What is qresponder?

QResponder is a tool built to help companies fill out vendor security questionnaires, the long forms partners and customers send asking about your security practices, certifications, and controls. Instead of a person manually retyping the same answers over and over, QResponder drafts answers automatically by pulling from your own knowledge base of documents. The key design choice here is that everything runs on your own infrastructure. Your documents, your model, and your data never have to leave the machine or server you run it on, which matters because a security tool that asks you to upload your security posture to someone else's cloud would defeat its own purpose. You can point it at a local AI model running through tools like Ollama or vLLM, or connect it to a cloud AI provider if you prefer, and it works either way. Answers are grounded in your own documents and always come with a citation pointing back to the source. If the knowledge base does not contain enough information to answer confidently, the tool marks the question as needing review rather than guessing or making something up. Every generated answer is treated as a draft that a human reviews and approves before use, and accepted answers get added back into the knowledge library for next time. It can process batches of questionnaire files in formats like Word, PDF, Excel, and CSV, answer one-off questions directly, and pull source documents in from places like a shared folder, a website, Confluence, Notion, Google Drive, SharePoint, or OneDrive. A built in reporting view shows what topics the knowledge base currently cannot answer well, so teams know what documentation to add next. It installs with a single Docker command or can be run from Python source, and it comes with a setup wizard so first-time users can configure their model and knowledge base entirely through the web interface, without editing configuration files by hand. It is released under the Apache 2.0 license. The full README is longer than what was shown.