License how you actually resolve a customer case: the ticket, the policy you applied, the reply, the exception, the refund or refusal. This is the training set for customer agents — and the eval set for whether they are allowed to speak.
This venue is a Wing in your Human architecture. Every exercise creates Rooms organized by Hall type. Data quality is tracked via Knowledge Graph triples.
Meet all milestones to unlock buyer engagement. Hybrid threshold — both content volume AND time consistency required.
Entries
Active Days
Min Days
Generic ‘be nice’ data produces agents that refund everything or refuse everything. Buyers pay for policy-faithful traces from people who have closed real queues.
5–8 hours initial, then 30 min/week · 4 steps · Each step builds your architecture
Case traces (JSON: issue, policy, reply, exception, outcome)
When readiness is achieved, an AAAK-compressed summary of your data is generated for buyer evaluation — privacy-preserving, compact, and instantly readable by any AI system.
Enterprise customer agents trained on expert resolution traces.
AI support for large brands. Buys expert ops traces and evals.
Fin needs human policy application, not generic chat.
Places support and ops experts with AI buyers.
Open the Data Builder to complete guided exercises. Each entry builds Rooms, Halls, and Knowledge Triples in your Human architecture — reaching buyer readiness in 30–60 days.