Kindlebit
Product Engineering and QAPublicly listed capability

Engineer a SaaS platform that scales with your customers and ships without drama.

We build web and SaaS products with clean multitenant architecture, authentication, billing, cloud infrastructure and automated delivery, and modernise legacy applications without stopping the business.

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Kindlebit publicly lists this capability on its website or a third party profile. Named, approved project evidence is being compiled and will be added when Kindlebit confirms it.

SaaS architecture

  1. Web client
  2. API layer
  3. Tenant and auth
  4. Billing
  5. Data stores
  6. Observability

Reference design. Components are options, not a statement of what is deployed at any customer.

Problems this service is built to solve

These are situations we expect buyers to recognise. Each one states why it happens, what it costs and how we would approach it.

Applications struggling to scale

A scheduling product runs fine with fifty customers. At five hundred, page loads slow, nightly jobs overrun into business hours and the database is at its limit every Monday morning.

Why it happens
The first version was built for speed to market, with shared state, unindexed queries and work done inside web requests.
What it costs
Churn from slow performance, firefighting that blocks new features and cloud spend that grows faster than revenue.
How we approach it
We profile real workloads, fix queries and indexes, move heavy work to queues, add caching and plan data partitioning, guided by load tests rather than guesses.
What to measure
p95 latency, error rate, cost per tenant and headroom at target load.

Slow product launches

Every release needs a weekend, a manual checklist and a freeze. Features sit finished for weeks waiting for a window.

Why it happens
Deployment is manual and risky, tests are thin and environments differ.
What it costs
Slow feedback, bigger releases and more defects per release.
How we approach it
We automate build, test and deployment, create production like environments, use feature flags and small releases, and add monitoring so problems are caught early.
What to measure
Deployment frequency, lead time for changes, change failure rate and time to restore.

Multitenant security complexity

A bug in a report query omits the tenant filter and one customer briefly sees another's rows. It is caught by a customer, not by the team.

Why it happens
Tenant isolation is implemented ad hoc in each query rather than enforced centrally.
What it costs
A serious data incident, contractual penalties and loss of enterprise deals.
How we approach it
We choose an isolation model (shared schema with row level security, schema per tenant or database per tenant) based on risk and scale, enforce it in the data layer, and add automated isolation tests.
What to measure
Isolation test coverage, cross tenant defects and time to onboard an enterprise security review.

Legacy technology constraints

The core product runs on a framework version that no longer receives security updates. Few engineers know it and every change is risky.

Why it happens
Years of changes without tests or documentation, and a platform that has been left behind.
What it costs
Security exposure, hiring difficulty and slow delivery.
How we approach it
We use incremental modernisation: characterise behaviour with tests, wrap legacy with APIs, migrate module by module with the strangler pattern and keep the product live throughout.
What to measure
Share of traffic on the new stack, defect rate per release and time to deliver a change.

Solutions we engineer

Concrete capabilities, each with the need it serves, how it integrates, what you receive and the value to expect.

Multitenant architecture

Tenant model, isolation enforcement, per tenant configuration and noisy neighbour controls.

Customer need
Serve many customers safely and economically.
Integration
Database, identity and cloud infrastructure.
Deliverable
Architecture, implementation and isolation tests.
Business value
Safe scale and enterprise readiness.

Authentication and authorisation

Role based access, SSO with SAML and OIDC, MFA, audit logs and API keys.

Customer need
Secure access with enterprise features.
Integration
Auth0, Okta, Entra ID, Cognito or custom.
Deliverable
Identity and access layer.
Business value
Meets enterprise security requirements.

Subscriptions and billing

Plans, trials, usage metering, invoices, taxes and entitlement enforcement.

Customer need
Monetise reliably.
Integration
Stripe, Chargebee or Recurly and your accounting system.
Deliverable
Billing service and entitlement model.
Business value
Accurate revenue and flexible pricing.

Cloud native deployment

Containers, infrastructure as code, autoscaling, backups and disaster recovery plans.

Customer need
Reliable, repeatable infrastructure.
Integration
AWS, Azure or Google Cloud.
Deliverable
Infrastructure code and runbooks.
Business value
Reliability and controlled cost.

CI/CD and release engineering

Pipelines with unit, integration and end to end tests, security scans, staged rollouts and feature flags.

Customer need
Ship often with confidence.
Integration
GitHub Actions, GitLab CI or Azure DevOps.
Deliverable
Pipelines and release process.
Business value
Faster, safer delivery.

API and integration layer

Versioned public APIs, webhooks, rate limits and documentation.

Customer need
Let customers and partners connect.
Integration
Customer systems and marketplaces.
Deliverable
API and developer docs.
Business value
Stickiness and ecosystem.

Legacy modernisation

Incremental migration, data migration with reconciliation and parallel run.

Customer need
Move forward without a freeze.
Integration
Existing application and databases.
Deliverable
Migration plan and delivered modules.
Business value
Lower risk and continuous delivery.

