See the Defect. Understand the Pattern. Improve the Process.

From Individual Inspections to Connected Quality Intelligence.

Visual Defect Analysis

Review product images for potential scratches, cracks, dents, surface irregularities, missing components, and other visible defects.

Quality Analytics

Explore defect patterns by product, machine, batch, shift, production line, and defect category.

Root-Cause Investigation

Compare available quality and production information to investigate possible contributing factors.

Corrective Action Management

Record issues, assign actions, monitor progress, and document outcomes.

PROPOSED CAPABILITY

The Defectra Quality Console

Overview · Inspection Records · Defect Categories · Quality Trends · Corrective Actions · Reports

Inspections Reviewed: 1,240 · Defect Records: 86 · Open Actions: 12 · Most Common Category: Surface Irregularity

Illustrative Demo Data — Not Actual Customer Results

v0.9 · concept build

A Clearer Path From Inspection to Action.

01 — Collect

Upload inspection images and import available production or quality records.

02 — Analyze

Organize inspection information and evaluate potential visible defects using computer-vision workflows.

03 — Investigate

Explore recurring patterns and compare available production context.

04 — Improve

Track corrective actions and review subsequent quality information.

Inspect an Image. See the Intended Workflow.

DEMO · NO INFERENCE

No detection is performed in this demo

See Patterns That Individual Inspection Reports Cannot Explain.

Defect trends over time · Defects by production line · Shift-wise comparisons · Batch-level analysis · Defect category distribution · Corrective-action status

Illustrative demo data — not actual customer results. Observed correlations and patterns require engineering review before they can be treated as causes.

Designed for the Realities of Manufacturing.

Plastic Injection Moulding

Surface imperfections, flash, sink marks, and appearance-related inspection.

Automotive Components

Component inspection records and recurring quality issues.

Metal Fabrication

Scratches, dents, surface irregularities, and weld appearance.

Electronics Assembly

Missing components and visible assembly defects.

Packaging and Consumer Goods

Print issues, missing labels, packaging appearance, and product presentation.

Target industries — not claimed customer deployments

A Practical Technical Foundation for Industrial Quality Workflows.

Inspection Images and Data → Processing and Analysis → Quality Records → Analytics and Corrective Actions.

Frontend

React and TypeScript

Backend

Python and FastAPI

Computer Vision

OpenCV and PyTorch

Database

PostgreSQL

Deployment

Cloud or customer-controlled infrastructure, depending on implementation requirements

Future integrations

Industrial cameras, ERP, and MES systems

Planned NVIDIA Stack

• CUDA GPUs for training the defect-detection models (planned)
• TensorRT for optimized defect-classification inference (planned)
• NVIDIA Triton Inference Server for model serving inside the processing engine (planned)
• NVIDIA Jetson as the edge option for in-line camera inspection (planned)

Proposed architecture — not every integration or AI feature is operational

Start With One Meaningful Quality Problem.

1. Understand the manufacturing process.
2. Select a priority defect category.
3. Review available images and quality records.
4. Evaluate a focused prototype against agreed criteria.
5. Discuss the scope of a potential pilot.

Building Software for Practical Industrial Problems.

Polystrat Technologies Private Limited is an Indian software technology company developing Defectra, a proposed manufacturing defect intelligence platform focused on visual inspection workflows, quality analytics, and corrective-action management.

Legal Name: Polystrat Technologies Private Limited

CIN: U22209TZ2025PTC035116

Status: Active

Incorporated: June 21, 2025

Address: Door No. 108/2, Ravindranath Tagore Road, Coimbatore North, Coimbatore, Tamil Nadu – 641006, India

Directors: Kusum Meena and Smt Priyanka Ghai

Product Developer: Mahesh Seth

Questions, Answered Honestly.

What is Defectra?

Defectra is a proposed manufacturing defect intelligence platform designed to support visual inspection workflows, quality analytics, and corrective-action tracking.

Does Defectra perform real-time inspection?

Real-time inspection depends on the implemented pipeline, supported equipment, and validated deployment.

Can we start with image uploads?

The proposed initial workflow is designed around image uploads and structured data imports, subject to the capabilities implemented in the product.

Can Defectra connect to ERP or MES systems?

Integration feasibility depends on the available interfaces and the customer’s technical requirements.

Does Defectra automatically determine root causes?

It is intended to help teams investigate patterns and possible contributing factors. Engineering teams must validate conclusions.

How can we discuss a pilot?

Use the enquiry form or contact the company directly.

Let’s Discuss Your Manufacturing Quality Challenge.

Tell us about your inspection process, the defects you want to investigate, and the quality information available to your team.

Polystrat Technologies Private Limited · Phone: 9978800198 · Company Email: [email protected] · Developer Email: [email protected] · Website: polystratstack.com

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