AI-Native Automotive Quality Platform
Qualitiviss

Find where quality is costing you. Understand why. Fix it. Make sure it doesn't come back.

Qualitiviss connects quality execution, quality records and quality intelligence in one system. From shop-floor SPC and internal rejection to customer complaints, 8D, PFMEA, Control Plans, MSA, audits, warranty and quality learning, it creates one connected quality source of truth—with QAI as the decision-support layer on top.

Illustrative operational viewDV-QUA / READ-ONLY
Process capabilityCpK 1.18
Evidence-backed findingDrift detected before rejection limit
Quality evidence · illustrative values
SPCNCRPFMEA
Drift detected before rejection limit. Sources include SPC, NCR, PFMEA.
Closed-Loop Quality ExampleEvidence-backed

A recurring dimensional rejection is increasing COPQ on one production line.

Internal rejection and cost trend are increasing on the affected product and line
Process capability has deteriorated and a similar historical failure already has a corrective action
The related PFMEA failure mode and Control Plan controls can be brought into the same investigation context
Recommended next step

Investigate the recurring cause, validate the corrective action, review the PFMEA and Control Plan, then verify effectiveness before closure.

Illustrative product-output example. Values and findings are not customer results unless a published case study is linked below.

78 → ≤45 days
Warranty closure moved from 78 days to within the published 45-day SLA in the linked case study
4×
Warranty volume handled in the published case study while maintaining the improved closure discipline
From Quality Data to Decisions

Your quality head’s daily intelligence workbench.

Move beyond scattered reports. Bring the quality evidence available across plant operations into one review: what changed, where losses are growing, which issues have recurred and what needs human attention.

Illustrative QAI Quality Review
Variation

Which process characteristics are drifting?

Evidence: SPC and inspection measurements

Loss

Which defects and lines are driving COPQ?

Evidence: Internal rejection and approved cost data

Recurrence

Where has a previously closed defect returned?

Evidence: Complaints, 8D and CAPA history

Prevention

Which process risks and controls need review?

Evidence: PFMEA and Control Plan context

Conceptual workflow, not a live customer dashboard. Data access and connected capabilities depend on the deployed modules and integrations. QAI assists; authorized teams validate and approve actions.

01

Detect and quantify

SPC, inspection and rejection reveal process deterioration and loss.

02

Investigate and correct

QAI supports evidence collection, complaint investigations and 8D preparation.

03

Prevent and verify

Connect lessons to PFMEA, Control Plans and approved effectiveness checks.

Beyond Conventional QMS

Don't just manage quality. Improve it.

Built for the shop floor. Trusted for compliance. Designed to help manufacturing teams connect quality evidence, investigate faster and prevent repeat losses.

Evaluating conventional enterprise QMS?

Evaluate how a quality platform supports both compliance and operational improvement. Ask more than whether a system documents compliance: how does it connect SPC, rejection and COPQ to complaints, 8D, PFMEA, Control Plans and action effectiveness?

Keep compliance connected

Bring process risks, control plans, audit evidence and corrective actions into a connected quality workflow.

See the cost of quality

Link shop-floor measurements and rejection evidence to recurring loss and COPQ priorities, subject to available integrations.

Investigate and prevent recurrence

Use QAI to assemble evidence and propose investigation priorities; engineers validate causes and approve actions.

Competitors offer differing quality-management, analytics and AI capabilities. This is a comparison of evaluation priorities, not a claim that other platforms lack these features. Ask for a demonstration of capabilities and integrations available in your deployment.

Why Teams Buy Qualitiviss

Stop paying for the same quality problem twice.

Traditional systems can help teams record a complaint, create an 8D and close an action. Qualitiviss is designed to close the quality loop: connect the failure to operational evidence, corrective action, PFMEA, Control Plan, SPC and effectiveness verification so recurrence becomes visible and preventable.

Value reason 01

Find where quality is costing money

Turn rejection percentages into COPQ priorities across scrap, rework, sorting, customer rejection, warranty and recurring defects—then drill into the plant, product, process, line, shift or characteristic driving the loss.

Value reason 02

Reduce complaint and 8D effort

Bring production, inspection, rejection and historical incident context into the investigation so engineers spend less time reconstructing what already happened and more time solving the problem.

Value reason 03

Close the quality loop, not just the record

Connect corrective action back to PFMEA, Control Plan and process control, verify effectiveness and retain the learning so the next team or plant does not start from zero.

Cost of waiting

A corrective action marked Closed does not prove the problem is eliminated. When quality records remain disconnected, the same defect can return through another line, product, shift or plant—and the organization pays for the problem again.

How the value becomes measurable
Detect
Understand
Correct
Prevent
Verify
Learn
Map the first business outcome
Published warranty case study

Qualitiviss connected product traceability, division and supplier ownership, and human approvals as the warranty team moved from 78 days to within the 45-day closure SLA while handling four times the volume.

Review the evidence
QAI — The Quality Decision Layer

Your quality system should do more than store records.

QAI works across the connected quality context available inside Qualitiviss to help teams understand what changed, what is costing money, what is recurring, what requires attention and what should happen next. AI proposes; authorized quality professionals validate and decide.

