Curtain & blinds quoting is a multi-axis pricing problem: fabric type, m², mounting style, and labor each affect the line item. The retailer was running it on Zalo chats and spreadsheets — fast for one salesperson, painful at team scale. NKKTech rebuilt the workflow on a dedicated est-invoice Enterprise tenant: own database, pricing-formula DSL, fabric-specific custom fields, quote approval, Zalo OA, and an AI sales agent.
We deployed the retailer on a dedicated est-invoice Enterprise tenant. Unlike the shared Standard tier, Enterprise gives the retailer its own PostgreSQL database, custom data model, and configurable business logic — so the platform fits the curtain workflow instead of forcing the workflow into a generic template.
The pricing-formula DSL lets the retailer express its quote math as readable rules:line_total = m2 * fabric.price_per_m2 + labor.hours * labor.rate. Custom fields on the customer and quote schema capture fabric SKU, window dimensions, mounting style, and installation notes — data that would have been ad-hoc text in a generic CRM.
On the customer-facing side, the Zalo OA integration pulls every chat into the same customer record, so any salesperson can pick up the thread with full context. The AI sales agent qualifies inbound leads, asks for window dimensions and fabric preferences up front, and books a measurement appointment without a human on the loop. A quote-approval workflow routes draft quotes above a configurable threshold to the manager before they go to the customer.
Tell us how you quote and where the workflow breaks. We'll show you the est-invoice Enterprise tenant we'd shape for you.