Case Study
AI-Powered Code Assistant for Leading Aviation Technology Company
Discover how a major aviation technology company transformed their complex legacy codebase into an intelligent, searchable knowledge system using AI-powered knowledge graphs and semantic code analysis.
Client Overview
A leading international aviation technology company, specializing in sophisticated airport management solutions worldwide, faced critical challenges in managing complex legacy codebases and proprietary systems. The company develops mission-critical technologies including deicing planning systems, airport operations platforms, and custom aviation solutions.
The company sought a solution that could:
Transform complex legacy codebases into searchable, intelligent knowledge graphs
Provide semantic search capabilities across multiple programming languages and proprietary systems
Accelerate developer onboarding and reduce knowledge transfer bottlenecks
Generate comprehensive documentation automatically from code and existing technical materials
Visualize code dependencies and relationships across their sophisticated tech stack
Challenges We Solve
Complex Legacy Codebase Management in Aviation Technology
Aviation technology requires sophisticated, mission-critical systems with proprietary languages, custom frameworks, and distributed technical knowledge across multiple formats
1. Proprietary SDL Scripting Language Complexity
The company’s custom SDL (System Definition Language) scripting created a significant knowledge barrier. New developers struggled with this proprietary language that had no external learning resources or community support.
2. Fragmented Knowledge & Dispersed Business Logic
Critical business logic was scattered across source code, PDF documentation, technical manuals, and tribal knowledge held by senior developers. Understanding deicing algorithms or airport management workflows required extensive detective work.
3. Slow Developer Onboarding & Knowledge Transfer
New engineers required 3-6 months to become productive due to the complexity of interconnected systems, custom frameworks, and undocumented business rules embedded within legacy code.
4. Code Maintenance & Impact Analysis Challenges
Making changes felt like playing Jenga: developers couldn’t easily predict what would break when modifying interconnected systems with multiple dependencies and languages.
5. Limited Test Coverage & Quality Assurance
The custom BITE test framework required specialized configuration knowledge. Most legacy systems lacked comprehensive unit tests, making refactoring and maintenance risky.
Our Solutions
ContextClue as the AI Engine for for Aviation Code Intelligence
Automated Docs Generation
AI-Powered Knowledge Assistant
Dependency & Relationship Graph
Conversational Code Intelligence
1. Auto-Generated Documentation & Technical Overview
2. AI-Powered Knowledge Assistant
- Automatically extracts structure and logic from legacy code
- Identifies declarations, functions, types, and key components
- Useful for onboarding, audits, and modernization planning
- Natural language interface to explore logic, dependencies & purpose
- Provides human-readable explanations of any snippet, class, or function
- Great for developers unfamiliar with legacy syntax or architecture
1. Auto-Generated Documentation & Technical Overview
- Automatically extracts structure and logic from legacy code
- Identifies declarations, functions, types, and key components
- Useful for onboarding, audits, and modernization planning.
2. AI-Powered Knowledge Assistant
- Natural language interface to explore logic, dependencies & purpose
- Provides human-readable explanations of any snippet, class, or function
- Great for developers unfamiliar with legacy syntax or architecture
Want to See ContextClue in Action?
Transform your legacy codebase into an intelligent, searchable knowledge system. Reach out for a custom demonstration tailored to your development workflow.
3. Dependency & Relationship Graph
4. Conversation Code Intelligence
- Automatically builds a graph of files, functions, APIs, or services
- See how components interact across layers
- Useful for debugging, refactoring, or system design reviews
- Uncovers undocumented logic and lost knowledge
- Boosts developer efficiency
- Accelerates IT integration and issue resolution
3. Dependency & Relationship Graph
- Automatically builds a graph of files, functions, APIs, or services
- See how components interact across layers
- Useful for debugging, refactoring, or system design reviews
4. Conversation Code Intelligence
- Uncovers undocumented logic and lost knowledge
- Boosts developer efficiency
- Accelerates IT integration and issue resolution
Role-Based Use Cases for the AI-Powered Code Assistant
As a new developer, I want to…
- search the codebase to identify the right places to write functional tests
- configure and understand the internal test framework (BITE)
- understand the overall impact of my code changes on the system
- detect potential problems in my implementation and track their implications across the codebase
As a developer & lead developer I want to…
- generate a changelog of the last release from commit messages
- automatically create technical documentation for new features introduced in my pull requests
- evaluate and plan the process of code migration and testing
As a manager I want to…
- examine and monitor the test coverage of the codebase
- clearly see how features in the codebase correspond to new feature documentation
- identify potential gaps and risks within the system
Results & Business Impact
Enhanced Code Comprehension
Development teams can instantly understand and modify sophisticated aviation algorithms, reducing reliance on tribal knowledge.
Streamlined Maintenance Operations
Code changes, debugging sessions, and system updates execute with predictable outcomes through comprehensive impact analysis and dependency visualization.
Preserved Institutional Knowledge
Critical aviation domain expertise and business logic captured in permanent, searchable knowledge graphs, protecting against knowledge loss during personnel transitions.
Automated Documentation Excellence
Technical documentation, compliance reports, and system specifications maintain perfect synchronization with actual code implementation, supporting regulatory requirements and operational transparency.