Define what reliable means.
Set explicit reliability objectives around agent outcomes—not generic system availability alone.
Agent Reliability Engineering
Define reliability objectives, continuously measure production reliability, understand behavioral coverage, and make auditable decisions about whether your agents are ready for production.

The reliability layer
Reliability engineering asks whether the system can be trusted to operate in production. Gentlity complements the tools already in your agent stack by turning their evidence into measurable objectives, governed coverage, and deployment decisions.
How Gentlity works
Keep your agents, evaluations, and observability stack. Add a reliability assurance layer that makes each decision explainable.
Core capabilities
Gentlity keeps the signals that matter separate, then connects them through explicit policy.
Set explicit reliability objectives around agent outcomes—not generic system availability alone.
Track reliability outcomes while keeping agent performance distinct from the health of the measurement system.
See whether an aggregate reliability number hides important, unmeasured agent behaviors.
Govern operations using SLO state, reliability evidence, burn rate, and journey coverage.
Provide delivery workflows with explainable ALLOW, WARN, or BLOCK decisions. Gentlity records the decision; your systems retain control.
Product
Explore sanitized views from the current Gentlity operations interface. Reliability, coverage, evidence, and deployment state remain independent, reviewable facts.

Product interface shown with synthetic names and data. Availability is limited to early-access engagements.
Fits your stack
Gentlity is a vendor-neutral reliability assurance layer. Evidence can come from the open-source Agent Reliability SDK, OpenTelemetry-compatible systems, supported adapters, or your own bounded integration.
Privacy-conscious by design
Gentlity is designed around minimal, structural reliability evidence. Its core reliability model does not require unrestricted collection of raw prompts, model responses, or tool payloads.
Early access
We are working with teams running AI agents in production.