We build multi-tenant SaaS platforms end to end — architecture, billing, integrations, compliance and cloud infrastructure. You own the code, the accounts and the roadmap.
Sample build · one admin view from a multi-tenant platform we design and code
Most SaaS platforms do not fail at launch. They fail eighteen months in, when the tenancy model will not scale, the billing logic cannot express a new plan, and the first enterprise buyer asks a security question nobody designed for. These are the six we settle up front.
Shared database, schema-per-tenant and database-per-tenant have very different cost, isolation and compliance profiles. Changing after launch is close to a rewrite.
Plans, seats, usage, proration, trials, coupons, dunning and tax are a real subsystem. Bolting them on later is where most revenue leakage starts.
Your first enterprise prospect sends a security questionnaire, and suddenly you need audit logs, SSO, RBAC and encryption you never designed for.
An architecture that works at fifty tenants can quietly cost more per customer at five thousand, turning growth into a margin problem.
B2B buyers expect your product to talk to their CRM, identity provider and data warehouse. Each unplanned integration delays the deal it was meant to win.
Teams that scope only the customer-facing app end up running support, provisioning and billing fixes out of database queries within a month of launch.
Some clients arrive with a validated product and no engineering team. Others have software that already works and needs to become a multi-tenant platform. These are the seven engagements we take, and what each one actually delivers.
Before anyone writes code, we settle the decisions that are expensive to reverse: which tenancy model your buyers and regulators require, how the data model separates tenants, what the per-tenant infrastructure cost looks like at your target scale, and which parts of the roadmap belong in release one. You leave with an architecture document, a cost model and a feature-by-feature build plan you can take to any team, including one that is not us.
What you get
Full-stack build of the application your customers log into: tenant-aware workflows, role-based permissions, onboarding, notifications, reporting and the admin console your own team runs the business from. Every feature is built against the multi-tenant core rather than as a standalone module, so a permission added in one place holds everywhere, and a tenant's data never leaks into another tenant's view through a missed query filter.
What you get
For products where the workflow is the differentiator and no off-the-shelf platform models it correctly. We build the domain logic your business actually runs on, with the configurability that lets each tenant adapt it without a fork: custom fields, configurable workflows, per-tenant branding and feature flags that let you sell different capability sets from one codebase.
What you get
A first release that a real customer can pay for, not a clickable demo. That means one core workflow done properly, onboarding, authentication, billing and the admin tooling to support it — built on the architecture the full platform will use, so version two is an extension rather than a rewrite. We cut scope by removing features, never by skipping the foundations that are expensive to add later.
What you get
B2B buyers rarely adopt a product that does not talk to the systems they already run. We build the public API, webhooks and SSO that make your platform integrable, then the specific connectors your pipeline is asking for: CRM, ERP, identity providers, data warehouses and payment systems. Each integration is built against the vendor's sandbox and monitored in production, because a silently failing sync is worse than no integration.
What you get
A long-run engagement where we act as your product engineering team: discovery, design, build, release and the operating work that follows. This is the model for companies without an in-house platform team, or with one that is already fully committed to the current product. You get a stable squad rather than rotating contractors, and the same people who built a subsystem are the ones who support it.
What you get
Turning single-tenant or on-premise software into a cloud-native multi-tenant platform. The engineering is only half the problem — the other half is moving live customers without losing data or breaking uptime commitments. We migrate in waves, with a rollback path at every wave and both systems running in parallel until the last customer is across.
What you get
SaaS spending keeps climbing, but buyers are far more disciplined than they were three years ago. Renewals get scrutinised, unused licences get cut, and the products that survive are the ones that prove their value inside the customer's own stack.
Sources: Precedence Research (global and U.S. SaaS market size, CAGR, regional share), Zylo 2026 SaaS Management Index (applications per company, licence utilisation). Market figures move quickly — treat them as direction, not a guarantee.
Multi-tenancy is the one decision that is genuinely expensive to reverse. It sets your infrastructure cost per customer, how strong your data isolation story is in a security review, and how far you can scale before the database becomes the bottleneck. We pick the model against your buyers and your compliance obligations, in week one.
