Minimum smart system · no marketplace yet

Private merchant graph + RFQ operating system.

The first tech should not be a public directory. It should be an internal system that turns Ef’s supplier conversations and Japan buyer interest into structured trade intelligence.

Minimum viable system: one database, three templates, one generated buyer pack, one weekly sales/RFQ rhythm.

Core principle

Every conversation becomes structured data. That is the moat before there is a marketplace.

Ef talks to suppliers

Catalogs, prices, MOQs, sample policy, export ability, Japan experience, documents, trust signals, red flags.

You structure the system

Database, RFQ templates, quote comparisons, buyer packs, AI extraction, and eventually the internal Trade OS.

The system learns

Who is real, who responds, what products quote well, where margins survive, and which buyers are serious.

The v0 stack

Start with tools that let Ef operate immediately. Move to a custom app only after the fields and workflow stabilize.

Layer	Minimum tool	Purpose
Database	Airtable / Google Sheets first; Postgres later	Supplier, buyer, product, RFQ, quote, deal records.
Documents	Google Drive / local folders	Catalogs, photos, certificates, proformas, freight quotes.
Communication	WhatsApp / LINE / Telegram / email	Real-world supplier and buyer conversations.
AI helpers	Manual paste-in prompts first; scripts later	Extract supplier profiles, translate, generate RFQs, normalize quotes.
Buyer output	Generated HTML/PDF packs	Professional deliverable buyers can pay for.

Database tables

This is a graph, not a flat list. Suppliers connect to products, products to RFQs, RFQs to quotes, quotes to deals.

Suppliers

Company, city, contact, category, products, catalog, MOQ, sample policy, export history, Japan experience, Incoterms, trust score, red flags.

Buyers

Importer, distributor, boutique, restaurant, hotel, designer. Track interest, pain, budget/order size, outreach status, next follow-up.

Products

Material, dimensions, weight, photos, MOQ, price range, HS candidates, compliance risk, food-contact/electrical/children flags.

RFQs

Structured buyer request: product, quantity, destination, target price, quality, sample need, deadline, required docs.

Quotes

Supplier reply: unit price, MOQ, currency, sample cost, lead time, Incoterms, payment terms, validity, risks.

Deals + tasks

Sample, negotiating, proforma, payment, production, freight, delivered, lost. Every deal needs an owner and next action.

Minimum workflow

The system exists to move from messy chat to buyer-facing decision.

Step	Action	Output
1	Ef finds or reactivates a supplier.	Supplier intake note + catalog/photos.
2	AI/person extracts structured supplier profile.	Supplier card with trust score and missing questions.
3	You/Ef identify Japan buyers/importers.	Buyer lead records with fit and outreach status.
4	Buyer interest becomes structured RFQ.	Clear buying request in Japanese/English/Turkish.
5	Ef sends RFQ to 5–10 suppliers.	Supplier replies captured as quote records.
6	System normalizes quotes.	Comparison table: price, MOQ, lead time, sample, risk.
7	Generate buyer pack.	Paid deliverable: shortlist, quotes, landed-cost assumptions, next step.

First smart automations

These are useful immediately. Marketplace features are not.

Supplier profile extractor

Input website/catalog/chat. Output category, products, contacts, trust signals, red flags, follow-up questions.

RFQ generator

Input vague buyer need. Output supplier-ready RFQ in Turkish plus buyer-facing summary in Japanese/English.

Quote normalizer

Input messy supplier replies. Output clean table: price, MOQ, sample, lead time, Incoterm, risk.

Translation/tone helper

Japanese buyer messages precise and polite; Turkish supplier messages direct and merchant-friendly.

Trust checklist

Company, address, export history, bank/account match, sample ability, references, suspicious urgency, too-good pricing.

Buyer pack generator

Click/generate selected suppliers and quotes into a clean HTML/PDF deliverable.

What not to build yet

These sound tempting, but they create drag before the business has real liquidity.

Do not build

public marketplace
supplier login
buyer login
payment/escrow system
chat system
reviews

Also defer

customs API integration
full landed-cost automation
complex permissions
public directory
AI matching as standalone product

Build instead

Private merchant graph, RFQ tracker, quote comparison, interaction memory, task follow-up, and generated buyer packs.

First folder/app structure

This can live inside /home/kuka/trade and evolve from CSV/templates to a real internal app.

/home/kuka/trade
  /data
    suppliers.csv
    buyers.csv
    products.csv
    rfqs.csv
    quotes.csv
  /templates
    supplier-intake.md
    buyer-discovery.md
    rfq-message.md
    quote-comparison.html
    buyer-pack.html
  /scripts
    extract-supplier-profile.ts
    generate-rfq.ts
    normalize-quote.ts
    generate-buyer-pack.ts
  /briefs
    ...
  /app
    internal Trade OS later

First week build

The goal is a working operating rhythm, not beautiful software.

Day	Build / operate	Proof
1	Create database tables and supplier/buyer views.	Can enter supplier + buyer records.
2	Create supplier intake and buyer discovery templates.	Ef can collect consistent info.
3	Add 20 suppliers and 10 buyers.	First structured lead base.
4	Create RFQ template for one category.	Vague need becomes supplier-ready request.
5	Create quote comparison template.	Can compare 3 suppliers cleanly.
6	Generate first buyer pack.	Professional deliverable exists.
7	Ask a buyer to pay for supplier pack/RFQ support.	Paid validation attempt.

The shortest version

Build a private supplier/buyer/RFQ/quote database. Use AI to turn messy chats into structured profiles and RFQs. Generate buyer-facing packs. Charge for those packs before building a marketplace.