Eterno.
A continuation, not a copy.
Independent student research project. No human data collected. Early build phase only.
Eterno is a living memory system designed to preserve emotional continuity with explicit consent, local preprocessing, family-governed review controls, and approved training workflows in ReLive datacenters. It is built for remembrance, not replacement.
"Goodbye is a conversation, not a sentence."
Every capture layer is opt-in and scoped. Families receive visibility and control surfaces by design.
Signals are preprocessed locally first, reviewed in the companion app, and only approved data is used for model training.
Eterno is designed with healthy boundaries, transparency, and paced interaction rather than dependency loops.
Early build.
"A letter they never got to write — that can still answer your questions."
Common questions about Eterno.
Public-safe overview of how we approach memory, consent, safety, and family control.
Is Eterno trying to bring someone back?
No. Eterno is designed as living memory, not resurrection. The goal is emotional continuity with clear boundaries, not replacement.
Who controls the experience?
Families remain in control. Consent settings, scope, and interaction boundaries are designed to be visible and adjustable.
How is privacy handled?
Eterno uses a staged workflow: local preprocessing first, family review and filtering in the app, then approved summaries and selected data are used for training in ReLive datacenters.
Can this create emotional dependency?
The product is designed with grief-aware pacing and healthy boundaries, including a gradual interaction model rather than always-on engagement.
What if a response feels inaccurate?
Safety and constraint layers are part of the design, with family-governed controls to reduce harmful or out-of-scope interactions.
What is the current stage of Eterno?
Eterno is in early build. Current work focuses on consent workflows, review controls, safety layers, and transparent training governance.