Analyst Pack · 01

COPQ Analyst

Turn quality loss into a daily management signal.

Identify the defects and processes contributing most to quality cost
Compare loss by plant, product, line, machine, shift and characteristic
Surface recurring patterns that deserve management attention
Intended outcome

A prioritized view of where the quality team should act first to reduce cost of poor quality.

QAI assists analysis and prioritization; management and quality teams retain decision authority.

Analyst Pack · 02

Complaint & 8D Analyst

Bring previous quality knowledge into every investigation.

Retrieve relevant production, inspection and rejection history
Surface similar historical complaints and corrective actions
Assist structured containment, investigation and 8D preparation
Intended outcome

Less time reconstructing history and more context for faster, stronger problem solving.

Engineers validate root cause, containment, corrective action and customer-facing responses.

Analyst Pack · 03

Prevention & Recurrence Analyst

Check whether closed actions are actually preventing recurrence.

Connect current failures with previous corrective actions
Highlight related PFMEA risks and Control Plan controls
Surface effectiveness-verification gaps and recurrence signals
Intended outcome

Stronger prevention discipline and a clearer link between corrective action and process control.

PFMEA, Control Plan and process-control changes remain under authorized human approval.

Analyst Pack · 04

Quality Review Analyst

Prepare the quality story without hours of manual consolidation.

Summarize rejection, COPQ, complaints, open 8Ds, CAPA ageing and SPC abnormalities
Highlight recurring defects, warranty signals, supplier quality and audit findings
Explain what changed, why it matters and what needs attention
Intended outcome

Quality professionals spend more time improving quality and less time preparing the story of what already happened.

QAI prepares evidence-backed analysis; the quality team reviews, validates and acts.

What It Does

Built around the work your team performs every day.

Start with one operating decision, connect the evidence already available and expand as value becomes visible.

01Online SPC — digitize variable and attribute inspection, monitor capability and detect process deterioration
02Internal Rejection & COPQ — connect scrap, rework, sorting and rejection to financial impact
03Customer Complaints & 8D — manage containment, investigation, corrective action and structured response
04PFMEA & Control Plan — keep process risks, controls, characteristics and lessons learned connected
05MSA & PPAP — govern measurement capability, readiness evidence and customer-quality documentation
06CAPA & Audits — manage ownership, ageing, evidence, findings and effectiveness verification
07Supplier Quality & Warranty — connect external failures back to product, process and manufacturing history
08Quality LMS & Organizational Memory — retain learning so teams do not restart from zero when problems recur
Questions It Helps Answer
?

Where is quality costing us the most right now?

?

Which defects, parts, processes, lines or shifts are driving COPQ?

?

Have we seen this customer complaint or failure mode before?

?

Did the previous corrective action actually prevent recurrence?

?

Which PFMEA and Control Plan are affected by this issue?

?

What changed this week, why does it matter and what needs attention next?

What Your Team Receives

One connected quality source of truth across quality planning, execution and corrective action

COPQ visibility by plant, product, part, process, line, machine, shift, characteristic and defect

Faster complaint and 8D preparation with relevant historical quality context

Connected PFMEA, Control Plan, SPC, inspection and corrective-action evidence

Effectiveness verification and recurrence visibility instead of record closure alone

QAI-assisted quality reviews, investigations, pattern detection and recommended next steps

Works With What You Have

Your current systems remain the source of truth.

Connect directly where data is accessible. Use EdgeVISS where operational data is trapped inside machines, controllers or industrial protocols.

Excel and existing quality recordsERP / MES / QMSInspection dataSPC measurementsInternal rejectionCustomer complaints8D / CAPAPFMEAControl PlansMSA / PPAPAudit findingsWarranty
Operational Outcomes
Lower cost of poor quality by prioritizing the losses that matter most
Reduce quality administration, searching and report preparation
Accelerate investigation and corrective-action discipline
Strengthen prevention by connecting failures back to PFMEA, Control Plans and process controls
Build organizational quality memory across plants, products, processes, customers and suppliers
Deployment

Designed for industrial architecture

Deploy in the architecture that fits the plant, data-governance and latency requirements. Access remains governed and operational experts retain decision authority.

CloudOn-premiseEdgeHybrid
Product case study

Commercial Vehicle Warranty Analysis: Closure Within a 45-Day SLA

See how Qualitiviss connected product traceability, stakeholder ownership and ticket closure, with QAI accelerating analysis.

Read case study
Application Layer + Decision Layer

Qualitiviss captures, controls and connects your quality processes. QAI analyzes context, surfaces patterns and assists decisions. Your quality team validates, approves and acts.

Explore QAI
Start With One Real Decision

See what Qualitiviss finds in your own operational data.

Begin with one dataset, one recurring problem and one decision your team needs to improve.

Start With One Quality Problem
PART OF CONNECTED INDUSTRIAL INTELLIGENCE

Start with Qualitiviss. Connect more when value is demonstrated.

Each Dataviss application can deliver independent value. Supported integrations can progressively connect operational context across functions. Your teams retain authority over critical decisions.

Explore the Dataviss ecosystem