Project Overview
| Client Industry | HR Technology / Workforce Management |
| Business Type | Founder-led startup transitioning from a services-based scheduling consultancy into a software product company |
| Project Duration | 24 weeks |
| AI Service Provided | SaaS Product Development |
| Technologies Used | React, Next.js, TypeScript, Node.js, PostgreSQL, Redis, AWS (ECS, RDS, S3), Stripe Billing, Auth0 |
The Client Challenge
The client had spent three years manually building custom shift-scheduling spreadsheets and light tooling for individual restaurant and retail clients as a paid consulting service. They’d proven the model worked clients loved it and paid well but it didn’t scale beyond one-off engagements.
The business problem:
- Every new client meant rebuilding largely the same scheduling logic from scratch in a new spreadsheet or lightweight tool, with no reusable product to sell.
- The founder wanted to convert the proven service into a true multi-tenant SaaS product that any retail or restaurant business could sign up for and use independently, without a consulting engagement.
- They had no experience with subscription billing, multi-tenant architecture, or building software meant to serve many customers simultaneously and securely, rather than one custom build per client.
- Existing clients were manually invoiced and had no self-service way to manage their account, add locations, or invite staff everything ran through the founder personally.
- The founder needed to raise a funding round to hire a team, and investors wanted to see a real SaaS product with recurring revenue infrastructure, not a services business with software elements.
The client needed a true product built from a foundation of proven domain expertise — not a rebuild of one client’s spreadsheet, but a generalized platform that could serve many businesses with different shift patterns, roles and compliance needs.
Our Solution
AirBrite Labs designed and built a multi-tenant SaaS scheduling platform from the ground up, generalizing the scheduling logic the founder had refined over three years of consulting into a configurable product that any retail or restaurant business could self-onboard and use.
Key capabilities delivered:
- Multi-tenant architecture — each business operates in an isolated account with its own locations, staff, and scheduling rules, built to serve many customers securely on shared infrastructure.
- Configurable scheduling engine — shift rules, role requirements, and labor compliance settings (overtime thresholds, required break periods) are configurable per business rather than hardcoded, generalizing the founder’s client-specific logic into reusable settings.
- Self-service onboarding — new customers can sign up, set up their locations and staff, and start scheduling without any manual setup from the founder.
- Subscription billing — tiered pricing based on number of locations and staff, with self-service plan upgrades and Stripe-managed billing replacing manual invoicing.
- Manager and staff mobile-friendly views — managers build schedules from a web dashboard; staff view and swap shifts from a mobile-responsive interface.
- Usage-based scaling — the platform is built to handle a growing number of tenant businesses without per-customer engineering work, unlike the prior consulting model.
Technical Approach
Multi-Tenancy Architecture: Implemented a shared-database, tenant-isolated model in PostgreSQL using row-level security policies scoped to each business account, balancing cost-efficient infrastructure with strict data isolation between customers.
Scheduling Engine: Built a rules-based scheduling engine in Node.js that generalizes the founder’s domain expertise into configurable parameters role requirements, shift length limits, overtime and break compliance rules rather than hardcoding logic specific to any one client’s prior spreadsheet.
Frontend: Next.js and TypeScript power the manager scheduling dashboard, with a mobile-responsive staff view built into the same application rather than a separate native app, given budget and timeline priorities for the initial launch.
Billing Infrastructure: Stripe Billing integrated for subscription management, supporting tiered plans based on location and staff count, self-service upgrades/downgrades and automated invoicing replacing the founder’s manual invoicing process entirely.
Authentication & Access Control: Auth0 handles authentication with role-based permissions distinguishing business owners, location managers, and staff members, each with different platform access and capabilities.
Performance: Redis caches frequently accessed scheduling data (current week’s published schedule, staff availability) to keep the scheduling dashboard responsive as tenant and data volume grows.
Infrastructure: Deployed on AWS ECS for auto-scaling application hosting, with RDS for the managed multi-tenant PostgreSQL database and S3 for document storage (compliance certifications, staff documents).
