ShippedSales AICPQEnterprise SalesRevenue Operations
// build study

QuoteForge

An AI CPQ and proposal platform that builds enterprise quotes from your catalog, guards every discount against the margin floor, routes approvals, and generates the proposal.

Client:Enterprise sales team (NDA)
Duration8 weeks
ScopeMVP product design and front-end build of the Quotes dashboard and single-quote detail experience, backed by a pricing-and-guardrail engine and an approval-routing workflow.

// The Quotes dashboard — pipeline KPIs, a quoted-vs-won trend, an open-quotes table with margin-health pills, and discount distribution against the 25% guardrail.

// the numbers

Figures from the engagement, shared under NDA.

We publish them unchanged and can’t break them down any further here. The reference build you can open runs entirely on sample data.

84Open quotes
$48KAvg. quote value
34%Win rate
3.2 hrsAvg. approval time
01In brief

If you read one part of this page, read these 4 lines.

  • Catches margin leakage at quote time, not in a month-end finance review
  • Gives every rep an AI recommended-max discount benchmarked on comparable deals
  • Enforces discount ceilings and margin floors so no deal slips below the line
  • Takes a deal from catalog configuration to a signed proposal in one flow
02Overview

What it does — and which part of it we built.

QuoteForge gives enterprise sales teams a single surface for configure-price-quote.

Reps assemble a deal from the product catalog, see the margin update live as they build it, and get AI guidance on how far they can discount before breaking policy. Out-of-band quotes route to the right approver automatically, and a branded proposal generates the moment the deal clears. BuildspaceLabs designed and built the MVP front end — a Quotes dashboard for the deal desk and a single-quote detail view with line items, a margin breakdown, an AI discount-guidance card and a live approval chain — turning a pricing engine and a set of guardrails into a workflow a rep can move through in minutes.

03The screens

Every screen here is from the reference build, not the client’s system.

The captions say what you are looking at. Every name and record on them is sample data.

04Outcomes

What the engagement left the client with.

  • Delivered a production-quality MVP of the Quotes dashboard and quote detail view in an 8-week engagement
  • Consolidated configuration, pricing guardrails, approvals and proposals into a single quote-to-close workflow
  • Gave revenue leadership a real-time view of discount and margin exposure across the open pipeline
  • Established a reusable design system (margin-health pills, discount bars, AI guidance cards) for the product's next surfaces
05How it is built

The stack was picked per constraint, not per house habit.

7 technologies across 3 layers — the shape of the stack follows the problem.

Frontend & Mobile
Next.jsReactTypeScript
Data & Infrastructure
PostgreSQL
Backend & APIs
Node.jsPython pricing engineTemporal workflows
Every feature in the build (6)
  • Quotes dashboard with open-quote, win-rate and approval-time KPIs above a live table
  • Catalog-driven configuration with bundles and product dependencies enforced
  • AI discount guidance with a recommended-max discount and the margin impact per deal
  • Margin guardrails — discount ceilings and margin floors checked at quote time
  • Routed approval chains with a full audit trail for out-of-policy deals
  • One-click branded proposal generation with line items, terms and an e-sign block
// see for yourself

Don’t take our word for it — it is running in the frame below.

This is the same page the provenance block links to: our reference build for QuoteForge, with its own look, copy and motion. Scroll inside it, or open it full-screen.

// more from the lab

A team that ships across the board.

36products in production
8industries served
68+technologies in play

Closest to QuoteForge

// next

Building something in this space?

A 30-minute call is enough for us to understand your situation and tell you whether we're the right team. Usable version in the first two weeks if we are.