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SaaS is software sold as an ongoing subscription and operated by the vendor rather than the customer. Technically, the defining constraint is multi-tenancy: one running system serves many customers whose data must never leak across the boundary between them.
That constraint reaches further into the architecture than most teams expect. Authentication, database queries, background jobs, file storage, caching and logging all need a tenant context. Retrofitting that into a single-tenant application is one of the more expensive rewrites in commercial software.
The commercial appeal is recurring revenue and the valuation multiple attached to it. The operational appeal is that you maintain one deployed version rather than supporting customers stranded on releases from three years ago.
The trade-off is that you now run production for everyone. An outage affects every customer at once, an upgrade cannot be deferred for a nervous client, and support load scales with the customer count rather than the licence count. That is a genuine operational commitment, not just an engineering one.
Our approach
Tenant isolation strategy is decided before anything else, because it is the hardest thing to change later. Shared schema with a tenant column is cheapest to run and hardest to guarantee. Schema-per-tenant isolates cleanly but complicates migrations. Database-per-tenant gives the strongest isolation and the highest infrastructure cost. We pick based on your compliance requirements and expected customer count, and write down the reasoning.
Billing is built against a provider rather than hand-rolled. Proration, failed payments, trials, upgrades mid-cycle, tax and dunning are each individually fiddly and collectively a product of their own. We integrate Stripe or Paddle properly, including the webhook handling that keeps your database and the provider in agreement.
Onboarding gets designed as a feature, not a redirect to an empty dashboard. The gap between signup and first genuine use is where most SaaS trials are lost, so it gets the same design attention as the core product.
Capabilities
Tenant isolation enforced at the data layer, not by remembering to add a filter in each query.
Plans, trials, proration, upgrades and dunning through Stripe or Paddle, with webhooks reconciled against your own records.
Tracking consumption and enforcing plan limits without the counting itself becoming a bottleneck.
Invitations, roles, permissions and seat counting — the parts of B2B SaaS that always take longer than estimated.
Internal tools so your team can diagnose a customer issue without running database queries by hand.
Instrumentation for activation, engagement and churn indicators, defined before launch rather than reconstructed later.
Stack
Process
Isolation strategy, plan structure and limits agreed first, since both are costly to change after customers exist.
The main workflow built end to end for a single tenant, proving the model before breadth is added.
Signup, teams, roles, invitations and subscription lifecycle — the surrounding machinery every SaaS needs.
Iterating on the product surface with tenancy and billing already established underneath.
Admin tooling, monitoring, backup and restore rehearsal, and a documented incident path.
Early customers onboarded deliberately, with activation and churn signals watched from the first week.
Use cases
Software for one industry where general-purpose tools require too much adaptation to be workable.
Turning a system you built for yourself into something you can sell, which is mostly a tenancy and billing problem.
Team accounts, role hierarchies, SSO and the procurement requirements enterprise buyers arrive with.
APIs and tools billed by consumption, where metering accuracy directly affects revenue.
Choosing an approach
This choice determines your operating cost, your compliance story and how hard migrations will be. It is worth deciding explicitly.
| Model | Choose when | What it costs |
|---|---|---|
| Shared schema | Many small tenants, cost sensitivity, no strict isolation requirement | Every query must be tenant-scoped; one mistake leaks data across customers |
| Schema per tenant | Moderate tenant count needing clearer separation | Migrations must run across every schema; tooling gets more complex |
| Database per tenant | Enterprise customers with contractual or regulatory isolation requirements | Highest infrastructure cost and the most operational overhead |
Outcomes
FAQ
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