Set explicit objectives
Describe the indicators, targets, and meaningful agent journeys that matter to your system.
Gentlity product
Move from individual evaluation results to explicit objectives, governed coverage, and operational decisions—without replacing your agent or observability stack.
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Reliability lifecycle
Each stage answers a different operational question. Gentlity preserves those distinctions so a green metric cannot hide missing evidence or uncovered behavior.
Describe the indicators, targets, and meaningful agent journeys that matter to your system.
Measure outcomes over time while preserving provenance and the distinction between reliability and measurement health.
Identify material behaviors that are governed, partially covered, or still unmeasured.
Connect SLO state, error-budget burn, evidence health, and coverage to explicit reliability policy.
Produce an auditable ALLOW, WARN, or BLOCK decision for a delivery workflow to consume.
Reliability objectives
Define indicator-specific SLOs, examine the current reliability ratio, and understand remaining error budget and burn rate without averaging unlike objectives together.


Behavioral coverage
Reliability evidence is only useful when its coverage is visible. Declared journeys, structural observations, required indicators, and critical gaps remain explicit.
Deployment assurance
Gentlity evaluates configured conditions and records the resulting ALLOW, WARN, or BLOCK decision with reasons, timestamps, and evidence knowledge. Your CI/CD system remains in control of enforcement.

Built for production AI systems
Works above the agent, evaluator, and observability choices your team already made.
Recorded decisions preserve their reasons and time context for later review.
Policy evaluation returns typed outcomes from explicit configured conditions.
Analyze reliability for selected periods and evidence knowledge without rewriting history.
Core reliability evidence is structural; raw prompts and responses are not required.
Deployment decisions can be consumed by CI/CD workflows without Gentlity owning them.
Early access
We are working with teams running AI agents in production.