Interior Shopping List Data Model and UI

Status: draft / demo-candidate
Module: Project Blueprints
Related product: interior design procurement automation
Related client / case: Aneta / Zagórzańska
Source: ../intake/2026-06-07-archi-ext-vol3-data-model-ui-beta.txt
Related blueprint: interior-shopping-list-beta.md
Last reviewed: 2026-06-07

Problem

The beta needs a concrete data model and UI structure so the team can capture products, relate them to rooms and categories, and keep uncertain values visible for review.

This blueprint focuses on the item-level model, not just the product story.

Target Users

interior designer,
project coordinator,
client reviewing the list,
implementation team.

Process Flow

Create a project.
Add rooms and batches.
Capture one shopping item at a time.
Store the product record with context.
Keep quantity and confidence visible.
Review uncertain items.
Export the client-facing shopping list.

Data Inputs

project name,
project stage,
purchase batch,
room name,
related rooms,
zone type,
room tags,
product name,
brand,
category,
subcategory,
variant,
unit,
store,
estimated price,
currency,
product URL,
quantity,
quantity source,
quantity status,
usage multiplier,
photo upload,
OCR text,
manual correction,
related document,
recognition status,
review status,
review comment.

Outputs

normalized shopping item record,
shopping list grouped by project, room and category,
list of uncertain items,
exportable client list,
data model ready for future OCR and document parsing improvements.

Automation Scope

The automation should normalize the item record but not pretend to know everything.

Key behaviors:

parse photo text when possible,
propose item fields,
store explicit uncertainty,
keep room and category logic editable,
preserve a link to the source photo or document.

AI Scope

AI should help with:

OCR,
product identification,
rough category suggestion,
store detection,
confidence estimation,
note generation.

Human Review / Validation

Human validation is required for:

room assignment,
multi-room applicability,
quantity,
price,
store confidence,
final review status.

UI Scope

The UI should have 4 core views:

Projects.
Project shopping list.
Add or edit item.
Client export.

The add/edit screen should include:

project context,
room assignment,
product fields,
commercial fields,
quantity logic,
source and review state.

The list screen should support filters:

by room,
by category,
by review state,
by quantity state.

Backend Scope

The backend should persist:

projects,
rooms,
batches,
shopping items,
source media,
review metadata.

It should also support:

filtering,
export,
future OCR enrichment,
future document-linked quantity estimation.

Integrations

photo upload,
OCR service,
PDF / drawing attachments,
CSV export,
later PDF export,
later n8n orchestration.

MVP

The smallest useful version is a single project with:

rooms,
shopping items,
photo upload,
manual corrections,
simple export.

Success Criteria

The MVP works if:

the model can hold a real item without losing context,
uncertain values remain visible,
filters work on the main list,
the exported list is readable for the client,
the team can extend the schema later without rewriting everything.

Out Of Scope

perfect automatic quantity calculation,
full product catalog lookup,
deep integration with every design tool,
all room taxonomies at once,
enterprise permissions and multi-tenant controls.

Risks

overfitting the schema to one project,
too many optional fields without a clear default flow,
unclear distinction between product and item,
confusing room naming,
brittle quantity logic.

Service Model

This blueprint can serve as:

a pilot app,
an internal RSYSTEM utility,
a client-facing beta,
a future branch module of RS360.

Backlog Seed

define item schema in code,
add room tags and zone type vocabulary,
implement list filters,
create review statuses,
connect media to records,
validate with 5-10 real shopping items.