Backend
Node
Our default API and service runtime where throughput and developer velocity both matter.
BackendREST and GraphQL APIsIntegration and orchestration services
Where we use it
Workloads we build with Node
REST and GraphQL APIs
Integration and orchestration services
Real-time and streaming features
Strengths
Why we choose it
- Shared language with the frontend
- Excellent I/O concurrency
- Mature package ecosystem
Considerations
What we watch for
- CPU-heavy work belongs elsewhere
- Dependency hygiene must be enforced
Services using this technology
Enterprise AIAI that runs inside your business, under your control.Business AutomationRemove manual effort from the workflows that carry your business.Custom SoftwarePlatforms engineered around your process, not the other way round.Digital TransformationModernise the estate without stopping the business.Cloud & InfrastructurePlatforms that are cheap to run and safe to change.
Industries where we deploy it
HealthcareClinical throughput, administrative relief and defensible data handling.ManufacturingConnected plants, predictable output, lower unplanned downtime.FinanceFaster decisions, defensible controls, lower cost to serve.GovernmentCitizen services, digitised process and auditable delivery.EducationAcademic operations, student experience and institutional reporting.LogisticsCost per shipment down, exceptions handled before they escalate.RetailDemand accuracy, margin protection and connected commerce.MiningSafety, asset uptime and site-to-corporate visibility.Real EstatePortfolio visibility, faster sales cycles, tighter project control.HospitalityOccupancy, guest experience and lean back-office operations.NGOMore programme impact per rupee of overhead.EnergyAsset reliability, consumption intelligence and compliance evidence.ConstructionProgramme certainty, cost control and site-level visibility.Professional ServicesHigher utilisation, faster delivery, protected margin.
Pairs well with
Capabilities built on Node
LLM IntegrationEmbedding language models into existing applications, APIs and business workflows.AI IntegrationConnecting AI capability to ERP, CRM, service desk and line-of-business systems.RPARobotic process automation for systems that expose no integration layer.Enterprise IntegrationA managed integration layer replacing point-to-point interfaces.API IntegrationDesigned, versioned and secured APIs across your application estate.Workflow AutomationRouting, approvals and hand-offs automated across teams and systems.
Related insights
Why enterprise AI pilots stall — and what changes when they do notThe gap between a working demo and a production system is organisational, not technical.Automation that survives auditDesigning RPA and document automation with controls, logging and ownership from day one.Modernising legacy systems without a big-bang cutoverIncremental strangulation beats a single weekend of concentrated risk.
Assess and plan
AI Readiness AssessmentScore your organisation across six readiness dimensions in about ten minutes.Enterprise AI Readiness ChecklistThe seven-dimension checklist we use before committing to an enterprise AI programme.Downloads centreCapability statement, readiness checklist and other practitioner material.
Downloadable guide
Node engineering standards
Our reference architecture, code standards, testing approach and operational checklist for this technology.
Need this stack delivered by
people who have run it in production?
Architecture review, team augmentation or full delivery — we will show you reference implementations before you commit.