Verune field notes
Practical evidence for teams shipping AI agents.
Methods, scenario anatomy, and standards translation for consequential voice and chat workflows. Every example is labeled, sourced, and bounded.
Flagship research
From Fluent to Reliable
The research foundation connecting adoption pressure, workflow risk, evaluation design, and launch evidence.
Foundational guides
Start with the decision your evidence must support.
The collection is organized around four buyer questions: what evaluation is, how local workflow context changes correctness, how agents recover from system uncertainty, and how evidence maps to launch governance.
AI agent evaluation is not observability, red teaming, audit, or certification.
A practical map of five related disciplines and the decision each one supports.
Read field guide02Fluent Indonesian is not proof of workflow reliability.
Why local language quality must be tested together with policy, tools, money, time, and recovery.
Read field guide03How to test payment timeout, retry, and human handoff.
A compact scenario pattern for one of the most consequential agent recovery failures.
Read field guide04A practical launch-readiness checklist for tool-using agents.
The minimum evidence a team should assemble before expanding a consequential agent workflow.
Read field guide05Mapping workflow evidence to NIST, OWASP, ISO 42001, and Indonesian guidance.
How standards can structure an evaluation without turning it into an unsupported certification claim.
Read field guideNext step
Apply the method to your own workflow.
Bring one agent, one consequential workflow, and the decision your team needs to make.