Latitude has launched AgentScore, an open-methodology evaluation system that tracks AI agent performance in production across outcome, reliability, cost, speed, and safety.

Static offline benchmarks and raw trace dumps are failing production agents; grounding continuous evaluation in statistical production telemetry is the missing operational standard.

• Holistic trade-off visibility: AgentScore prevents teams from optimizing for a single metric in isolation by penalizing agents that achieve fast execution through hallucinated shortcuts or excessive tool and token spend.

• Statistically grounded gating: Enforcing a 1,000-session minimum and displaying 95% confidence intervals prevents engineering teams from prematurely reacting to noisy, small-sample anomalies.

• Closed-loop remediation via MCP: Bundling failure states into structured issues that can be dispatched directly to coding agents turns production observability into an automated feedback loop for regression testing and code fixes.

• Sample size barrier for early-stage teams: The strict evidence threshold means low-traffic or specialized internal agents will struggle to qualify for scoring, keeping this tool primarily relevant for agents already deployed at scale.