Feed whole codebases to LLMs — compile repositories into one AI-friendly file

Feed whole codebases to LLMs — compile repositories into one AI-friendly file targets a $18.0B = 20M professional developers x $900/year average dev-tool spend total addressable market with low saturation and a year-over-year growth rate of 30%+ (developer AI tools & RAG adoption).

Key trends driving demand: LLM-driven developer workflows -- dev teams increasingly use LLMs for code search, PR summaries, and automated refactors, driving need for repo ingestion tools.; RAG adoption -- retrieval-augmented generation is standardizing how external data is supplied to LLMs, demanding reliable doc ingestion pipelines.; Vector DB commoditization -- managed vector stores and cheap embedding compute make per-repo indexes affordable for teams of all sizes.; Mono-repo & microservices growth -- larger and more distributed codebases increase the friction of ad-hoc context assembly for models..