What is AI Trainer, and when should I use it?

Quick answer

A simple explanation of how AI Trainer helps shape better model understanding.

What it means

AI Trainer helps your team turn positioning, proof points, and differentiators into clearer signals that large language models can understand and reuse more accurately.

Why it matters

Open the matching product area from the main dashboard sidebar so the explanation is tied to the right feature.

How it works

• Start with the core truths you want models to understand about the brand.
• Add clear positioning, audience fit, and proof points.
• Review how those signals align with the prompts you care about most.
• Iterate when outputs show gaps, confusion, or weak recommendation quality.

Helpful tips

• Use specific language rather than broad brand claims.
• Train for clarity, not just creativity.
• Update inputs whenever positioning or proof changes meaningfully.

Possible issues and troubleshooting

• If the feature description seems vague, verify which plan or module is actually enabled for the organization.
• If the outputs look odd, compare the current organization and selected inputs before assuming the feature is broken.
• If the data seems incomplete, confirm the relevant run has finished and the latest setup was saved.

What to do next

Once the feature makes sense, use it in a real workflow and check whether it changes the next decision.