NLG Consultation — Design the Right Text Generation System

I will assess your text generation requirements and deliver a written NLG consultation report covering the appropriate generation approach (template-based, neural, or LLM-based), the tradeoffs between control and fluency for your use case, your data requirements, quality evaluation methodology, and a recommended implementation path. NLG approach selection depends heavily on your control requirements — if every generated sentence must be factually grounded in a specific data record with no hallucination risk, template-based or extractive approaches are more appropriate than LLM generation; if natural language quality and variation are the priority and some paraphrase error is acceptable, neural generation delivers substantially better output.

The report covers your generation task characterisation, approach comparison (template, neural seq2seq, or LLM), data requirements, quality evaluation methodology, and a phased implementation roadmap.