A wealth management firm wants to build an AI assistant to help financial advisors draft personalized investment recommendations for high-value clients. The firm faces two major challenges: The AI must provide advice based on the firm's proprietary, up-to-the-minute market analysis, not on the model's general, outdated knowledge. Due to strict regulatory compliance and the high financial stakes, any final recommendation sent to a client must be flawless and verified for accuracy and suitability. Which combination of techniques is essential to address both of these challenges effectively?