Cloud infrastructure that
holds up at
enterprise scale.

The cloud decisions you make today determine how fast you can ship, how well your systems hold up under load, and how much you pay to run everything. We have been building and migrating enterprise cloud infrastructure since the early days of AWS, Azure, and GCP, and we stay through delivery.

Explore the service lines →See it in production

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Five practices. One team.
No handoffs.

We cover the full cloud lifecycle under one roof. Strategy upfront, engineering in the middle, operations afterward — no gaps between phases, no handoffs to other firms. The same team that built the roadmap executes it.

START HERE / ADVISORY

Decide before you move.

A migration that skips planning costs more than the one that took three months to plan. We map your current state, design the target architecture, and produce a prioritised roadmap before a single workload moves.

Outputs: readiness report · architecture · TCO · security posture · roadmap
THEN / END TO END

No handoff after the plan.

The same team that built the roadmap executes it. Migration, cloud-native engineering, integration, and managed services — all from one practice with shared context on your architecture.

Covers: migration · build · integration · managed services

The full stack,
handled in-house.

Each practice connects to the next. Advisory informs the migration. Engineering runs alongside it. Integration handles what stays on-premise. Monitoring picks up when everything is live.

START HERE

Decide before you move.

Before committing budget to a migration, we map your current state — what runs where, what it costs, what the risk is, and what the right path forward actually looks like. Outputs include a cloud readiness report, reference architecture, TCO analysis, security posture review, and a prioritised migration roadmap.

Cloud readinessArchitecture designTCO analysisSecurity postureMigration roadmap

AWS. Azure. GCP.
We work across all three.

We are not tied to any one provider. We have certified practitioners across all three platforms and recommend based on your workloads, compliance requirements, existing licenses, and total cost of ownership — not on partnerships.

Amazon Web Services

EC2LambdaEKSS3AuroraRDSDynamoDBRedshiftElastiCacheShieldWAFIoT GreengrassCloudFrontKinesis

Best for workloads requiring the deepest managed-service breadth and the largest partner ecosystem.

Microsoft Azure

Virtual MachinesFunctionsContainer RegistryAzure SQLCosmos DBIoT HubAzure DNSTraffic ManagerHDInsightStream AnalyticsData Factory

Best fit when the enterprise already runs Microsoft — M365, Dynamics, or Active Directory.

Google Cloud Platform

Kubernetes EngineCompute EngineApp EngineCloud SQLMemory StoreCloud CDNVPC NetworkBigQueryVertex AIPub/Sub

Best fit for analytics-first workloads and organisations building on Kubernetes or Vertex AI.

A migration approach built
around what actually fails.

Most cloud migrations fail because of skipped discovery, missing dependencies, and no success criteria. Our four-phase methodology addresses each of these directly — and we stay through Phase 4, not just Phase 1.

PHASE 01

Preparation and planning

Define objectives, build the business case, align stakeholders, and establish the governance model. Nothing moves without a clear destination.

Objectives · business case
PHASE 02

Discovery, assessment, and proof of concept

Inventory every asset, map dependencies, assess workload complexity, and validate the architecture with a PoC before committing the full estate.

Assess · map · validate
PHASE 03

Design, migrate, and validate

Apply the 5R framework workload by workload. Migrate in waves. Validate against success criteria at each checkpoint before proceeding.

5R · data · hybrid
PHASE 04

Optimize

Post-migration we tune performance, right-size resources, set up observability, and hand over runbooks. We stay until operations are stable and costs are dialled in.

Optimize · we stay

The right strategy
for every workload.

Large workload portfolios contain applications at every stage of their lifecycle. Some should be rehosted, some refactored, some retired. Applying the wrong strategy to a workload is where migration costs balloon. We assess every workload individually before it moves.

R1

Rehost

Lift and shift

Move the workload to cloud infrastructure with minimal code changes. Fast, low-risk, best for stable applications on a deadline.

R2

Replatform

Lift, tinker, shift

Optimize for cloud during the move — swap the database engine, containerise, or adopt a managed runtime without refactoring app logic.

R3

Refactor

Redesign & re-architect

Re-architect for cloud-native benefits: microservices, serverless, event-driven. Higher upfront investment, highest long-term value.

R4

Retain

Keep on-premise

Some systems should stay. Compliance constraints, latency requirements, or end-of-life timelines may make migration the wrong call entirely.

