MVP ENGINEERING CASE STUDY: PROJECT VIZ

Client
ProjectViz
Involvement
1 Product Lead, 2 Full-Stack Engineers, 1 ML Engineer, 1 UI/UX Designer
Scope
WhatsApp capture bot, language-model extraction layer, responsive web dashboard, admin API
Results
MVP live in 4 weeks · first enterprise licence signed in week 5 · 65% drop in "lost" tasks during pilot
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GOAL

WhatsApp-to-dashboard pipeline with real-time NLP task extraction.

Legacy manufacturers and utilities across the Global South run multimillion-dollar projects inside WhatsApp threads. Critical updates vanish, accountability blurs, and executives don't discover blockers until deadlines slip. ProjectViz believed those raw conversations could be transformed into reliable project data, but needed a production-ready proof—fast enough to win paying customers and simple enough that workers wouldn't have to change a single habit.

Builded's brief was clear: delivering an end-to-end MVP in four weeks that listens to chat traffic, tags owners and due dates with near-real-time accuracy, and displays status in one lightweight dashboard that loads on spotty 3G. No feature creep, no vanity polish—just the shortest path from idea to invoice.

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RESULTS

Production deployment in 28 days, enterprise renewal in 30 days

Day 28, the MVP went live. A discreet bot now listens to existing WhatsApp groups, our NLP layer tags tasks, owners, and deadlines in real time, and a lightweight React dashboard surfaces status for supervisors who previously worked blind. In the first 30 days closed work orders rose 18%, missed-deadline incidents fell 65%, and the plant manager renewed for three years, six times the build cost.

For ProjectViz, the pilot did more than validate technology; it proved a revenue model. For Builded, it showcased our edge in tightly-scoped discovery, parallel design-and-build sprints, and a hand-off that lands in production instead of backlog. Where traditional shops pitch roadmaps, we ship market traction.

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MVP ENGINEERING CASE STUDY: PROJECTVIZ

MVP ENGINEERING CASE STUDY: PROJECTVIZ

Client
ProjectViz
ProjectViz
Involvement
1 Product Lead, 2 Full-Stack Engineers, 1 ML Engineer, 1 UI/UX Designer
1 Product Lead, 2 Full-Stack Engineers, 1 ML Engineer, 1 UI/UX Designer
Scope
WhatsApp capture bot, language-model extraction layer, responsive web dashboard, admin API
WhatsApp capture bot, language-model extraction layer, responsive web dashboard, admin API
Results
MVP live in 4 weeks · first enterprise licence signed in week 5 · 65 % drop in “lost” tasks during pilot
MVP live in 4 weeks · first enterprise licence signed in week 5 · 65 % drop in “lost” tasks during pilot
Project Image
GOAL
Legacy manufacturers and utilities across the Global South run multimillion-dollar projects inside WhatsApp threads. Critical updates vanish, accountability blurs, and executives don’t discover blockers until deadlines slip. ProjectViz believed those raw conversations could be transformed into reliable project data, but needed a production-ready proof—fast enough to win paying customers and simple enough that workers wouldn’t have to change a single habit.

Builded’s brief was clear, delivering an end-to-end MVP in four weeks that listens to chat traffic, tags owners and due dates with near-real-time accuracy, and displays status in one lightweight dashboard that loads on spotty 3G. No feature creep, no vanity polish—just the shortest path from idea to invoice.
Project Image
RESULTS
Day 28, the MVP went live. A discreet bot now listens to existing WhatsApp groups, our NLP layer tags tasks, owners, and deadlines in real time, and a lightweight React dashboard surfaces status for supervisors who previously worked blind. In the first 30 days closed work orders rose 18 %, missed-deadline incidents fell 65 %, and the plant manager renewed for three years, six times the build cost.

For ProjectViz, the pilot did more than validate technology; it proved a revenue model. For Builded, it showcased our edge in tightly-scoped discovery, parallel design-and-build sprints, and a hand-off that lands in production instead of backlog. Where traditional shops pitch roadmaps, we ship market traction.
Project Image
Project Image
Project Image