Yellowfin provides embedded analytics with recent AI NLQ (Natural Language Query) capabilities released in version 9.15 (April 2025). The platform offers both Guided NLQ (structured question building) and AI NLQ (free-form natural language powered by LLMs). Enterprise pricing starts around $50/user/month with implementation costs of $5,000-$50,000+ depending on complexity. The platform specializes in embedded analytics—white-labeled BI capabilities integrated into SaaS products and enterprise applications. Features include Signals (automated business monitoring), Stories (data-driven narratives), and collaboration tools. AI NLQ uses configured LLM connections (OpenAI, Azure OpenAI, or custom endpoints) with semantic layer translation. Supports databases through JDBC connectivity including all major platforms. The embedded focus differentiates from visualization-first tools like Tableau. Page should cover: Guided NLQ vs AI NLQ comparison, embedded analytics use cases, implementation requirements, LLM configuration options, pricing model for embedded scenarios, comparison with Looker embedded and Metabase, and version 9.15 AI feature details.