One database, one schema, a tenant identifier on every row, enforced at the data-access layer so a missing filter cannot leak data across tenants.
One database instance, a dedicated schema per tenant. Stronger separation and simpler per-tenant restores, at the cost of migrations that must run across every schema.
A dedicated database, and often dedicated infrastructure, per tenant. Usually what regulated or large enterprise buyers require, and what makes data residency straightforward.
Whichever tenancy model you run, these five layers carry the platform. A request arrives, gets resolved to a tenant, checked against permissions and entitlements, served from tenant-scoped data, and metered for billing.
Every request resolves to a tenant before it touches business logic, whether it arrives through a subdomain, a custom domain or an API key. Authentication, SSO and session handling all carry tenant context, so no downstream service has to guess who is asking.
Roles and permissions are enforced at the API layer rather than hidden in the interface, and plan entitlements are checked in the same place, so an expired subscription cannot be worked around by calling the endpoint directly.
Tenant scoping lives in the data-access layer itself, not in individual queries, which is what prevents the single most common SaaS data leak: one forgotten WHERE clause. Migrations, backups and restores are all tenant-aware.
Usage is measured where it happens and written to an event stream the billing system reads, so seats, API calls and storage bill accurately without a nightly reconciliation job guessing after the fact. Rate limits and quotas run off the same counters.
Everything runs as infrastructure-as-code in your own cloud accounts, with per-tenant cost attribution and monitoring that can answer which tenant caused a spike. That is the difference between a platform your team can operate and one only we can.
A SaaS platform is four products sharing one codebase: what customers use, what their admins configure, what your team operates, and what your engineers build on. Teams that scope only the first one end up building the other three in a panic after launch.
We design and build the surface your customers actually work in every day. Every feature here is built tenant-aware from the start, so what a user sees is always scoped to the organisation they belong to and the plan that organisation pays for.
What we build into it
We build signup that provisions a live tenant, seeds sample data and lands the user in a working state, rather than an empty screen they have to configure.
Email, social and enterprise SSO through SAML or OIDC, with session handling that carries tenant context into every downstream service call.
The domain logic your product exists for, built as configurable workflow rather than hardcoded rules, so each tenant adapts it without a fork.
In-app, email and webhook notifications driven by real product events, with per-user preferences so the product does not get muted in week two.
Indexed search scoped to the tenant at the index level, so performance stays flat as the largest tenant grows past everyone else.
Reporting built off the production data model with read replicas, so a customer running a heavy report never slows down someone else's writes.
Background-generated exports in the formats buyers ask for, which is also what GDPR portability and enterprise procurement reviews require.
A responsive web app by default, and native iOS or Android where the workflow genuinely happens away from a desk rather than because it sounds good.
WCAG-aligned components and externalised strings from the start, because retrofitting either one across a mature product is a multi-month project.
The controls your customer's own administrator needs. Getting this right is what lets a deal close without your team doing manual setup for every new account, and it is the single biggest driver of support ticket volume when it is missing.
What we build into it
Invite, deactivate and reassign users, with team or workspace structures that mirror how the customer's organisation is actually shaped.
Standard roles out of the box plus custom roles for enterprise tenants, enforced server-side so the UI is never the only thing stopping an action.
Per-tenant logo, colours, email templates and custom domain, which is usually what turns a product into something an enterprise will put in front of its own users.
Custom fields, statuses, templates and workflow rules the admin controls, so onboarding a new tenant does not require an engineer.
Plan changes, seat adjustments, payment methods and invoice history the customer handles themselves, with proration calculated correctly at the moment of change.
An append-only record of who did what inside their workspace, exportable, which is the first thing a security questionnaire asks for.
Self-serve connection and disconnection of integrations with clear sync status, so a broken connector is visible to the customer before it reaches your support queue.
Scoped API credentials and webhook endpoints the tenant manages, with delivery logs so their developers debug without opening a ticket.
Per-tenant retention and deletion policies, which is what makes GDPR and internal governance commitments something you can actually honour.
The internal console your own team runs the business from. This is the section most teams cut to save budget, and the one they rebuild under pressure a month after launch when support is being run out of database queries.
