Cloud Application Development Services

Cloud Application Development Services | RaftLabs

See our work

  • Cloud-native architecture from sprint 1 -- not bolted on at the end

  • AWS, GCP, Azure -- whichever fits the project, not the one we know best

  • Serverless functions, containers, and managed services reduce your ops overhead

Recent outcomes

Voice AI · Research

Text-based interviews converted to automated phone calls

6× deeper insights

AI Automation · Ops

Manual invoice OCR across 40+ gas stations

20k+ txns day one

Loyalty · Retail

SuperValu & Centra loyalty platform with receipt validation

1,062 users in 4 weeks

SaaS · Logistics

Multi-carrier shipping hub for Indonesian eCommerce

2,000+ shipments yr 1
4.9 / 5 on ClutchSee all work

Recognition

Sound familiar?

  • Your app grew faster than your infrastructure and now every new feature requires a DevOps sprint to make it work?

  • You're paying for server capacity you don't need because no one set up auto-scaling from the start?

  • Your dev team is great at building features but keeps getting pulled into Kubernetes firefights?

In short

RaftLabs provides cloud application development services -- building SaaS products, APIs, and internal tools that are cloud-native from day one on AWS, GCP, or Azure. Most cloud app projects take 10--16 weeks. The studio handles architecture, backend, frontend, serverless functions, and CI/CD pipeline setup so clients don't need a dedicated DevOps hire.

Trusted by

Vodafone
Nike
Microsoft
Cisco
T-Mobile
Aldi
Heineken
GE

RaftLabs builds cloud-native applications on AWS, GCP, and Azure -- SaaS products, internal tools, and APIs that are designed for the cloud from the first architecture decision. Not applications that get lifted and shifted after launch.

Most cloud cost and scaling problems come from applications built for traditional servers and later moved to cloud infrastructure. The fix is architecture, not migration.

Capabilities

What we build

  • 01

    Serverless applications

    Functions on AWS Lambda, GCP Cloud Run, or Azure Functions for workloads that need to scale to zero and back without server management. Event-driven architectures, API backends, scheduled processing pipelines, and webhook consumers built on managed compute. You pay for what runs, not for servers that sit idle between requests.

  • 02

    Containerised applications

    Docker and Kubernetes on AWS ECS, GKE, or Azure AKS for applications that need consistent runtime environments and horizontal scaling. Container images built for reproducibility -- the same image that passes tests in CI is the one deployed to production. Auto-scaling configured from day one, not added when traffic spikes cause the first outage.

  • 03

    Cloud-native SaaS products

    SaaS products built with multi-tenant architecture, subscription billing, role-based access, and the cloud infrastructure decisions that hold at 10,000 users -- made at 10. Authentication, data isolation, managed queuing, and background job processing designed into the product from sprint 1.

  • 04

    API development and cloud integration

    REST and GraphQL APIs that connect your application to third-party cloud services -- Stripe, Twilio, SendGrid, AWS services, GCP services, and others. API gateways for rate limiting, authentication, and request routing. Webhooks for event-driven integrations between systems.

  • 05

    Cloud database setup

    Managed database selection and configuration based on your data model and access patterns. AWS RDS, Aurora, and DynamoDB. GCP Firestore, Cloud SQL, and BigQuery. Azure Database services. Backup schedules, read replicas, connection pooling, and query performance configuration included. You don't inherit a database that breaks at scale.

  • 06

    CI/CD pipeline and deployment automation

    GitHub Actions, AWS CodePipeline, or GCP Cloud Build configured for automated testing, staging deployment, and production releases. Infrastructure as code in Terraform or AWS CDK so your environment is reproducible and version-controlled. Monitoring and alerting via CloudWatch, Datadog, or GCP Monitoring set up before launch, not after the first incident.

  • 07

    Multi-region architecture

    Applications deployed across multiple regions or availability zones for workloads where downtime is expensive. Read replicas in closer regions to cut latency. Global load balancing. Disaster recovery configurations with documented RTO and RPO targets. Right-sized for your actual uptime requirements, not over-engineered for a theoretical scale you won't hit.

Process

How we build cloud-native applications

Five steps from blank slate to a deployed, monitored application running on your cloud account.

  1. Week 1
    01

    Architecture and cloud provider selection

    Before writing code, we decide the cloud provider, the core services, and the cost model. Which services fit the workload, what the infrastructure will cost at current and projected load, and which architectural decisions are cheap to change now but expensive to change after launch. We document this and get your sign-off before development starts.

  2. Week 1--2
    02

    Infrastructure as code setup

    Terraform or AWS CDK to define every resource -- compute, networking, storage, security groups, IAM roles, DNS -- in version-controlled code. Not click-ops. Your staging and production environments are created from the same codebase with environment-specific configuration. State managed in a remote backend. Your team inherits infrastructure they can modify, extend, and rebuild from scratch.

  3. Weeks 2--10
    03

    Application build in sprints

    Development in two-week sprints with cloud-first patterns throughout. Managed services where they cut operational overhead. Serverless where workload characteristics justify it. Every feature built against the staging environment, not a local machine. You see working software every two weeks, deployed to real cloud infrastructure.

