When Sullivan & Cromwell had to apologize to a federal judge for AI-generated “hallucinations” in a court filing, it underscored a serious trust gap in professional AI use. Legal briefs, M&A due diligence and financial audits demand accuracy—one stray citation or made-up figure can wipe out weeks of work. That forces lawyers and analysts back into manual fact-checking, nullifying AI’s productivity gains. Korekt steps in as a real-time verification layer. It hooks into any large language model via API or a browser extension and checks every factual claim—legal citations, market stats, financial figures—against primary sources like Westlaw or Bloomberg. Think of it as brakes on generative AI: you still get fast, creative output, but you don’t have to vet every line yourself. On pricing, Korekt offers three SaaS tiers: a Pro Seat for individuals; a Business Tier with team dashboards, compliance logs and audit trails; and an Enterprise API with usage-based fees for firms embedding Korekt into their own tools. They’ll kick off with a freemium “Hallucination Grader” web tool to scan pasted text, plus an open-source library for validating specific data types to attract developers. A “Hallucination Index” site will document AI errors and drive SEO traffic. Competition comes from Thomson Reuters and LexisNexis, which are building in-house AI suites. Korekt’s edge is neutrality—it works with any LLM—and workflow lock-in. Once embedded in a lawyer’s drafting process, removing it means higher risk of errors. The MVP stack could run on FastAPI with Python, use BeautifulSoup and Pandas for scraping and data structuring, and store verification logs in PostgreSQL. A React-based browser extension built with Plasmo ties it all together.