What we build into it
Provision, suspend, upgrade and inspect any tenant from one place, with every action written to an audit trail as it happens.
Support staff can view a customer's account to reproduce an issue, time-limited, consent-aware and fully logged, rather than asking for their password.
Failed payments, refunds, credits, discounts and plan overrides handled in the console and reconciled against the billing provider daily.
Per-tenant activity timelines and error context, so first-line support resolves an issue without escalating to an engineer every time.
Enable features per tenant or per cohort, so you can run a beta with five customers and roll back without a deploy if it goes badly.
Event instrumentation wired into the product so activation, adoption and churn signals come from real usage rather than a survey.
Health, latency and error-rate monitoring with alerts that name the affected tenant, so an incident starts with a fact instead of a search.
Infrastructure cost broken out per tenant and per feature, which is how you find the customer whose usage is quietly eating your margin.
Onboarding, trial-expiry and re-engagement messaging wired to real product events rather than a generic time-based drip.
The layer that decides whether your platform can be extended, sold into technical organisations, and maintained by a team that is not us. This is also what makes the difference between a product and a platform other companies build on.
What we build into it
A versioned, documented REST or GraphQL API with rate limiting and a sandbox, generated from the same schema the product runs on so docs never drift.
Signed webhooks with retries, exponential backoff and a replay log, because an unreliable webhook is worse for a customer than no webhook.
Automated test, build and deploy with blue-green or canary releases, so shipping on a Wednesday afternoon is routine rather than an event.
Every environment defined in Terraform or equivalent, in your repositories, so infrastructure is reviewable and reproducible rather than clicked together.
Unit, integration and end-to-end tests including explicit tenant-isolation tests that fail the build if data can cross a tenant boundary.
Automated backups with tested restores and a documented recovery objective, verified by actually restoring rather than assuming it works.
Load tests against realistic tenant distributions, so the noisy-neighbour problem is found in staging rather than by your largest customer.
Architecture decision records, runbooks and onboarding docs written as we build, so a new engineer is productive without reverse-engineering the system.
Development, staging and production built from the same definitions, which removes the entire class of bugs that only appear in production.
Adding a payment button takes a day. Building a subscription system that handles a customer upgrading mid-cycle, adding eleven seats, hitting a usage overage and then failing a card takes considerably longer — and getting it wrong shows up as revenue leakage nobody notices for two quarters.
What the billing layer handles
Providers we wire it to
Sample build · one invoice from a billing engine we design and code
The engine is the same everywhere. What changes per vertical is the compliance surface, the integrations buyers expect on day one, and which part of the platform we have to build first for the product to be sellable at all.
EHR-adjacent platforms, telemedicine, care coordination and practice management, where PHI handling shapes the architecture before any feature does.
Lending platforms, treasury and wealth tooling, compliance workflow and embedded finance, where a ledger that reconciles is non-negotiable.
Claims management, underwriting support, policy administration and broker portals, usually replacing a spreadsheet-and-email process.
Multi-location ordering, inventory, staff scheduling and loyalty, where each franchise or location is effectively its own sub-tenant.
Multi-channel order and inventory platforms, merchandising tools and retail analytics sitting on top of storefronts the merchant already runs.
Fleet and freight management, warehouse operations and shipment visibility, where the data arrives from telematics and EDI rather than a form.
Learning platforms, assessment tools and student information systems, where each institution is a tenant with its own roles and academic calendar.
Property and tenant management, leasing workflow, brokerage CRM and portfolio analytics across owners, managers and residents.
Project, job and crew management with scheduling, estimates and compliance documentation, used mostly on phones on a site with poor signal.
Hiring, onboarding, performance and workforce management platforms, where the data is sensitive and the integrations are with payroll and identity.
Campaign, content and analytics platforms that live or die on how many other tools they connect to and how fast reporting loads.
Production monitoring, maintenance and quality platforms pulling from machines and ERP systems rather than from users typing.
Citizen service, case management and internal workflow platforms, where accessibility and procurement requirements are as binding as the features.
