A retail company wants to deploy a generative AI chatbot to assist customers with product recommendations. The chatbot must align with the company's brand voice and provide accurate, up-to-date information. Which strategy should the company prioritize when developing this solution?
Trap 1: Use a generic pre-trained model without customization to reduce…
A generic model lacks brand-specific knowledge and may produce off-brand responses.
Trap 2: Deploy a large language model with a feedback loop to iteratively…
Feedback alone does not guarantee data freshness or brand alignment without grounding.
Trap 3: Train the model on public customer reviews to capture common…
Public reviews may not reflect the company's brand voice and can introduce biases.
- A
Ground the model with proprietary product data and brand guidelines in a retrieval-augmented generation (RAG) architecture.
RAG with curated data ensures responses are accurate, up-to-date, and on-brand.
- B
Use a generic pre-trained model without customization to reduce development time.
Why wrong: A generic model lacks brand-specific knowledge and may produce off-brand responses.
- C
Deploy a large language model with a feedback loop to iteratively improve responses.
Why wrong: Feedback alone does not guarantee data freshness or brand alignment without grounding.
- D
Train the model on public customer reviews to capture common preferences.
Why wrong: Public reviews may not reflect the company's brand voice and can introduce biases.