AI coding for complex codebases
Most models are strongest in common languages because public training data and benchmarks overrepresent Python, JavaScript, and modern web stacks. Cosine is also built for the languages critical systems still run on — COBOL, ABAP, Fortran, Verilog, C, C++, .NET, enterprise Java, and other legacy languages.
Understand the system first
Cosine explores the repository, maps dependencies, identifies key flows, and explains how unfamiliar systems fit together before making changes.
Recover missing knowledge
Generate module summaries, architecture notes, interface documentation, and operational context so critical knowledge is no longer trapped with a small number of specialists.
Change with confidence
Cosine can add tests, create scaffolding, verify behaviour, and prepare reviewable changes before risky refactors or modernisation work begins.
Where niche-language teams use Cosine.
Legacy documentation
Turn long-lived code into architecture notes, onboarding material, module summaries, and operational documentation.
Test scaffolding
Create tests around critical paths before refactoring, migration, or broader modernisation work.
SME support
Help newer engineers understand systems previously maintained by a small number of specialists.
Framework migration
Support incremental movement away from old frameworks, libraries, services, or infrastructure patterns.
Language-specific post-training
Adapt model behaviour to customer-specific languages, coding standards, internal frameworks, and proprietary toolchains.
Secure modernisation
Run modernisation work in the environment your security model requires, including cloud, VPC, on-premises, or fully air-gapped deployment.