Start local
Treat Indonesian language and operating context as part of the system behavior, not a translation layer added at the end.
About Verune
Verune Labs is building an independent evaluation and assurance practice for consequential agent workflows, beginning with the language and operating complexity of Indonesia.

Company
Verune Labs was founded in July 2026 in Jakarta, Indonesia by Fadli Adrian. We are building independent AI agent evaluation infrastructure for consequential real-world workflows.
The thesis
Agent failures emerge where language, local convention, policy, tools, and recovery meet. Verune makes those intersections observable before teams expand into real customer workflows.
Treat Indonesian language and operating context as part of the system behavior, not a translation layer added at the end.
Tie every important claim to a reproducible interaction, observed state, and consequence a team can inspect.
Optimize the evaluation for a concrete launch or remediation decision rather than an abstract benchmark score.
Operating principles
Begin with the workflow outcome and risk boundary, then choose the scenarios that make the decision clearer.
Prefer captured behavior and system state over claims about what the agent should have done.
State what was not tested and avoid presenting a bounded evaluation as universal proof of reliability.
Structure evidence so product and engineering teams can reproduce, prioritize, fix, and retest it.
Engineering and evaluation
Verune is building evaluation infrastructure for AI agents across scenario generation, trace analysis, evidence synthesis, adjudication, and regression testing. Claude Code is part of our engineering workflow, while we are expanding Claude into internal evaluation workflows for analyzing transcripts and tool traces, generating localized test scenarios, and structuring reproducible findings.

Founder
Fadli works directly with teams to scope launch risk, review evidence, and translate observed failures into engineering decisions. Verune is founder-led, Indonesia-first, and designed to compound each engagement into a stronger evaluation method and scenario corpus.
Meet Fadli on LinkedInNext step
If your team has a working agent and a consequential decision, bring the real launch question.