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Cloud Migration Services
End-to-end migration of workloads to AWS, Azure and Google Cloud assessment, strategy, landing zone build and phased cutover delivered by senior cloud engineers.
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AI-Era Ready AWS Cloud Services
We are a US-based AWS Cloud Services company helping startups, scale-ups and enterprises architect, migrate, modernize and operate workloads on Amazon Web Services. Senior AWS-certified engineers who treat the Well-Architected Framework as the floor, not the ceiling, and who have operated production AWS environments through real incidents, real audits and real CFO conversations about the bill.
13+
Years of Experience
50+
Experts in Our Team
40+
Happy Customers Worldwide
250+
Projects Delivered Successfully
4.9/5 ratings
5/5 ratings
Every Layer of AWS, Engineered as a Single Practice
Whether you are migrating a legacy workload off an aging data center, re-architecting a monolith for cloud-native scale, or layering AWS AI Services onto a production environment that already runs on Amazon Web Services, our AWS Cloud Development Services cover every layer of what production on AWS actually demands. Architecture, migration, DevOps, security, cost governance, AI workload operations and managed operations delivered by senior engineers who know which AWS service earns its keep for your workload and which one just looks good in the slide deck.
AWS Architecture & Well-Architected Reviews
Most AWS environments accumulate architecture decisions made under time pressure, by engineers who have since moved on, against requirements that changed three times since launch. We run Well-Architected Reviews as a genuine engineering assessment across all six pillars, not a checkbox exercise. Every finding is prioritized by actual risk, and the remediation roadmap sequences by impact. New greenfield architectures get designed from first principles. Existing environments get reviewed, hardened and documented to the standard AWS intended when they wrote the framework.
AWS Cloud Migration Services
Migrations fail in the planning stage, not the execution stage. Before we move a single workload, we run a dependency-mapped assessment covering application interdependencies, data gravity, license entanglements and the real cost-to-serve number nobody has written down honestly. We execute in phased waves using AWS Migration Hub, Application Migration Service and Database Migration Service, with the right strategy per workload: rehost where it makes sense, refactor where it pays back. Zero-downtime cutover patterns, data integrity validated at every checkpoint and rollback plans that have actually been tested.
AWS Application Development
AWS gives you more ways to build than any other cloud platform. That is its strength and its trap. We build AWS-native applications using EC2 and ECS where persistent compute fits, Lambda and API Gateway where serverless earns its keep, EKS for container orchestration at scale and Step Functions for workflows that need to be auditable, retryable and fully observable. The application requirement always drives the service selection. We pick what fits the workload, not what the last client happened to use.
AWS Security & Compliance Services
Security on AWS is a shared responsibility and most incidents happen on the customer side of that line. We run AWS security as a continuous operational discipline: IAM governance with least-privilege enforcement, Security Hub for consolidated posture management, GuardDuty for threat detection, Macie for sensitive data discovery, Inspector for vulnerability management and Config for compliance drift detection. SOC 2, HIPAA, PCI-DSS and ISO 27001 controls are operated as a continuous posture, with evidence collected automatically as part of the daily work.
AWS Cost Optimization & FinOps
The AWS bill does not quietly improve without a deliberate FinOps practice behind it. We build cost governance into every AWS environment from day one: tagged resources, budgeted accounts with anomaly alerting, Compute Optimizer recommendations acted on, and reserved instance and savings plan analysis run on a defined cadence. Cost Explorer gets used as an operational tool, not a monthly postmortem. Most clients see 25 to 40 percent reduction in their underlying AWS spend within the first six months, not from cutting capacity but from cutting the waste that accumulated while nobody was paying attention.
AWS AI Services & Generative AI Development
Amazon Bedrock, SageMaker, Rekognition, Textract, Comprehend and the full suite of AWS AI Services are the building blocks of production AI systems that run at real scale. We design and build AWS Generative AI Solutions using Bedrock for foundation model access, Knowledge Bases for RAG architectures and SageMaker for custom model training and inference. The production disciplines come with it: token-level cost monitoring, prompt versioning, model evaluation pipelines and inference observability. AI features that ship to production users, not just to the demo environment.
AI-Native AWS Engineering, Not AWS With AI Bolted On
Most AWS shops treat AI as something you add to an existing environment after the architecture is set. We treat it as a first-class decision from the start. Every layer below uses AWS AI Services, automation and AI-assisted engineering to build AWS Cloud AI Solutions that predict, prevent and right-size before the problem surfaces in your incident channel.
01
Foundation models in production, not in notebooks
We build Generative AI solutions on Amazon Bedrock with the production discipline AI workloads actually demand: RAG architectures using Bedrock Knowledge Bases and Amazon Kendra, agentic workflows through Bedrock Agents, multi-model routing for cost and latency optimization and the evaluation harnesses that catch output quality regressions before your users do.
Highlights:
- Bedrock multi-model orchestration
- RAG pipeline engineering
- Agentic workflow development
01
Foundation models in production, not in notebooks
We build Generative AI solutions on Amazon Bedrock with the production discipline AI workloads actually demand: RAG architectures using Bedrock Knowledge Bases and Amazon Kendra, agentic workflows through Bedrock Agents, multi-model routing for cost and latency optimization and the evaluation harnesses that catch output quality regressions before your users do.