How we solve it

A delivery sequence built around architecture, testing, CI/CD and operational readiness.

Clarify product and constraints

Define users, tenants, scale targets, compliance needs and the first release outcome.

Design architecture

Choose the tenancy model, data design, service boundaries and cloud setup, and record decisions with their trade offs.

Design the product and APIs

Detail flows and API contracts, plan the data model and design for observability from the start.

Build in increments

Deliver working slices every sprint with code review, automated tests and demos to stakeholders.

Integrate and migrate

Connect identity, billing and third party systems, and migrate data with reconciliation checks.

Validate quality and security

Run functional, performance and security testing, including tenant isolation, dependency scanning and accessibility checks.

Deploy and operate

Release through the pipeline with staged rollout, monitoring and runbooks. Agree service levels.

Improve continuously

Review metrics, incidents and costs each sprint, and plan technical debt work alongside features.

Solution in action: Launching a multitenant analytics SaaS with enterprise sign in

Reference Architecture An illustrative scenario. It describes how we would structure the work, not a delivered customer project.

Starting problem

A company wants to turn an internal reporting tool into a product for external customers.

Existing workflow

A single customer internal application with shared tables, local accounts and manual deployments.

Improved workflow

The product is rebuilt around a tenant model with row level security, SSO and role based access, plans and usage metering through a billing provider, and a pipeline that deploys on every merge after tests. A public API and webhooks let customers feed data in.

A new customer signs up.

Systems involved

Web application, API, identity provider, billing provider, database, queue, monitoring.

Data movement

Tenant scoped data, usage events and billing records.

Human decisions

Customer admins manage users and plans. Support staff access tenant data only through audited tooling.

Automation opportunities

Provisioning of a new tenant, entitlement checks and deployment.

Exception handling

Failed payments move accounts to a grace state and notify admins instead of cutting access immediately.

Resulting user experience

A new customer signs up, connects SSO and loads data on the same day, and sees only its own data.

KPIs to evaluate

  • Availability
  • Activation rate
  • p95 latency
  • Deployment frequency

What you receive

Concrete deliverables for this service, written so you can check them against the contract.

  • Architecture decision records and diagrams
  • Deployed application in staging and production
  • Tenant isolation design and automated tests
  • Identity, billing and API integrations
  • Infrastructure as code and CI/CD pipelines
  • Automated test suites across layers
  • Monitoring dashboards, alerts and runbooks
  • Technical documentation and developer onboarding guide

Technology and engineering

Options we would evaluate for this service. Unless a group is marked as publicly listed on kindlebit.com, treat each tool as a proposed implementation option. Naming a tool does not imply a vendor partnership.

Front end

  • React
  • Next.js
  • Vue
  • Angular
  • TypeScript

Back end

  • Node.js
  • Python
  • FastAPI
  • .NET
  • ASP.NET Core
  • Java

Data

  • PostgreSQL
  • MySQL
  • SQL Server
  • MongoDB
  • Redis

Cloud and delivery

  • AWS
  • Azure
  • Google Cloud
  • Docker
  • Kubernetes
  • Terraform
  • GitHub Actions

Publicly listed Kindlebit stack

  • Node.js
  • Python
  • .NET Core
  • React
  • AngularJS

Relevant Kindlebit work and evidence

We use the strongest evidence available and say which kind it is.

Reference ArchitectureInteractive demo with simulated data

AI Powered SaaS Product demonstration

A simulated multitenant application with tenant isolation logic, plan entitlements, search, an assistant and observability. It is a reference demonstration built with synthetic data.

Open the demonstration

Business outcomes and success criteria

These are the measures we would agree before work starts. They are criteria for success, not results from past engagements.

Availability

Uptime against the agreed service level.

Activation

Share of new tenants reaching first value.

Latency

p95 response time at target load.

Deployment frequency

Releases per week with change failure rate.

Questions buyers ask

Which technology stack will you use?

We select it based on your team, hiring market, performance needs and hosting. We work in React, Next.js, Node.js, Python and .NET, and document the reasons for the choice.

How long to build an MVP?

Commonly three to five months for a focused product, depending on scope, integrations and compliance. We define a first release that tests the riskiest assumptions.

How do you secure a multitenant system?

By enforcing tenant isolation in the data layer, using least privilege access, testing isolation automatically and logging access. We also support enterprise requirements such as SSO.

Can you take over an existing codebase?

Yes. We start with a code, security and architecture review, then agree a plan to stabilise, document and extend it.

Who owns the code?

Ownership is defined in the contract. Our standard approach is that you own the code built for you, and we use open standards and avoid proprietary lock in.

How do you price?

Fixed scope for well defined phases or a dedicated team for evolving products. Cloud and third party licences are itemised separately.

Related services

Industries where this applies

Discuss your SaaS platform architecture.

Describe the product, the customers and the scale you expect. We will outline the architecture and the first release.

Review your platform architecture Explore a demonstration