Nearly every SaaS product now has an AI feature, and most of them are a chat box nobody opens twice. We build AI into the places where it removes real work: the parts of the product where a user is reading, classifying, summarising or waiting, and the parts of your operation you would otherwise have to staff.
Assistants scoped to the tenant's own data with permissions enforced at retrieval, so a user can never surface a record they would not otherwise be allowed to open.
Turning the PDFs, invoices and forms your users currently retype into structured records, with a confidence score and a human review queue rather than blind trust.
Routing, classification and next-step suggestions inside existing workflows, where the model proposes and the system still enforces your business rules.
Churn, demand and risk scoring trained on your platform's own usage history, surfaced where someone can act on it rather than in a monthly report.
Detection across usage, billing and access patterns, tuned so a genuinely busy tenant does not trip the same alarm as an account takeover.
Retrieval over tenant-scoped content with vector indexes partitioned per tenant, so relevance improves without ever crossing an isolation boundary.
Tenant isolation applies to AI features exactly as it does to everything else. Vector indexes are partitioned per tenant, prompts carry permission context, model outputs are logged for audit, and we make the training and retention posture explicit so it can be answered in a security review rather than discovered in one.
In B2B SaaS the integration list is often what closes the deal. We build the API-first core that makes integrations cheap to add, then the specific connectors your sales conversations keep asking for.
Not seeing yours? If it has an API, we can integrate it — and because the platform is API-first underneath, a new connector is a scoped piece of work rather than a re-architecture. Every integration ships with sync monitoring, so a silently failing connector surfaces as an alert instead of a support ticket three weeks later.
Enterprise buyers do not ask whether you are secure. They send a spreadsheet with two hundred questions and wait. These controls are cheap to build in during architecture and painful to retrofit once you have live customers and a deal on the line.
TLS in transit, encryption at rest with managed keys, and field-level encryption where the data warrants it.
Role-based access enforced server-side, with custom roles for enterprise tenants and no shared admin logins.
An append-only record of security-relevant events, retained and exportable in the format auditors expect.
Credentials in a managed vault with rotation, never in source control, environment files or a shared document.
Automated backups with tested restores and documented recovery objectives, verified rather than assumed.
Dependency scanning, container scanning and patch cadence wired into CI so findings block a release.
Per-tenant retention policies and verifiable deletion, which is what makes a GDPR request answerable.
Alerting, escalation paths and a documented runbook, so a 2am incident follows a process rather than instinct.
Frameworks we build to
We build to the technical controls each framework requires and produce the architecture and control documentation your auditor asks for. Which of these apply depends on your market and your buyers, and that is settled during discovery rather than assumed.
Idea Usher is a software development partner, not an auditor, law firm or certification body. We build to the technical controls these frameworks require and document them for review. The certification or attestation itself is issued by a qualified third party, and we build to the requirements they and your counsel define.
A stack list tells you nothing on its own. What matters is why one option gets picked over another for your product, so each group below includes the decision rule we actually apply during architecture.
The service layer, APIs and business logic that everything else depends on.
The application your customers and their admins use every working day.
Where tenant data lives, and what keeps it separated and fast.
Everything runs in your accounts, defined as code, from the first deployment.
For products where the work genuinely happens away from a desk.
What makes shipping routine and incidents short.
We write down everything you need first, then build the platform one feature at a time rather than as one large reveal at the end. Every stage below has a duration and a named deliverable you sign off on, so you always know what you are getting and when.
We document your business model, target customers, core workflows, pricing model, compliance obligations and the integrations your buyers will ask for, then turn that into a written spec and a feature-by-feature roadmap.
We select the tenancy model, design the data isolation approach, map service boundaries, choose the stack against your constraints and model per-tenant infrastructure cost at your target scale.
We design the customer app, the tenant admin area and your internal console as clickable prototypes, so layout and flow disagreements happen in Figma rather than in code.
We build in a fixed order: tenancy and auth, then the core workflow, then billing, then admin tooling. Each piece ships to staging with its own automated tests as it is finished, with a working demo at the end of every sprint.
Public API, webhooks, SSO and the specific connectors your pipeline needs, each built against the vendor's sandbox and verified before it touches live tenant data.