R5

Retire

Decommission

If a workload has no active users or a duplicate already exists, retiring it reduces cost and maintenance overhead from day one.

Enterprise cloud work
we have shipped.

From a HIPAA-compliant IoT monitoring platform to an industrial sensor network spanning 80 countries — these are production systems built and running at scale.

Bedside monitoring that catches deterioration before it becomes critical

An FDA-cleared, HIPAA-compliant bedside system that detects early clinical deterioration in unmonitored patients. Heart rate, respiratory rate, SpO₂, and temperature captured via body sensor, surfaced to a nursing dashboard with criticality-based alerting — all on a HIPAA-compliant AWS cloud infrastructure.

Senzit — IoT fleet management platform deployed across 80+ countries

End-to-end cloud engineering for Mann+Hummel's industrial IoT monitoring platform — from sensor ingestion to fleet management dashboard. Built on AWS IoT Core and running at global scale across 80+ countries, tracking filter performance and maintenance intervals in real time.

Enterprise-wide cloud transformation across 100+ countries

Cloud integration architecture connecting Azure workloads with legacy SAP systems across Syngenta's global operations — incremental by design, no big-bang migration, operational in 100+ countries.

Intelligent IT service management

AIOps-powered IT service management platform on AWS that uses ML-based incident prediction to cut mean time to resolution, reduce L1 ticket volume, and power India's largest network end-to-end.

Omni-channel diagnostics platform at national scale

Rebuilt the patient engagement layer end to end on a hybrid Azure and AWS architecture — consumer app, phlebotomist app with route optimization, ML report-delivery prediction, and 100× throughput scaling from 2K to 30K+ daily orders.

More case studies →

Cloud-native,
built to last.

Our architecture covers the full stack — from client to server to managed cloud services. Every layer is designed to work together so performance, reliability, and cost stay coherent as the system scales.

Server technology

  • Apache · NGINX
  • Node.js · Python
  • Java · PHP
  • C# · JBoss
  • Linux · Windows Server

Databases

  • MySQL · PostgreSQL
  • MongoDB · Redis
  • Oracle · SQL Server
  • DynamoDB · Cosmos DB

Cloud managed services

  • API Gateway · App Service
  • Queueing & streaming · ML / AI services
  • IoT platform · Object storage
  • CDN · Serverless compute

Client

  • HTML5 / React · Android
  • iOS · Xamarin
  • React Native · Flutter
  • Progressive Web Apps

Infrastructure

Load balancerAPI gatewayContainersServerlessRDBMSCacheNoSQLGraph DBMobileDesktopIoT

What teams ask us
about cloud.

We are vendor-agnostic. We have certified practitioners across AWS, Azure, and Google Cloud, and we recommend based on your workloads, existing licenses, compliance requirements, and total cost — not on partnerships. Many of our clients run multi-cloud or hybrid environments and we manage both.
Security is baked into the migration design, not bolted on afterward. During advisory we review your current security posture, during migration we configure IAM, encryption at rest and in transit, network segmentation, and secrets management. After go-live, we run periodic vulnerability assessments and continuous compliance monitoring.
We start with a TCO analysis in the advisory phase so you know what cloud will actually cost before committing. During engineering we configure auto-scaling and rightsizing policies. Post-migration we set up FinOps dashboards and run quarterly cost reviews to flag idle or oversized resources before they inflate your bill.
Yes — and this is the norm, not the exception. Most enterprises cannot or should not move everything to the cloud. We design the integration layer that connects your cloud workloads with on-premise systems through APIs, event streaming, and data pipelines. The goal is a coherent architecture, not a forced full migration.
Cloud-native means building applications that take full advantage of cloud primitives: containerisation with Kubernetes, serverless functions for event-driven workloads, managed databases instead of self-managed VMs, and infrastructure-as-code so everything is reproducible. We design for elasticity and operational simplicity from the start.
Yes. Our monitoring and management practice handles infra operations post-migration — patching, scaling, alerting, incident response, and scheduled vulnerability assessments. Engagements are scoped to what you need: some clients hand off full operations, others keep their own team and use us for specialist overflow.

AI-native companies win.
Let's build yours.

Tell us what you are running today and where you need it to go. We come to the first call with questions, not a pitch deck.

Talk to our cloud team →