Building a Full SaaS in 4 Weeks: Our Process, Start to Finish
A real walkthrough of how we took a fintech SaaS from spec to live deployment in 28 days.
FinBridge came to us in March with a spec document, a $3,500 budget, and a launch deadline four weeks out. They needed a multi-tenant fintech dashboard: accounts, transactions, reconciliation, reporting, and a client-facing portal with role-based access. The kind of thing a traditional agency would quote at $120,000 and six months.
This is what the next 28 days looked like.
Week 1: Architecture and data modelling
Day 1 was a 90-minute discovery call with the CTO and product owner. We came with a draft data model based on their spec — they corrected three assumptions and added two requirements we hadn't anticipated. By end of day we had a final entity-relationship diagram and a list of 47 user stories.
Days 2–3: the technical spec. Database schema (PostgreSQL), API surface (REST, 31 endpoints), frontend architecture (React, component tree), auth design (JWT + refresh tokens, three roles), deployment topology (AWS ECS + RDS + CloudFront). We ran this past their CTO for approval. One round of feedback, one revision.
Days 4–5: scaffolding. Repository structure, CI/CD pipeline, local development environment, and the first 12 shared components (buttons, inputs, tables, modals) generated and reviewed.
Week 2: Core functionality
Auth system, multi-tenancy, accounts module, and basic transaction management. Roughly 180 AI-generated functions reviewed and merged, 27 rejected and rewritten. The rejection rate was high this week because we were establishing patterns — once the first 40 functions establish the project's conventions, AI output quality improves significantly.
Week 3: Reporting + client portal
The reporting module was the highest-complexity piece: dynamic filters, aggregation queries, CSV/PDF export, and a chart library integration. This was also where we caught the most performance issues — the AI wrote queries that worked correctly on small datasets but would have killed the database at scale. Added appropriate indexes and rewrote the three most expensive queries.
The client portal — a read-only view with custom branding per tenant — went smoothly. Well-defined scope, clear component boundaries, fast AI output.
Week 4: QA, security, deployment
Full test pass against all 47 user stories. Security scan: one medium issue (an endpoint missing rate limiting), fixed same day. Load testing at 10× expected volume: no issues. DNS configuration, SSL, monitoring setup, documentation handoff.
Day 28: production deployment. FinBridge went live with zero critical bugs at launch.
What made it possible
Speed without chaos requires structure. Every hour saved by AI in generation was matched by deliberate process around review, integration, and testing. The discipline is unglamorous but it's the actual product. Any team can generate code fast. Shipping it reliably is the skill.