow, agree on acceptance criteria, and expand only after your team can verify the evidence and operational value.

Edge deployment — Jetson setup85%
Model fine-tuning60%
Paid pilot — production validation35%
Multi-line rollout10%

Real-Time Production Line Visibility

Monitor every inspection event across stations, shifts, and lots. Drill into any defect with full image evidence, confidence scores, and operator context.

Station Overview

Status
RunningENG
Spec Pack
🚩Chef Knife 8"⚠13 check definitions
KPIs
Illustrative sample dataFirst Pass Yield 94.2%Throughput 2,400/hrScrap Rate ↓ 38%

Automated Shift Quality Reports

First-pass yield trends, defect breakdowns by type and station, and corrective action tracking — generated automatically at every shift change.

Critical — line stopped
Warning — FPY dipping
Healthy — all lines passing

FPY at 94.2% across all stations this shift. Zero critical holds.

Shift B · Feb 17, 14:00

SOP-Driven Quality Standards Enforcement

SOP-driven spec packs
Per-defect threshold tuning
AQL-based lot acceptance
Chef Knife 8"›Spec Pack•••
Check definitions forblade integrityzoe

Visual inspection criteria for edge chips, burrs, and temquinnper color deviations. Thresholds set per product SKU with AQL sampling rules for lot-level accept/reject decisions.

Edge-First AI Inspection

On-site processing keeps production decisions available even when cloud services are not.

Multi-Line, Multi-Site Deployment

Scale from one station to entire facilities. Centralized analytics across every production line.

Structured deployment

Scope → Validate → Expand — with agreed evidence at each phase.

Cost of Poor Quality Tracking

Quantify COPQ reduction, scrap savings, and inspection ROI across every deployment phase.

Contact

Discuss a Private Deployment

We will map one active product or contract from purchase order through production, quality review, corrective action, and customer delivery.

Request a private scoping call

Email us with one active product or contract. We will reply directly to arrange a private scoping session.

Request a private scoping call

If no email window opens, write to contact@intelfactor.ai.

Company

IntelFactor Systems LLC

Location

Santa Barbara, California

Bring one active contract or product, its acceptance criteria, and the people responsible for production and approval. We will scope a private workflow before any broader rollout.

Private scoping session

Invite-only and tied to your acceptance criteria