Alignmenter – Measure brand voice and consistency across model versions

Show HN: Alignmenter – Measure brand voice and consistency across model versions

Alignmenter – Measure brand voice and consistency across model versions is active in the show hn launch space.

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I built a framework for measuring persona alignment in conversational AI systems.*Problem:* When you ship an AI copilot, you need it to maintain a consistent brand voice across model versions. But "sounds right" is subjective. How do you make it measurable?*Approach:* Alignmenter scores three dimensions:1. *Authenticity*: Style similarity (embeddings) + trait patterns (logistic regression) + lexicon compliance + optional LLM Judge2. *Safety*: Keyword rules + offline classifier (distilroberta) + optional LLM judge3. *Stability*: Cosine variance across response distributionsThe interesting part is calibration: you can train persona-specific models on labeled data. Grid search over component we

Alignmenter – Measure brand voice and consistency across model versions is positioned in show hn launch, a segment that rewards a clear, focused offering.

Directory data places it at the Show HN launch stage.

Website: www.alignmenter.com