Understand what must be preserved
Assess the existing system, its business or engineering logic, dependencies and the evidence needed for a safe transition.
Reliability
and control
Legacy Modernization & Migration
Modernize complex legacy systems without sacrificing reliability.
We help organizations assess, transform and migrate legacy applications, engineering systems and workflows using the right combination of deterministic conversion, automation, validation and selective AI. The focus is on reducing migration risk, preserving business logic and creating a maintainable path forward.
- Legacy Assessment
- Migration Architecture
- Automated Conversion
- Rule-Based Transformation
- AI-Assisted Gap Resolution
- Automated Validation
- Computer Vision
- Human-in-the-Loop
- Modernization Governance
Our approach
Modernization Starts With Understanding What Must Be Preserved
Safe modernization begins by understanding the existing logic and evidence. We automate known transformations, use selective AI only for genuine gaps and validate each transition with traceable rules and human review where needed.
Automate deterministic change
Turn repeatable conversions into governed rules and automate migration steps wherever transformations are known and testable.
Resolve genuine gaps
Use selective AI for unresolved or ambiguous mappings, retain human approval and progressively convert validated discoveries into versioned rules.
Validate every transition
Automate testing and validation, preserve traceability and govern each release so modernization reduces risk instead of relocating it.
Proven in complex transitions
Selected Case Studies
Explore modernization work spanning industrial engineering systems, AI-assisted conversion, computer-vision validation and analytical instruments.
Industrial Engineering Modernization Automation Program
Business Problem
Modernizing legacy industrial engineering environments required multiple repetitive conversion, assessment and validation activities across a large engineering-system modernization journey.
Solution / Approach
Provided program-level solution architecture across six coordinated automation workstreams covering engineering conversion, assessment and validation. Defined solution boundaries, integration patterns and deterministic-vs-AI decision strategies across the portfolio.
Outcome
Created a coordinated modernization approach instead of disconnected utilities. Automated testing reduced a validation activity from approximately 4 months to about 1.5 days per project.
Technology / Capability
- .NET
- Python
- Automation
- Industrial Modernization
- Architecture Governance
AI-Assisted Graphics Modernization
Business Problem
Legacy industrial graphics needed conversion to a modern target platform, but not every source-to-target mapping could be represented safely by fixed rules.
Solution / Approach
Reverse-engineered proprietary source structures and analyzed source/target graphics. Derived deterministic mappings for known transformations and designed an AI-assisted gap-resolution approach using retrieval, structured LLM outputs, confidence/evidence validation and human approval. Validated discoveries could then become versioned deterministic rules.
Outcome
Created a modernization strategy designed to improve consistency and explainability while progressively reducing repeated LLM usage and long-term AI cost.
Technology / Capability
- Python
- Azure OpenAI
- Azure AI Search
- RAG / Embeddings
- Structured Outputs
- Rule Repository
Computer Vision for Automated Migration Validation
Business Problem
Migration teams needed a faster and more consistent way to compare legacy and converted engineering graphics despite differences in color, scale and image boundaries.
Solution / Approach
Developed an image-comparison approach using .NET and OpenCV, including color neutralization, scale normalization, black-and-white conversion, cropping and visual-difference analysis.
Outcome
Enabled automated visual-comparison capability to support migration validation and reduce dependence on purely manual inspection.
Technology / Capability
- .NET
- OpenCV
- Image Processing
- Computer Vision
- Automated Validation
Legacy Analytical Instrument Software Engineering
Business Problem
A mature analytical-instrument product contained long-standing software defects and required ongoing release engineering against physical gas/liquid analysis equipment.
Solution / Approach
Worked in a restricted laboratory environment, deployed code to analytical instruments and resolved a long-standing memory-management/pointer defect. Subsequently developed a new .NET wizard component within a short delivery window.
Outcome
Resolved a defect that had persisted across multiple releases and successfully took a new .NET component live within 15 days.
Technology / Capability
- Embedded C++
- .NET
- Analytical Instruments
- Memory Management
- Life Sciences
Modernize with a controlled path forward
Planning a Legacy Modernization?
Start by understanding what must be preserved, what can be automated and where migration risk really sits. We can help assess the current environment, define the modernization architecture and identify opportunities for automation.