Full regression, load testing against realistic tenant distributions, penetration testing, and explicit tenant-isolation tests that fail the build if data can cross a boundary. Testing everything together catches the interactions that testing features alone cannot.
You and your team use the platform yourselves, checked line by line against the requirements list from stage one. Anything that does not match gets fixed and re-verified before a launch date is on the table.
Production deployment into your cloud accounts with on-call coverage through the first weeks, then the ongoing work: monitoring, incident response, security patching, cloud cost optimisation and the next round of features.
Most agencies hide this in an FAQ as a single number spanning an order of magnitude. Three shapes of build cover almost every SaaS engagement we take — what moves the number is how many integrations you need on day one, whether compliance certification is required at launch, and how many user roles the product supports.
$60K – $140K*
3–5 months to first paying customer
$150K – $350K*
6–10 months to launch
????*
Scoped per engagement
Scope bigger than these tiers, or a model that does not fit them?
Custom Request — Get a Quote NowCost and timeline above are estimates only, not fixed quotes — your exact number is scoped on a free call.
Cloud hosting, third-party software licences, payment processing fees and audit or certification costs sit outside the build and vary by scale and jurisdiction. We quote the engineering, help you model the running cost per tenant during architecture, and keep both numbers visible rather than surfacing the second one after launch.
The right model depends on how defined your scope is and whether you already have engineers. We will tell you honestly which one fits, including when the answer is a smaller engagement than you came in asking for.
A defined deliverable with a fixed price and timeline. Best when the requirements are settled and you want budget certainty, typically after a discovery engagement has done the hard thinking.
A named cross-functional team — engineers, designer, QA and a delivery lead — working only on your product, with roadmap priorities you set each sprint. The most common model for a platform that will keep evolving.
Specific engineers embedded into your existing team and processes, reporting into your leads. Best when you have an engineering function that needs capacity or a specific skill rather than a whole team.
Custom development is not always the right answer, and we will say so on a call. But if you are weighing the options for a platform you intend to sell for years, these are the trade-offs that actually show up eighteen months in.
| What matters at scale | Low-Code Platform | Cheapest Offshore Shop | Hiring In-House | Idea UsherCustom SaaS Build |
|---|---|---|---|---|
| Time to first customer | Fastest | Varies wildly | 6+ months to hire | 3–5 months |
| Multi-tenancy done properly | Platform's model only | Usually a tenant column | Depends who you hire | Chosen in week one |
| Cost per tenant at scale | Per-seat licence forever | Rarely modelled | Learned the hard way | Modelled before build |
| Enterprise security review | Inherits their posture | Retrofitted in panic | Needs a security hire | Controls built in |
| Billing beyond a checkout | Basic plans only | Scoped as one ticket | Underestimated | A first-class subsystem |
| You own the code | Locked to the platform | Varies by contract | Yes | Full ownership, your cloud |
| Documentation & handover | Vendor docs only | Rarely produced | Often skipped | Runbooks, IaC and ADRs |
| Continuity if someone leaves | Platform continues | Project stalls | Key-person risk | 250+ team, documented |
Different starting points, same platform underneath. What changes is which layer we build first and how much of the compliance surface has to exist on day one.
Validated demand and a board expecting a launch date, with no in-house platform team yet.
Turning a proven manual service into software their existing clients will pay a subscription for.
Holding a working product installed per customer and needing it to become one cloud platform.
An internal tool good enough that the company wants to sell it to its own industry.
A product that works but an architecture that will not hold the next order of magnitude.
Selling infrastructure to other operators, which needs multi-tenancy and white-label from day one.
Healthcare, finance and public sector, where compliance shapes architecture before features do.
An existing engineering function that needs a squad or a specific skill rather than a whole vendor.
SaaS products fail on the parts nobody demos: the tenancy model that will not scale, the billing edge case that quietly loses revenue, the security question that stalls a deal for a quarter. Those are engineering problems, and they are the part we are good at.
Product design, frontend, backend, billing, integrations, infrastructure, security and QA handled by one team rather than stitched across three vendors.
