Cortexia solutions

// service_modules

Three Focused Computer Vision Services

Each module addresses a distinct category of visual intelligence challenge — select the one that matches your current need, or discuss a combined approach.

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// methodology

How We Approach Each Engagement

01

Site Assessment

We begin by understanding your environment — physical setup, camera infrastructure, existing systems, and the specific visual problem to be solved.

02

Data Strategy

We assess your existing image samples, identify gaps, and plan a data pipeline — collection, labelling, augmentation — suited to your model requirements.

03

Training & Validation

Model development, iterative training, and structured validation against held-out test data — with a written validation report produced before deployment.

04

Deploy & Handover

Integration into your environment, go-live support, and a full documented handover — including model weights, configuration files, and maintenance guidance.

Visual Inspection Quality Control
mod_01 / visual_inspection
From RM 8,000

// solution_01

Visual Inspection & Quality Control

Development of computer vision systems for manufacturing quality control — detecting defects, anomalies, and non-conformities on production lines. The service includes camera placement advisory, model training on client sample data, and integration with existing manufacturing execution systems. Suited for Malaysian manufacturers seeking more consistent inspection outcomes.

Key outcomes

  • Defect detection at machine speed — independent of operator fatigue
  • Consistent inspection criteria across all production shifts
  • Documented defect categorisation with visual evidence logs
  • MES integration for real-time quality dashboards
  • Camera placement advisory included in scope

Engagement steps

1.

Site visit and production line assessment — camera geometry, lighting, defect category inventory

2.

Sample data collection and labelling pipeline setup

3.

Model training, iterative refinement, and structured validation

4.

MES integration and go-live with documented handover

Enquire About This 8–14 weeks typical

// solution_02

Object Detection & Tracking

Custom object detection model development for applications in retail analytics, warehouse management, and security monitoring. The engagement covers dataset preparation, model training and optimisation, and deployment in edge or cloud environments. Designed for organisations that need to understand spatial activity from video feeds.

Key outcomes

  • Real-time object detection from existing camera infrastructure
  • Multi-object tracking with persistent IDs across frames
  • Zone occupancy and footfall analytics for retail or warehouse use
  • Edge deployment option for on-site low-latency inference
  • Alert and reporting outputs integrated with your existing tools

Engagement steps

1.

Requirements review — target objects, tracking logic, deployment constraints

2.

Dataset preparation and annotation for target object classes

3.

Model training, optimisation for target hardware, and validation

4.

Deployment, integration testing, and handover with documentation

Enquire About This 5–10 weeks typical
Object Detection Tracking
mod_02 / detection
From RM 6,500
Image Classification Tagging
mod_03 / classification
From RM 4,000

// solution_03

Image Classification & Tagging

Building image classification systems that categorise visual content for asset management, content moderation, and cataloguing purposes. Services include training data curation, model development, API integration, and ongoing model performance monitoring. Applicable to media companies, e-commerce platforms, and digital asset managers.

Key outcomes

  • Structured categorisation of large image libraries at scale
  • REST API integration for pipeline-based asset processing
  • Custom taxonomy built around your content or product structure
  • Ongoing monitoring to flag model drift over time
  • Suitable for content moderation workflows with human-in-loop option

Engagement steps

1.

Taxonomy design — define categories, review sample content

2.

Training data curation and labelling quality assurance

3.

Model development, fine-tuning, and validation testing

4.

API integration, performance baseline documentation, and handover

Enquire About This 4–6 weeks typical

// solution_matrix

Choosing the Right Module

Use this matrix to identify which service aligns with your current need. Multiple modules can be combined in a phased engagement.

Feature Visual Inspection Detection & Tracking Classification
Best for manufacturing environments
Retail & logistics applications
Media & content management
Camera placement advisory
Edge device deployment
API integration
MES integration
Starting priceRM 8,000RM 6,500RM 4,000
Typical timeline8–14 weeks5–10 weeks4–6 weeks

// shared_standards

Technical Standards Across All Modules

Data Security

All client data handled under NDA and PDPA-aligned practices. Secure storage during training, deletion or transfer at project close per your policy.

Performance Benchmarking

Every model is evaluated against agreed performance metrics — precision, recall, F1. Results documented in a written report delivered before production go-live.

Support Coverage

Post-deployment support terms discussed during scoping. Direct contact with the delivery engineers for questions or issues — no routing through a generic helpdesk.

Version Control

Model weights, configuration files, and training pipelines are version-controlled and handed over. Retraining from a documented baseline remains straightforward after handover.

Fixed Written Scope

Work begins from a written quote with defined deliverables. No scope adjustments without explicit client approval. No ambiguous billing.

Model Monitoring

Post-deployment accuracy tracking available across all modules. When drift is detected, we raise it proactively and propose a retraining schedule.

// next_step

Not sure which module fits your situation?

Send us a brief description of the visual problem you are trying to solve and we will advise on scope, feasibility, and the right starting point — without obligation.

Describe Your Challenge