qmd Local Searchv1.0.0

Developers use qmd to quickly locate specific code snippets, configuration files, or API documentation within large project repositories. It replaces slow 'find' commands with fast, semantic-aware searches, improving productivity during debugging or feature implementation.

Researchers and students index their markdown notes, papers, and datasets to perform combined keyword and semantic searches. This helps in gathering relevant literature or findings efficiently, supporting literature reviews and hypothesis testing without relying on cloud services.

IT teams or support staff use qmd to search internal documentation, troubleshooting guides, and config files stored locally. It enables fast retrieval of solutions or procedures, reducing resolution times and maintaining data privacy by avoiding external APIs.

Writers and content creators index their markdown drafts, articles, and resources to find related content or references. Semantic search helps in discovering themes or ideas, streamlining the writing process and ensuring consistency across documents.

Offer a free basic version for individual users with limited collections or search features, and a paid premium version for teams with advanced features like collaborative indexing, priority support, and enhanced model options. Revenue comes from subscription fees.

Sell licenses to large organizations needing secure, local search across internal documents, codebases, and proprietary data. Include customization, integration with existing tools, and dedicated support. Targets industries with strict data privacy requirements.

Release qmd as open-source software to build a community and drive adoption, while offering a managed cloud-hosted version for users who prefer convenience. Revenue is generated from hosting fees, additional storage, and premium support services.