Nexasoft

The right technology,for your problem.

We don't sell a favourite framework. We choose proven, well-supported technology that fits your goals, your team and the systems you already run, and we explain every choice in plain language.

Stack layers covered
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Major clouds
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Practices on every project
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  • Proven, well-supported technology
  • Everything in your accounts
  • Security and testing in every release

How we choose

Every option passes five checks.

  1. Every option
  2. FitSolves your problem, not ours
  3. OwnershipYour team can run it
  4. MaturityProven and well supported
  5. CompatibilityWorks with what you run
  6. CostAffordable over five years
  7. Your stack

What we build with

And when we'd recommend each one.

Every product we build sits on the same eight layers. The experience your users see sits on top; the infrastructure that runs it sits at the base.

Security and quality aren't separate stages. They run alongside every layer, from the first line of code to production. Select a layer to see what we use and when we'd recommend it.

Web

Fast, accessible interfaces that work on every screen.

  • ReactInteractive interfaces, dashboards and portalsWhen:You need a rich UI and a large pool of developers to maintain it
  • Next.jsReact apps with server rendering and static pagesWhen:Search visibility and first-load speed matter, such as public sites and storefronts
  • TypeScriptTyped JavaScript across front end and back endWhen:Always; types catch whole classes of bugs before release
  • Tailwind CSSConsistent styling and design systemsWhen:You want a design system that stays consistent as the team grows

Mobile

Apps people keep on their home screen.

  • FlutterOne codebase for iOS and AndroidWhen:You need both platforms quickly with a shared team and budget
  • Swift and SwiftUINative iOS appsWhen:The app depends on deep device features or top-tier iOS performance
  • Kotlin and Jetpack ComposeNative Android appsWhen:The same, on Android; Kotlin is Google's preferred language for Android

Backend and APIs

The services, APIs and data stores behind every product.

  • Node.jsAPIs and real-time servicesWhen:Workloads are I/O-heavy and the team already writes TypeScript
  • Java and Spring BootLarge business systemsWhen:Banking and enterprise systems that need maturity and long-term support
  • .NET (C#)Business applications and APIsWhen:You run a Microsoft environment such as Azure, SQL Server and Entra ID
  • Python and FastAPIData and AI servicesWhen:The service sits close to data science or machine learning work
  • GoHigh-throughput servicesWhen:Very high request volumes with low latency, such as order or event pipelines
  • PostgreSQLPrimary relational databaseWhen:Our default for transactional data: reliable, open source, widely supported
  • RedisCaching, sessions and queuesWhen:Hot data must be served in milliseconds
  • Apache KafkaEvent streaming between systemsWhen:Many systems need the same events reliably and in order

Data and AI

From raw data to dashboards, models and assistants.

  • SnowflakeCloud data warehouseWhen:Analytics teams need fast SQL over large data with little infrastructure to manage
  • DatabricksLakehouse for data engineering and machine learningWhen:Large or unstructured data and ML workloads on Apache Spark
  • dbtTested, version-controlled data transformationsWhen:Always alongside a warehouse; it makes data pipelines reviewable like code
  • Power BIDashboards and reportsWhen:Business users live in Microsoft 365 and need self-serve reporting
  • scikit-learn and PyTorchMachine learning modelsWhen:Forecasting, scoring and classification on your own data
  • LLM APIs with retrieval (RAG)Assistants and document automation grounded in your contentWhen:Answers must come from your documents, with sources, not the model's memory

Cloud and DevOps

Infrastructure that's automated, observable and repeatable.

  • AWS, Azure, Google CloudHosting, managed databases and servicesWhen:We match the cloud to your existing contracts, skills and compliance needs
  • TerraformInfrastructure as codeWhen:Always; every environment is created from reviewed code, never by hand
  • DockerPackaging services consistentlyWhen:Always; the same container runs on a laptop and in production
  • KubernetesRunning many containerised servicesWhen:You operate many services that need scaling and self-healing; for a few, simpler managed options are often better
  • GitHub ActionsCI/CD pipelinesWhen:Every change should be built, tested and deployed automatically
  • Grafana, Prometheus or DatadogMonitoring, logs and alertsWhen:Always; we agree service levels and alert on them from day one

Enterprise platforms

The systems large organisations already run on.

