The purpose of this document is to align on the initial design of Reply-O-Meter. Everything here is very early and likely to change.

## Overview
The following is a product-oriented view of all the stages that need to happen in the final V1 product:

*Data Ingestions*
Input: raw photos
Output: List of Artifacts that link the raw photo with a textual representation
1. Ingest all of the raw data files. Photos of letters, postcards, and photos.
2. Digitization: conversation of the data to a textual representation.

*Data Normalization*
Input: List of Artifacts
Output: Graph of Entities (Person, Location, and Event)
1. Metadata: extract the Metadata on the Entities that each Artifact refers to, such as Person, Event, and Location
2. Normalization: translation of all material to one internal language (e.g. English)
3. Artifacts: creating Artifacts from joint raw material. Example: photos of person and the name/time from the photo's backside.
4. Reconciliation: Create and/or Update existing Entities based on the information from the new Artifacts.

*Browser*
Input: Graph of Entities
Output: Updates to Artifacts and/or Entities
1. Feedback: User may correct any of the Ingestion or Processing steps, which will retrigger the rest of the flow.
2. Tuning: Will trigger model training/tuning if relevant.

*Story Creator*
Input: Graph of Entities
Output: Story
1. Chat Agent: User can chat with an Author to create stories based on the known Entities.

*Graphic Artist*
Input: Story, Graph of Entities
Output: Graphic Novel
1. People: Given a style, create visual representation for each Person across their life.
2. Supporting Material: Gather maps of the Location and the relevant Events.
3. Create a graphic novel based on the story.