Generic LLMs are excellent for prototyping and drafting, but institutional reporting needs reproducibility, benchmarks, all-comment coverage, and clear governance. Student Voice Analytics provides deterministic, versioned runs, sector benchmarks, TEF-style outputs, and BI exports—built for UK-HE cycles.
For TEF-grade evidence, we prioritise deterministic methods, versioning, audit trails, and sector benchmarks; LLM-based prose generation can sit after governed classification pipelines.
Who is this guide for in universities?
NSS/PTES/PRES/UKES and module evaluation owners
Governance and Data Protection teams needing residency, access control, and auditability
BI teams integrating repeatable outputs into planning cycles
Why look beyond generic LLMs for student comments?
Reproducibility: prompt or model drift undermines year-on-year comparability.
Benchmarks: sector context is essential to prioritise actions.
Residency & privacy: UK/EU processing and audit trails are often required.
Watch-outs: Prompt/model drift, reproducibility, residency, and explainability require strict controls and versioning.
What procurement checklist should we use?
All-comment coverage; HE-specific taxonomy and sentiment
Sector benchmarks; versioned runs; UK/EU residency and audit logs
BI-ready exports; TEF-style documentation
Need clarity?
FAQs about generic LLM alternatives
Quick answers to procurement and implementation questions we hear most often.
Can we still use LLMs?
Yes—use LLMs after governed classification (e.g., Student Voice Analytics) to draft executive-ready summaries while keeping institutional evidence deterministic and reproducible.
Do you send data to public LLM APIs?
Student Voice Analytics executive summaries can be generated by in-house models on owned hardware with UK/EU processing options.
