SaaS Product Development
Multi-tenant SaaS platforms built for recurring revenue from day one.
SaaS is a specific discipline. A general-purpose web app becomes a SaaS product the moment you need multiple isolated customer accounts, a subscription billing cycle, tiered feature access and a way to onboard a new customer without anyone on your team touching a database. These are engineering problems with well-understood patterns — but they need to be built deliberately.
We design and build the full SaaS stack: tenant isolation at the data layer, Stripe billing with plan management and usage metering, email-based onboarding flows, an internal admin panel to manage customers and subscriptions, and the instrumentation that tells you which features your customers actually use. Everything ships on infrastructure you own with no ongoing licence to us.
What this covers
Multi-tenant architecture with strict tenant data isolation (row-level or schema-level)
Subscription billing via Stripe: plans, trials, upgrades, downgrades, invoices and webhooks
Feature gating by plan tier, with a clean abstraction the rest of the codebase uses
Self-serve onboarding: sign-up, email verification, team invitations and guided setup
Internal admin panel: customer list, subscription management, impersonation and manual overrides
Usage tracking, in-app analytics and the instrumentation needed for product-led growth loops
Security fundamentals: least-privilege API design, audit logging and secure secrets management
Deliverables
- A live, multi-tenant SaaS product with billing and onboarding on infrastructure you own
- Source code, architecture documentation and environment setup guide
- Stripe billing configuration and webhook handling, fully tested
- Internal admin panel for customer and subscription management
- A product-analytics baseline so you can see what users do from launch day
What we build with
SaaS product engineering
A SaaS product is not a web application with a Stripe checkout bolted on. It is a system designed from the ground up around the assumption that hundreds or thousands of isolated customer accounts will co-exist in the same infrastructure, that each account will have its own billing state, feature entitlements, and team members, and that the owner of that account can provision themselves without any intervention from your team.
The engineering problems this introduces — tenancy isolation, plan-gated execution paths, metered usage, self-serve account lifecycle — are well understood and repeatable. The mistake is treating them as features to add later rather than constraints that shape the data model and API design from the first migration.
How we build a SaaS product
SaaS introduces a set of cross-cutting concerns that must be resolved early, because retrofitting tenancy isolation or a billing abstraction onto an existing codebase is expensive. We front-load these decisions in a tight architecture phase before the first product feature is built.
- Tenancy model selection: row-level security (shared schema), schema-per-tenant, or database-per-tenant — documented against compliance requirements and expected account volume
- Data model design with tenant_id propagation strategy and cross-tenant query guard patterns
- Billing model specification: flat subscription, per-seat, usage-metered, or hybrid
- Stripe product and price object design, including trial mechanics and proration behaviour
- Feature entitlement schema: plan-to-feature mapping that the application reads at runtime
- Sign-up flow: email/password and OAuth provider paths, email verification, and duplicate account detection
- Workspace provisioning: isolated data namespace created atomically on account creation
- Team invitation flow with role assignment, pending-invite tokens, and expiry handling
- Welcome sequence: transactional emails (Resend / SendGrid) triggered by lifecycle events, not cron
- In-app onboarding checklist to drive activation toward the product's key engagement moment
- Stripe webhook receiver with signature verification (Stripe-Signature header), idempotency checks, and a dead-letter log for failed events
- Subscription lifecycle handlers: checkout.session.completed, customer.subscription.updated, invoice.payment_failed, customer.subscription.deleted
- Dunning logic: grace period on payment failure before feature access is restricted
- Plan upgrade and downgrade flows with immediate proration and seat-count reconciliation
- Billing portal integration for self-serve card updates and invoice download
- Gate abstraction: a single authorisation function isFeatureEnabled(tenantId, feature) that the rest of the codebase calls
- Plan-feature matrix cached in Redis with invalidation on Stripe webhook receipt
- Usage counters: atomic increments in Redis with a periodic flush to the billing record and Stripe usage reporting for metered subscriptions
- Soft and hard limits: warn at 80% of a metered limit, block at 100%, with a clear upgrade prompt
- Admin override capability for sales-assist situations, logged to the audit trail
- Internal admin panel: customer list with plan, MRR, and last-active date; subscription management; manual plan overrides
- Impersonation: the ability to log in as a customer account for support debugging, with every impersonation session written to an audit log
- Customer event log: a chronological record of billing events, feature usage, and support actions per account
- Bulk operations: pause, cancel, or migrate a cohort of accounts without direct database access
- Usage dashboard per account so customer success can answer ‘what are they actually doing’ without a data query
Tenancy and billing architecture
Resolve the two decisions that touch every other part of the system: how tenant data is isolated at the database layer, and what the billing model looks like in terms of plan structure, metering, and lifecycle events. These are irreversible choices at scale.
Self-serve onboarding
The onboarding funnel is the most performance-sensitive part of a SaaS product. A new account provisioning itself at 2 AM must succeed completely — including workspace creation, billing setup, welcome email, and guided setup — without any human intervention.
Billing integration
Stripe is a reliable billing engine, but integrating it correctly requires handling a large surface area of webhook events, idempotency constraints, and edge cases. We treat billing as a first-class subsystem with its own test suite.
Feature gating and usage metering
Feature gates must be fast (read from cache, not the billing database on every request), consistent (the same plan state is seen by the API and the UI), and easy for engineers to apply without understanding the full billing model.
Admin and operational tooling
Your customer success and engineering teams need internal visibility and the ability to act on a customer’s account without touching the database directly. We build this as a first-class internal application, not an afterthought.
