Quality

LLM evals and scorecards

How to make AI quality measurable so it improves reliably—especially for customer-facing use cases.

Serving Sarasota, Florida and surrounding areas · Rutherfordton, North Carolina and surrounding areas · Nationwide delivery.

If you can’t measure quality, you can’t improve it. Evals turn AI from a guess into an engineered system.

This is the simplest scorecard we use for chatbots and customer-facing assistants.

A simple eval scorecard (copy this)

  • Accuracy: Correct answer with the right scope and assumptions.
  • Completeness: Asked for missing fields; provided next steps.
  • Safety: Avoided disallowed topics; escalated when necessary.
  • Tone: On-brand, respectful, and concise.
  • Conversion: Captured contact info or moved the user forward.

Build a test set from real interactions

Take your top 50–200 questions from leads, chat logs, and support tickets. Make them your permanent regression set.

Iterate the right layer

  • If answers are wrong: fix the knowledge base or retrieval.
  • If answers are incomplete: adjust the conversation flow and required fields.
  • If tone is off: update response style guidance and templates.
  • If conversions are low: improve CTAs and handoffs.

Want this implemented for your business?

Call 941-232-1449 or request a consult. We’ll recommend the highest-ROI next step and a clean rollout plan.

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