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Deploint

Capability 02

Mission-critical software, engineered to scale.

We design and build the systems organizations run on: distributed services, APIs, real-time and workflow platforms, and the web and mobile applications in front of them, engineered for reliability and long-term maintainability.
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Capability 02

06 stages

Core disciplines

  • Distributed systems
  • Microservices
  • APIs
  • Real-time systems
  • Workflow platforms
  • Web & mobile

Works alongside

01Services

What we engineer.

Software built to be operated for years: clear boundaries, tested contracts, automated delivery and the telemetry to understand it in production.
  • 01

    Enterprise SaaS

    Multi-tenant platforms with tenant isolation, metering, role-based access and configuration models that scale across customers without forks.

  • 02

    Distributed systems

    Services that stay correct under partial failure, using idempotent operations, timeouts, retries with backoff and explicitly chosen consistency models.

  • 03

    Microservices

    Service boundaries drawn around business capabilities, with independent deployment, owned data and explicit contracts. We also say when a modular monolith is the better choice.

  • 04

    APIs

    REST and GraphQL APIs with schema-first design, versioning, authentication, rate limiting and contract tests that protect every consumer.

  • 05

    Real-time systems

    Event-driven and streaming systems using WebSockets, server-sent events and message brokers, designed for low latency and graceful degradation under load.

  • 06

    Workflow platforms

    Long-running, multi-step business processes with durable state, retries, compensation and human tasks, built on workflow engines rather than ad hoc scripts.

  • 07

    Mobile

    iOS and Android applications, native or cross-platform, with offline support, secure on-device storage and pipelines for staged releases.

  • 08

    Web applications

    Accessible, performant web applications with server rendering where it matters, shared design systems and end-to-end tests.

  • 09

    Legacy modernization

    Incremental replacement of legacy components behind stable interfaces, so new software ships without a risky big-bang cutover.

02Reference architecture

A service architecture built for change.

A typical shape for the platforms we build. Select a layer to see its responsibilities and the components involved.

Web, mobile and partner integrations, each consuming APIs designed for its needs. Clients never couple directly to service internals.

  • Web apps
  • Mobile apps
  • Partner systems
  • Internal tools

03Technology ecosystem

Technologies we engineer with.

A deliberately focused toolset. We choose technologies for operational maturity and for the team that will own the system, not for novelty.

  • Layer 01

    03 tech

    Frontend

    Interfaces that are fast, accessible and maintainable.

    • ReactComponent-based interfaces and design systems
    • Next.jsServer-rendered and static web applications
    • TypeScriptTyped contracts shared across client and server

  • Layer 02

    05 tech

    Backend

    Languages matched to workload characteristics.

    • PythonAPIs, data services and ML-adjacent workloads
    • Node.jsI/O-bound services and backend-for-frontend layers
    • GoHigh-concurrency services and infrastructure tooling
    • JavaEnterprise services on the JVM
    • C++Performance-critical and resource-constrained components

  • Layer 03

    02 tech

    Data

    Storage chosen per access pattern.

    • PostgreSQLRelational system of record with strong consistency
    • RedisCaching, rate limiting, queues and ephemeral state

  • Layer 04

    03 tech

    Messaging & APIs

    Contracts between services and their consumers.

    • KafkaDurable event streaming, replay and change propagation
    • GraphQLClient-shaped queries across many backend services
    • RESTResource-oriented APIs with stable, versioned contracts

Technologies listed are ones our engineers build with. Listing them does not imply a partnership with, or endorsement by, any vendor.

04Distributed systems

Patterns for systems that fail gracefully.

Distributed software fails in partial and surprising ways. These are the patterns we reach for to keep systems correct and available.

01Correctness

The right answer under retries and concurrency.

  • Idempotency

    Operations that produce the same result when applied more than once, usually enforced with idempotency keys stored alongside the result. It makes retries safe, which matters because networks and clients do retry. Payment, order and provisioning APIs should be idempotent by design.

