Privata is private AI for responding to RFPs, RFIs, DDQs, and security questionnaires, without sending sensitive content to shared AI models. It extracts every question and requirement from an RFx, drafts confidence-scored answers grounded in your own approved content, and lets your team review and export submission-ready responses. Built for proposal teams in regulated industries, where bid content cannot be exposed to public AI.
In practice, Privata works in three steps. Ingest: it reads the full RFx and pulls out every question, requirement, and deadline. Create: it drafts cited answers from your document library and past responses, with a confidence score on each. Respond: your team reviews the low-confidence answers first, approves rather than rewrites, and exports a submission-ready file. Accepted answers are saved back for reuse, so the next proposal starts further ahead.
Privata runs where your data is allowed to live: multi-tenant cloud, a single-tenant instance on your own subdomain, or self-hosted via Docker, Kubernetes, or Azure AKS. LLMs run inside your approved environment, so sensitive RFx content never reaches an outside model. For federal teams, Privata connects to SAM.gov, so you can open an opportunity as a project in one click and go from discovery to response without copy-paste.
Key capabilities include automatic requirement extraction; confidence-scored, cited answers; a collaborative Response Editor; an Approved Answers Library for reuse; private document search across your knowledge base; the Proposal Collateral Studio for capability statements, past performance, technical approach, and presentation decks; Contract Opportunity Search for SAM.gov; submission-readiness scoring; and a Chrome extension that fills web-based submission portals. Privata reads PDF, Word, Excel, PowerPoint, CSV, XML, Markdown, images, and URLs, and exports to DOCX, PDF, XLSX, PPTX, and CSV, or merges answers back into the buyer's original template.
