Code Repository Decoding & LLM Dataset Fine-Tuning

The Challenge

A software-as-a-service developer needed to optimize onboarding time for new software engineers and build custom model fine-tuning pipelines. Their legacy application comprised thousands of unstructured code repositories lacking standard documentation. At the same time, formatting and sanitizing raw development logs into high-quality instruction-tuning datasets for specialized model fine-tuning was tedious and error-prone.

The Engineered Solution

Jampuk Intelligence designed and implemented an automated Code Decoding & Dataset Validation pipeline powered by our autonomous digital workers and Document Intelligence.

• → Automated Repository Mapping: Background workers parse codebases, tracing dependency structures, function signatures, and building semantic search graphs stored in Weaviate.
• → Dataset Sanitization & Tokenization: Custom sanitizers scrub raw developer logs, removing proprietary database connection strings and secret tokens automatically.
• → Continuous MLOps Validation: Open-source grounding guardrails integrate into CI/CD pipelines, evaluating datasets for semantic drift and formatting errors before training.