How we'd choose
There's rarely one right answer — these are the trade-offs we weigh before recommending an approach.
Single-tenant vs Multi-tenant pooled vs Hybrid tenancy
Tenancy model is the most consequential early decision in a SaaS build. It determines your infrastructure cost floor, compliance posture, onboarding automation ceiling, and the blast radius of a data incident. Choose the model that fits your actual customer base and regulatory environment, not the one that sounds most enterprise.
| Criterion | Single-tenant (dedicated infra per customer) | Multi-tenant pooled (shared schema, RLS) | Hybrid (pooled default, dedicated for enterprise) |
|---|---|---|---|
| Data isolation | Complete physical isolation — no shared resources; a misconfigured query cannot leak cross-tenant data | Logical isolation enforced by PostgreSQL Row Level Security policies or application-layer tenant_id filters; a missing WHERE clause is a data leak | Pooled accounts carry the RLS risk; dedicated enterprise tenants get physical isolation where it is contractually required |
| Infrastructure cost | High and scales linearly with customer count — each new account provisions its own database, compute, and networking | Low floor — all tenants share the same database cluster; cost scales with data volume and query load, not account count | Moderate — the dedicated tier adds per-customer overhead only for accounts that pay for it |
| Compliance fit | Strongest compliance story for SOC 2, HIPAA, and GDPR data residency requirements; each tenant’s data can be placed in a specific region or jurisdiction | Acceptable for most B2B SaaS; requires demonstrable RLS policy testing and a documented breach-containment procedure for enterprise sales | Covers the majority of customers economically while satisfying the contractual isolation demands of regulated enterprise accounts |
| Onboarding automation | Requires infrastructure provisioning on sign-up (database creation, DNS record, TLS certificate); adds seconds to minutes of latency and meaningful failure surface | Instant — a new row in the tenants table is the only provisioning step | Instant for pooled accounts; dedicated provisioning is typically a manual or semi-automated sales-assist step for enterprise contracts |
| Schema migration complexity | Every migration must run against N customer databases — a fleet migration script is required; failures mid-run leave tenants on mismatched schemas | One migration, one database; zero-downtime migration patterns (expand-contract) apply cleanly | One migration for the pool; a separate coordinated migration run for dedicated tenants |
| When to choose | Enterprise-only or highly regulated verticals (healthcare, fintech, defence) where customers mandate physical isolation and the ACV justifies per-tenant infrastructure cost | Self-serve or SMB SaaS with high account volume, automated onboarding requirements, and no hard contractual isolation mandates | Products that start in the SMB segment and sell upmarket — pooled by default gives you low operating cost; the dedicated tier is unlocked as an enterprise SKU without a rebuild |
Anti-patterns we prevent in SaaS builds
Tenant ID as an application-layer convention only
The tenant_id column exists on every table but the database itself does not enforce it. Row Level Security is not enabled; the application filters by tenant_id in every query as a matter of discipline. One missing WHERE clause in a list endpoint or a background job that forgets to scope its query exposes all customers’ data to whichever tenant triggered the request. This is not a theoretical risk — it is the most common data-leak pattern in multi-tenant SaaS.
Enable PostgreSQL Row Level Security on every tenant-scoped table and set a default policy of DENY. Application code sets a session-level tenant context (SET LOCAL app.current_tenant = $1) before executing queries; the RLS policy enforces it. A query that forgets the context returns no rows rather than all rows. Add an integration test that asserts cross-tenant data is unreachable from any authenticated session.
Billing state read from the database on every request
The feature gate calls the subscriptions table (or worse, the Stripe API) on every authenticated request to determine the current plan. Under load this creates a hot read path on billing data, adds latency to every API response, and couples request throughput to Stripe API availability. When Stripe has an incident, your product has an incident.
Cache the plan entitlement set per tenant in Redis with a short TTL (60-300 seconds). Invalidate the cache entry on receipt of a Stripe webhook that changes subscription state. The feature gate reads from Redis; the Stripe API is only called by the webhook handler and by the billing admin panel. This decouples product latency from billing system availability entirely.
Webhook delivery treated as guaranteed
Billing logic depends on Stripe webhooks arriving exactly once, in order. In practice, webhooks are retried on delivery failure, can arrive out of order (an invoice.paid before the checkout.session.completed that triggered it), and can be delivered more than once. Code that does not account for this creates duplicate subscription records, double-charges, or silently fails to activate accounts whose checkout webhook was temporarily unreachable.
Treat every incoming webhook as potentially a duplicate and potentially out of order. Store a processed event log keyed on the Stripe event ID and skip events already in the log (idempotency). Handle each event type based on the current state in your database, not on what you expect the sequence to have been. Write a test suite that replays event sequences in non-natural order and asserts correct billing state after each permutation.
Common questions
How do you handle tenant data isolation — do we share a database?
It depends on your compliance requirements and scale targets. Row-level isolation (shared schema, tenant ID on every table) is fast to build and serves most SaaS products well. Schema-per-tenant adds isolation overhead but is straightforward to implement where regulations require it. We recommend the right approach for your specific situation and explain the trade-offs clearly.
Can you take over a SaaS product that is already built but needs significant work?
Yes. We audit the existing codebase, identify the structural issues, and triage them by risk and business impact before touching anything. We will tell you honestly if the right call is incremental improvement or a targeted rebuild of a specific layer.
Related capabilities
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