The tenancy model is chosen in week one against your buyers and compliance obligations, because it is the one decision that is genuinely expensive to reverse.
Source code, cloud accounts and IP are yours from the first deployment, with documented handover so an in-house team can take over whenever you choose.
SOC 2, HIPAA and GDPR technical controls built into the data model and infrastructure, so your first enterprise security review is a form rather than a project.
Published tiers and a two-week scoping exercise instead of a number that spans an order of magnitude buried in an FAQ.
Monitoring, incident response, security patching, cloud cost work and the next round of features, so the roadmap keeps moving past go-live.
Bring us your product and target customers and we will map the tenancy model, the billing model, the integration surface and the compliance requirements, then hand you a scoped estimate with a realistic timeline.
Book a Free Strategy CallThe eight questions that come up in almost every first call about a SaaS build, answered the way we would answer them on that call.
A production-grade SaaS MVP covering onboarding, multi-tenancy, billing, one core workflow and admin tooling generally runs $60,000 to $140,000. A full platform with deeper workflows, integrations, analytics and a mobile app typically runs $150,000 to $350,000. Enterprise platforms with heavy compliance, complex tenancy or multi-region infrastructure start around $350,000. Cloud hosting, third-party licences, payment processing fees and audit costs sit outside the build. Every figure here is an estimate, not a fixed quote, and your exact number comes out of a two-week scoping exercise.
A focused MVP usually takes three to five months from kickoff to first paying customer. A full platform runs six to ten months, and enterprise builds with compliance certification and multi-region infrastructure run ten months and up. The variables that move the timeline most are how many integrations you need on day one, whether you require SOC 2 or HIPAA at launch rather than later, and how many user roles the product has to support.
Multi-tenancy is how one running application serves many customers while keeping each customer's data separate. There are three common models. A shared database with a tenant ID on every row is the cheapest to run and the fastest to ship. A separate schema per tenant gives stronger isolation with moderate operational overhead. A separate database per tenant gives the strongest isolation and is often what regulated enterprise buyers require. The right answer depends on your customer size, your compliance obligations and your cost target, and it should be settled in architecture rather than retrofitted later, because changing tenancy model after launch is close to a rebuild.
Yes, and it is usually underestimated. We build plan and pricing configuration, seat and usage metering, trials, upgrades and downgrades with correct proration, coupons, dunning and failed-payment recovery, tax handling, invoicing, and revenue reporting that reconciles to the cent. We wire this to Stripe, Chargebee, Paddle or whichever provider fits your model, and we keep pricing logic configurable so you can change plans without a code release.
We build to the technical controls those frameworks require: encryption in transit and at rest, role-based access control, audit logging, secrets management, backup and recovery, vulnerability management and infrastructure-as-code so your environment is reproducible and reviewable. We also produce the architecture and control documentation your auditor will ask for. We are a software development partner rather than an auditor or law firm, so the certification itself is issued by a qualified third party, and we build to the requirements they and your counsel define.
Yes. You own the source code, the infrastructure accounts and the intellectual property outright, and we hand over documented repositories, infrastructure-as-code, runbooks and architecture decision records at the end of the engagement. The platform runs in your cloud accounts from the first deployment rather than ours, so there is no migration event when the engagement ends and no dependency on us to keep operating.
Yes, and it is one of the more common engagements we take. The usual starting point is single-tenant software installed per customer, or an on-premise product your team maintains across many versions. We assess the current codebase, design the tenancy and data isolation model, build the tenant provisioning and billing layer, then migrate customers in waves with a rollback path at each wave rather than in one switchover. Existing customer data and uptime commitments shape the sequence more than the code does.
Most clients keep us on for platform engineering after launch, because a SaaS product is never finished. That covers monitoring and on-call coverage, incident response, security patching, cloud cost optimization, and the next round of features and integrations. We also hand over enough documentation and knowledge transfer that an in-house team can take ownership whenever you are ready, which is the point of owning the code and the infrastructure in the first place.
We build SaaS platforms from the tenancy model to the user interface. Whether you are launching a new product, productising a service, or moving on-premise software to the cloud, we build the complete technology underneath it — and hand you the keys.
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