AI-Powered Design Defect Identification for a Confidential Client -

Use Case: AI-Powered Design Defect Identification for a Confidential Client

Industry: Engineering Design
Solution: AI-Driven Defect Detection & Process Optimization (Ongoing Engagement)

Problem Statement

Manual design verification in engineering processes is time-consuming, repetitive, and heavily dependent on manpower.
A US-based engineering design firm approached AerixNova to explore how AI could:

Automate defect identification
Reduce manual verification effort
Improve overall operational efficiency

The goal was to adopt a structured, low-risk approach — starting with a single-use case Proof-of-Concept (PoC) before scaling to a full AI transformation.

Solution

Our Approach: AerixNova AI Engagement Framework

This project is currently an ongoing engagement — delivered in phased milestones using our proven 3-step AI Evaluation Process.

1. Feasibility Study — Explore Possibilities

High-level AI readiness assessment
Stakeholder interviews to understand business challenges
Opportunity mapping for AI-driven automation

Deliverable: A detailed AI Opportunity Report outlining feasibility, potential use cases, and estimated business impact.

2. Standard AI Evaluation — Assess & Visualize Value

Data feasibility checks and preliminary analysis
Early AI insights leveraging client data
Demonstration of how AI could drive operational efficiency

Deliverable: An Interactive AI Value Dashboard Prototype visualizing potential impact areas for defect detection automation.

3. Advanced AI Strategy — Execute with Proof of Concept

Custom AI model development (In Progress)
Scenario-based ROI projections
Clear transformation roadmap with budget estimation and implementation milestones

Deliverable: A phased AI Transformation Roadmap aligning technology with business objectives.

Ongoing Impact

This project is currently in active development — with early phases completed and PoC work in progress.
Our engagement has already enabled the client to:

Visualize the potential to reduce manual hours spent on repetitive verification tasks
Identify opportunities to optimize manpower allocation
Gain early insights into operational efficiency improvements
Align internal teams on the strategic value of AI in design defect identification

The next steps focus on PoC refinement, AI model validation, and preparation for broader implementation across other processes.

Why AerixNova

Our AI Engagement Framework enabled the client to:

Explore AI opportunities with minimal risk
Validate value early before investing in full-scale transformation
Execute an AI strategy aligned with business outcomes and ROI expectations

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