Technical AI Solutions for Production Systems
Three focused service offerings addressing specific AI engineering challenges — architecture design, integration consulting, and specialized model training.
Back to HomeOur Methodology
Quorux engagements follow a structured approach grounded in empirical research and production constraints. We begin with problem definition and requirements gathering to establish clear success criteria, then conduct literature review and baseline establishment to understand current state-of-the-art approaches, followed by candidate solution experimentation with systematic ablation studies, and conclude with deliverable preparation including comprehensive documentation and knowledge transfer sessions.
This methodology ensures that recommendations reflect both what research literature suggests and what operates reliably in deployed systems. We emphasize reproducibility — all experiments include versioned datasets, environment specifications, and detailed procedures allowing independent verification of reported results.
Projects are structured with checkpoint reviews where you can evaluate preliminary results before committing to full scope. If initial experiments reveal that target performance isn't achievable with available data or computational resources, we document why and propose alternatives rather than continuing toward unrealistic goals.
Neural Network Architecture Design
Custom design of neural network architectures optimized for your specific problem space — whether image classification, sequence prediction, graph analysis, or multimodal learning. The service includes architecture research, experimentation with candidate designs, ablation studies, and a final architecture specification with training recipes.
What You Receive
- Architecture research and candidate experimentation across multiple design approaches
- Systematic ablation studies to understand component contributions
- Reproducible experiment notebooks with full training procedures
- Performance benchmarks comparing against baseline methods
- Final architecture specification with hyperparameter recommendations
Project Investment
RM 7,900
Typical Duration
2-4 weeks
AI Integration Consulting
Advisory engagements that help organizations navigate the practical decisions involved in bringing AI into existing technology stacks. The service covers system compatibility assessment, data pipeline requirements, infrastructure sizing, vendor evaluation support, and change management planning.
Deliverables Included
- System compatibility assessment with your current infrastructure
- Data pipeline architecture and infrastructure sizing recommendations
- Vendor evaluation support with comparison matrices
- Change management planning and team capability assessment
- Structured recommendations document with implementation timelines
Consultation Fee
RM 2,300
Typical Duration
1-2 weeks
Optical Character Recognition Customization
Adapting and training OCR systems for specialized document types — handwritten forms, multilingual documents, degraded historical records, or non-standard layouts. The service covers character set expansion, layout analysis tuning, post-processing pipeline development, and accuracy benchmarking.
Service Components
- Character set expansion for specialized document formats
- Layout analysis tuning for non-standard page structures
- Post-processing pipeline development and error correction
- Accuracy benchmarking on your specific document types
- Deployable service with testing tools and documentation
Service Price
RM 3,600
Typical Duration
2-3 weeks
Solution Comparison
Understanding which service best addresses your specific technical challenge.
| Feature | Architecture Design | Integration Consulting | OCR Customization |
|---|---|---|---|
| Custom Model Training | |||
| Infrastructure Recommendations | |||
| System Integration Guidance | |||
| Ablation Studies | |||
| Vendor Evaluation | |||
| Reproducible Experiments | |||
| Deployment-Ready Code | |||
| Investment | RM 7,900 | RM 2,300 | RM 3,600 |
Best For
Teams with defined ML problems needing optimized architectures and training procedures
Best For
Organizations evaluating how to incorporate AI into existing technology stacks
Best For
Teams processing specialized documents that general OCR handles poorly
Shared Technical Standards
Quality practices applied across all solution engagements.
Version Control
All code delivered with Git repositories, environment specifications, and reproducible setup procedures.
Documentation
Comprehensive technical documentation explaining architecture decisions, hyperparameter choices, and deployment considerations.
Testing Procedures
Test suites with unit tests for data processing, integration tests for inference, and validation notebooks.
Security Practices
Work under NDA as standard, compatible with air-gapped environments, adherence to your data governance frameworks.
Performance Benchmarking
Baseline establishment, comparison against published benchmarks, ablation studies to understand component contributions.
Knowledge Transfer
Walkthrough sessions explaining technical decisions, references to relevant literature, support for extending the work.
Ready to Discuss Your AI Challenge?
Whether you need architecture design, integration guidance, or specialized model training, we're here to provide thoughtful engineering and realistic assessments.
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