  • SAP S/4HANAERP: finance, supply chain, manufacturingWhen:You need an integrated ERP with industry processes built in
  • SalesforceCRM for sales, service and marketingWhen:Customer-facing teams need one shared view of every customer
  • ServiceNowIT and employee service managementWhen:Requests, incidents and approvals need one workflow platform
  • MuleSoftIntegration between enterprise systemsWhen:Many systems must exchange data through managed, reusable APIs

Security

Protection built into every layer, not added at the end.

  • Microsoft Entra ID, OktaSingle sign-on, MFA and access controlWhen:Always; one identity layer for every app
  • OWASP ASVS and OWASP ZAPSecurity requirements and automated scanningWhen:Always; ASVS sets the bar, ZAP checks every build
  • Burp SuiteManual penetration testingWhen:Before major releases and on a regular schedule
  • Snyk or DependabotDependency vulnerability scanningWhen:Always; most modern code is open-source dependencies
  • Microsoft Sentinel, SplunkSecurity monitoring (SIEM)When:You need 24×7 detection across systems

Quality and testing

Confidence in every release.

  • Vitest and JestUnit testsWhen:Always, for business logic
  • PlaywrightEnd-to-end browser testsWhen:Always, for critical user journeys such as sign-up and checkout
  • k6Load and performance testingWhen:Before launches and expected traffic peaks
  • SonarQubeCode quality and coverage checksWhen:Always, as a gate in the pipeline

How we design systems

The simplest architecture that will still work in three years.

  • Modular monolith

    One deployable application, split internally into clearly separated modules.

    We use it when

    Our default for new products: simpler to build, test and run, and modules can be split out later.

  • Microservices

    Independent services, each owning its data and deployed separately.

    We use it when

    Several teams must ship independently, or parts of the system scale very differently.

  • Event-driven

    Systems publish events, such as “order placed”, that others react to.

    We use it when

    Many systems need the same change reliably, such as orders flowing to inventory, billing and analytics.

  • API-first and headless

    The API is designed first; web, app and partners all use it.

    We use it when

    The same data serves several channels, such as web, mobile, store and marketplaces.

  • Strangler fig modernisation

    A new system grows around the old one, replacing it feature by feature.

    We use it when

    Replacing a legacy system the business can't afford to switch off in one go.

  • Serverless functions

    Small pieces of code run on demand by the cloud provider.

    We use it when

    Workloads are spiky or infrequent, such as file processing, schedules and webhooks.

How we build and ship

Six practices on every project, whatever the stack.

  • Every change is reviewed

    No code reaches the main branch without a pull request approved by another engineer.

  • Automated pipelines

    Every commit is built, tested and scanned automatically; releases go out through the pipeline, never by hand.

  • Infrastructure as code

    Servers, networks and permissions are defined in Terraform and reviewed like application code, so environments can be rebuilt exactly.

  • Tests at three levels

    Unit tests for business logic, integration tests for APIs and end-to-end tests for critical user journeys.

  • Observability from day one

    Logs, metrics and alerts are set up before launch against agreed service levels, so problems are seen before users report them.

  • Documented decisions

    Significant technical choices are recorded as short architecture decision records, so your team knows why the system is built the way it is.

AI that holds up in production

Useful, measurable and under your control.

Most AI pilots fail not because the model is weak, but because nobody measured it, nobody checked its answers and nobody owned the data. We build those guardrails first.

  • Start with one measurable use case

    We agree a business metric (hours saved, error rate, response time) and a baseline before building anything.

  • Grounded in your data

    Assistants answer from your approved documents using retrieval, and show their sources.

  • Evaluated before and after launch

    We test against real examples, track accuracy over time and alert when quality drops.

  • Humans review low-confidence cases

    Anything the system is unsure about goes to a person, and those decisions improve the system.

  • Your data stays protected

    Enterprise AI services configured so your data isn't used to train providers' models, within the region and access rules you set.

Technical questions

Stack, lock-in and architecture.

Often, yes. The list shows what we use most. If your system runs on something else, we'll tell you honestly how much experience we have before we start.

No. We use mainstream, well-documented technology, keep everything in your repositories and cloud accounts, and document key decisions, so any competent team can take over.

Not by default. AWS, Azure and Google Cloud are all strong; the right one usually depends on your existing contracts, team skills and compliance needs.

No. For most new products we start with a well-structured modular monolith, which is simpler and cheaper to run, and split out services only when there's a clear reason.

Automated tools flag outdated and vulnerable packages on every build, and support agreements include regular, planned upgrades.

Ready to move your business forward?

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