Behavioral alignment
Your principles,
put into practice.
We help AI teams define how their models should behave in difficult conversations, identify where they fall short, and develop expert training data to improve them. Then we test again on unseen situations.
In development
A question of judgment
Supportive, without
simply agreeing.
Your assistant should acknowledge a person’s feelings while remaining honest about uncertainty. We identify where that balance breaks down, create expert-reviewed examples, and measure whether an updated system handles new conversations better.
One example of the behavior we could work on together.
Define the behavior
In developmentWe work with your team and relevant experts to turn broad principles into clear expectations, including the difficult cases where priorities compete.
- An agreed scope and behavior specification
- Examples of appropriate responses and meaningful failures
Find where it falls short
In developmentWe test the current system across realistic conversations, including changing context, repeated pressure and everyday cases that should still receive useful help.
- A baseline evaluation with reviewed transcripts
- Failure patterns, reviewer reasoning and documented disagreement
Build better examples
In developmentWe develop data around the failures that matter. Your team can use it in its training process; together, we examine which changes improve the intended behavior.
- Expert demonstrations and response comparisons
- Preference rationales and review criteria for your training workflow
Measure what changed
In developmentWe compare the original and updated systems on separate, unseen situations. Reviewers assess responses without knowing which version produced them.
- Repeated runs, uncertainty and checks for regressions
- A report on improvements, remaining failures and tradeoffs
A focused first engagement.
One behavior, one product context and one improvement cycle. Built for teams developing conversational AI, with an agreed scope and evidence they can inspect.
Our focus is human interactions, emotional context and conversational safety. Findings describe the behavior tested, rather than certifying a model’s overall safety.