Implementation Process
- Discovery & Requirement Analysis (Weeks 1–4): Worked closely with the founder to extract and document the scheduling logic and business rules that had been living in ad hoc spreadsheets and the founder’s personal expertise, translating tacit knowledge into a formal product specification.
- Prototype / PoC (Weeks 5–7): Built a working prototype of the configurable scheduling engine and tested it against three of the founder’s existing client scenarios to confirm the generalized rules produced correct schedules.
- Development (Weeks 8–17): Built the multi-tenant architecture, self-service onboarding flow, manager dashboard, staff scheduling views, and billing integration.
- Integration (Weeks 18–19): Connected Stripe Billing, Auth0, and finalized the tenant isolation and row-level security implementation.
- Testing (Weeks 20–21): Migrated the founder’s existing consulting clients onto the new platform as beta tenants, validating real-world scheduling scenarios and gathering structured feedback before public launch.
- Deployment (Week 22): Public self-service signup launched, with existing clients fully transitioned to the SaaS platform.
- Optimization (Weeks 23–24 and ongoing): Refined onboarding flow based on new self-service signup drop-off patterns and tuned the scheduling engine’s default rule templates based on beta feedback.
Key Features Delivered
- Multi-tenant architecture with secure, isolated data per business account
- Configurable, rules-based scheduling engine generalized from real client scenarios
- Self-service onboarding requiring no manual setup from the founder
- Stripe-based subscription billing with tiered, usage-based pricing
- Manager scheduling dashboard and mobile-responsive staff shift views
- Role-based access control for owners, managers, and staff
- Compliance-aware scheduling rules (overtime, break requirements) configurable per business
Business Results
- All existing consulting clients successfully migrated to the self-service SaaS platform, eliminating the founder’s per-client manual scheduling work entirely
- New customer signups became self-service, with average time from signup to first published schedule under 30 minutes
- Monthly recurring revenue infrastructure was established for the first time, replacing ad hoc consulting invoices with predictable subscription billing
- The founder successfully raised a seed round, citing the working multi-tenant product and early recurring revenue as key proof points for investors
- New tenant onboarding required zero engineering involvement, compared to the multi-week custom build previously required per client
- The platform onboarded new paying customers beyond the founder’s prior personal network within the first two months post-launch, validating demand beyond existing relationships
Technology Stack
| Layer | Technology |
|---|---|
| Frontend | React, Next.js, TypeScript |
| Backend | Node.js |
| Database | PostgreSQL (multi-tenant, row-level security) |
| Caching | Redis |
| Authentication | Auth0 |
| Billing | Stripe Billing |
| Cloud Infrastructure | AWS ECS, RDS, S3 |
Why the Solution Worked
The platform succeeded because it generalized real, proven domain expertise rather than starting from a generic scheduling template. The founder’s three years of consulting had already validated what businesses actually needed the engineering challenge was translating that tacit, client-specific knowledge into configurable product logic that worked across many different businesses, not reinventing the scheduling problem from scratch.
Building true multi-tenancy with proper data isolation from day one rather than a quick single-tenant build that would need re-architecting later meant the platform could actually scale to serve many customers securely from launch, which mattered directly to investor confidence during fundraising.
Future Scalability
The SaaS foundation is built to support continued product growth, including:
- Adding payroll system integrations so scheduling data flows directly into existing payroll providers customers already use
- Building a native mobile app for staff as usage and mobile engagement data justify the investment
- Expanding configurable compliance rules to support additional states and labor law variations as the customer base grows geographically
- Adding analytics and labor cost forecasting features on top of the now-centralized scheduling data across tenants
Because tenant isolation, the scheduling engine, and billing are built as distinct, well-defined layers, new features and integrations extend the existing platform rather than requiring architectural rework.
Final Outcome
The founder’s proven scheduling expertise, once trapped in a one-client-at-a-time consulting model, is now a genuine multi-tenant SaaS product with self-service onboarding, recurring revenue, and room to scale. What was a services business with software elements is now a software business with the recurring revenue model and growth trajectory to match.