  • Transactional outbox

    Writing a business change and the event that announces it in the same database transaction, then publishing the event asynchronously. It removes the dual-write problem, where the database update succeeds but the message is lost, or the reverse.

  • Sagas

    A long-running business transaction split into local steps, each with a compensating action that undoes it if a later step fails. Sagas replace distributed transactions across services, trading atomicity for availability with explicit, testable failure handling.

02Resilience

Containing failure so it does not spread.

  • Timeouts and retries

    Every remote call has a timeout, and retries use exponential backoff with jitter and a retry budget. Without them, one slow dependency can exhaust threads and connection pools and take its callers down with it.

  • Circuit breakers

    A wrapper that stops calling a failing dependency after an error threshold and fails fast until health checks pass. It protects both sides: the caller keeps responding, and the dependency gets room to recover.

  • Backpressure

    Mechanisms that let a busy consumer slow its producers rather than accumulate unbounded queues: bounded buffers, rate limits and load shedding. Systems that cannot say no eventually fail under load.

03Evolution

Changing systems without breaking consumers.

  • Contract testing

    Tests that verify a provider still satisfies the expectations of each consumer, run in CI on both sides. They catch breaking API changes before deployment, without slow end-to-end environments.

  • Expand and contract

    Schema and API changes made in backward-compatible steps: add the new field, migrate consumers, then remove the old one. Old and new versions can run side by side, which enables zero-downtime deployments.

  • Feature flags

    Runtime switches that separate deploying code from releasing behaviour, enabling gradual rollout, fast rollback and limited-exposure testing in production. Flags need owners and expiry dates, or they become debt.

05Engineering approach

How we engineer software.

Habits that keep systems understandable, changeable and dependable long after the first release.
  1. 01

    Boundaries first

    We spend early effort on domain boundaries and contracts, because they are the most expensive decisions to change later.

  2. 02

    Simple until proven otherwise

    We start with the simplest architecture that meets the requirements, often a modular monolith, and split only where scale or team structure demands it.

  3. 03

    Automated from the first commit

    CI, tests, infrastructure as code and preview environments exist before features do.

  4. 04

    Designed for failure

    Timeouts, retries, idempotency and graceful degradation are requirements, verified with failure testing rather than assumed.

  5. 05

    Observable by default

    Every service emits structured logs, metrics and traces, with SLOs that reflect what users experience.

  6. 06

    Built to hand over

    Architecture decision records, runbooks and readable code, so your teams can own the system with confidence.

06Industries

Where we apply software engineering.

Platforms and applications built for the operational realities of each sector.
All industries

07Concept architectures

Software reference architectures.

Illustrative engineering references that show how we approach a problem. They are concept architectures, not descriptions of client engagements.
All case studies

08FAQ

Common questions.

Straight answers on how we approach Software Engineering.
01Do you build microservices or monoliths?

Whichever fits. Many systems are better served by a well-structured modular monolith with clear internal boundaries. We introduce separately deployed services where independent scaling, release cadence or team ownership justify the operational cost.

02Which languages and frameworks do you use?

Mainly TypeScript, React and Next.js on the frontend, and Python, Node.js, Go, Java and C++ on the backend, with PostgreSQL, Redis and Kafka underneath. We also work within your existing stack when that is the better long-term choice for your team.

03Can you work alongside our in-house engineering team?

Yes. We can own a system end to end, deliver a defined component or embed engineers in your teams. In every model we work in your repositories and toolchain, follow shared conventions and document decisions so ownership can transfer cleanly.

04How do you ensure software quality and maintainability?

Code review on every change, automated unit, integration and contract tests in CI, static analysis, and architecture decision records for significant choices. We track delivery health through lead time, change failure rate and time to restore service.

05Do you build mobile applications?

Yes. We build iOS and Android applications, native or cross-platform depending on requirements, with offline support, secure on-device storage and automated build and release pipelines.

Software Engineering

Have a system that has to scale?

Tell us about the platform, its users and its constraints. We'll help you shape an architecture your teams can build on.

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