  4. Week 10--12
    04

    Load testing and auto-scaling validation

    Before launch, we run load tests against your production configuration. We validate that auto-scaling triggers work correctly, that the database handles concurrent connections at peak load, and that the application recovers from dependency failures without cascading. No surprises on launch day.

  5. Week 12+
    05

    Deployment automation and monitoring setup

    Production deployment with monitoring, alerting, and log aggregation configured before the first real user hits the application. CloudWatch dashboards, Datadog monitors, or GCP Monitoring -- whichever fits the stack. Runbooks for the most common operational scenarios. Your team can run the application without depending on us.

Cloud infrastructure should be an advantage, not a tax on your engineering team.

Tell us what you're building and your current infrastructure situation. We'll scope the cloud architecture and give you a cost estimate before development starts.

Talk about your cloud project

Related services

What clients say

What clients say about working with us

Three-year average engagement. Founders and operators describing the work in their own words. No marketing varnish.

Niccolo Pescetelli
Niccolo Pescetelli
Co-founder & Director, PSi

Working with RaftLabs felt like having an extension of our own team. They're extremely nimble and responsive, adapting quickly to changing startup needs. I highly recommend them, especially for small and mid-sized companies.

01 / 14

Recent work

Projects that started like yours

Multi-carrier shipping SaaS: 2,000+ shipments across 70+ countries in year one

We developed a multi-carrier shipping SaaS solution in Indonesia, helping fast-growing eCommerce businesses ship globally with ease. Integrated with Shopify, it offers instant Aramex, FedEx, DHL, and UPS rate comparisons, automated fulfilment, and end-to-end shipment management.

Read case study
Multi Carrier Shipping Software
AI Phone Agent To Conduct Voice Interviews at Scale

AI phone agents conducting automated voice interviews at global scale

We rebuilt a text-based AI interview platform as a voice-first system that conducts automated phone interviews globally, removing user friction and surfacing richer insights through natural conversations.

Read case study
Gas Station Management Software Case Study

AI-powered OCR scaling gas station operations to 20k+ daily transactions

This purpose-built gas station inventory management software uses AI-based OCR to automate invoice processing and unify inventory, sales, and vendor tracking. Designed for scale, it gives owners real-time control across 40+ locations, without disrupting existing POS systems.

Read case study
AI OCR Loyalty Platform for SuperValu and Centra
Loyalty · Retail

SuperValu and Centra needed a loyalty platform. We shipped one that acquired 1,000+ users in 4 weeks.

We built an AI-powered loyalty platform for Musgrave's SuperValu and Centra that automates receipt validation with 99.9% accuracy, acquiring 1,062 users in 4 weeks.

Read case study
See all projects

Frequently asked questions

A focused cloud-native application -- one core workflow, a backend API, and a web or mobile frontend -- typically runs $25,000--$60,000. A more complete product with multiple modules, third-party integrations, and a data layer runs $60,000--$120,000. Projects with real-time features, multi-region requirements, or strict compliance posture (HIPAA, SOC 2) run higher. All engagements are fixed cost based on scoped features. You know the number before development starts.

AWS is the default for most projects -- it has the broadest service selection, the largest partner network, and the most available talent. GCP is the right call when your workload is data-heavy or ML-centric -- BigQuery, Vertex AI, and Dataflow are significantly stronger than the AWS equivalents. Azure makes sense when your organisation is already deep in the Microsoft stack -- Active Directory, MSSQL, and Office 365 integrations are tighter on Azure. We recommend based on your workload profile and existing tooling, not our default preference.

Cloud migration moves an existing workload -- servers, databases, applications -- from on-premises or a legacy host to the cloud. Cloud application development builds something new with cloud infrastructure as the target from day one. Migration is about moving what exists. Cloud-native development is about building for the cloud from the first commit. If you have an existing server-based application you want to move, see our cloud migration service. If you're building something new and want it to run on cloud infrastructure, that's this.

Yes. Every cloud application we build ships with a CI/CD pipeline and deployment automation. We set up GitHub Actions or AWS CodePipeline for automated testing and deployment, staging and production environments separated at the infrastructure level, monitoring and alerting via CloudWatch, Datadog, or GCP Monitoring, and infrastructure as code (Terraform or CDK) so your environment is version-controlled and reproducible. You don't need a dedicated DevOps engineer to run what we build.

Yes, but it costs more. Applications built on traditional server architecture require re-architecting to take advantage of cloud services. Auto-scaling, managed databases, serverless functions -- these aren't things you bolt on later without touching the application code. Starting cloud-native means those decisions are made during architecture, not after launch. If you already have a server-based application and want to migrate it, see our cloud migration service. The earlier you design for cloud, the less that migration will cost.

Work with us

Tell us what you need. We'll tell you what it would take.

We scope Cloud Application Development Services | RaftLabs in 30 minutes. You walk away with a clear cost, timeline, and approach. No commitment required.

  • Scope and cost agreed before work starts. No surprises. No obligation.
  • Working prototype within 3 weeks of kickoff.
  • Pay by milestone. You see progress before each invoice.
  • 60-day post-launch warranty. Bug fixes, UI tweaks, and deployment support. No retainer.
  • All conversations are NDA-protected.