Highlights:
- Bedrock multi-model orchestration
- RAG pipeline engineering
- Agentic workflow development
AWS Capabilities We Deliver, Layer by Layer
AWS Cloud Services is not one capability. It is a category spanning compute, storage, networking, databases, security, AI and the operational layer that keeps everything running at 3 a.m. on a holiday weekend. Here are the AWS capabilities we deliver and the engineering bar we hold ourselves to on each one.
Compute & Serverless
EC2 instances right-sized for your actual workload profile, not the demo benchmark. Fargate for containerized workloads where you want managed compute without managing nodes. Lambda where stateless, event-driven execution earns its keep and not where it creates the cold start latency your users will notice. Auto-scaling policies written against your real traffic patterns, not the default CloudWatch thresholds that alert too late.
Containers & Kubernetes on AWS
EKS clusters designed for multi-tenant workloads with namespace isolation, RBAC that holds up under a security review and network policies that mean something. ECS for teams who want managed container orchestration without the operational overhead of Kubernetes. ECR for image management with lifecycle policies that keep your registry clean and your pull times predictable. Helm, Kustomize and GitOps through Argo CD or Flux baked in from day one.
AWS Data Platform & Analytics
Redshift clusters sized for your query patterns, not the largest node in the documentation. Athena for ad-hoc analysis against S3 data lakes without provisioning infrastructure. Glue for ETL pipelines that stay maintainable past the first sprint. Kinesis for streaming data that needs to be processed in real time, not in last night's batch job. Lake Formation for the governance layer that keeps your data lake from becoming a data swamp
AWS Networking & Connectivity
VPC architecture with subnetting designed for your compliance scope, not copied from the getting-started guide. Transit Gateways for multi-account connectivity without the peering mesh that becomes unmanageable at scale. Direct Connect for hybrid workloads where latency and throughput make the public internet the wrong choice. Route 53 for DNS management, CloudFront for content delivery and WAF for the layer-7 protection your public endpoints need.
AWS Storage & Databases
S3 with lifecycle policies that move data to the right storage tier automatically and delete it when it stops earning its keep. RDS and Aurora tuned for your actual query patterns, with read replicas where they pay back and Multi-AZ where your RPO actually demands it. DynamoDB for workloads that need millisecond reads at any scale, with capacity planning and access pattern design that prevents the hot partition issues that only surface in production.
AWS Identity & Governance
IAM governance with least-privilege policies that survive a real access review, AWS IAM Identity Center for federated identity across accounts, Service Control Policies enforced at the organization level and the joiner-mover-leaver automation that keeps your access model current without depending on a manual process that someone skips on a busy week.
AWS DevOps & Automation
CodePipeline, CodeBuild and CodeDeploy for AWS-native CI/CD. GitHub Actions and GitLab CI where they fit the team better. Terraform and AWS CDK for infrastructure as code that stays readable past the hundredth resource. Systems Manager for operational automation, patch management and the configuration compliance that your auditor is going to ask about.
AWS AI & Machine Learning Services
Bedrock for foundation model access with the governance controls enterprise deployments require. SageMaker for custom model development, training and inference. Rekognition, Textract, Comprehend, Polly and Lex for the purpose-built AI services that get most projects 80 percent of the way there faster than a custom model. Kendra and OpenSearch for enterprise search that understands intent, not just keywords.
The AWS Cloud Consulting Partner Worth Hiring
We are not just another AWS Cloud Solutions Provider with a logo wall of certifications. We are the AI-first AWS engineering partner you bring in when uptime, cost discipline and audit-readiness are not acceptable to leave unsolved, and when you need engineers who know AWS well enough to push back when a service does not actually fit your workload.
AWS AI Services as a First-Class Practice
Amazon Bedrock, SageMaker, AWS Generative AI Solutions and LLMOps are wired into how we architect and operate AWS environments. Not added as a talking point. We operate AI workloads in production on AWS and treat the AI layer as a first-class engineering surface.
Senior AWS Engineers, No Bench Warmers
You get AWS-certified architects and senior engineers who have operated production environments through real incidents, real compliance audits and real conversations with CFOs about a $400,000 monthly bill. Not juniors learning IAM policies on your downtime.
Well-Architected, Not Just AWS-Deployed
Every AWS engagement starts from the six pillars: operational excellence, security, reliability, performance efficiency, cost optimization and sustainability. We treat the Well-Architected Framework as an engineering baseline, not a marketing claim.
FinOps Built Into Every AWS Engagement
Tagged resources, budgeted accounts, anomaly detection, right-sizing reviews and savings plan analysis are operated as a continuous practice, not a quarterly cleanup. GPU spend included. The savings show up in invoices, not slide decks.
Security, Compliance & Transparent Delivery
SOC 2, HIPAA, PCI-DSS, ISO 27001 and GDPR controls operated as a continuous posture with evidence collected automatically as part of the work. Clear SLAs, honest status reporting, no surprise AWS infrastructure bills.
Built for the AI-Era AWS Stack
We architect for Bedrock, SageMaker, serverless, EKS and the AWS services shaping the next five years of cloud-native engineering. Not just the architecture that was current when your last AWS partner was hired.
Our AWS Cloud Services Delivery Process
Most AWS engagements do not fail technically. They fail because the assessment never established the real cost-to-serve baseline, the architecture was designed for the whiteboard demo rather than the production workload, or the handover left the in-house team operating an environment they do not fully understand. Our AWS Cloud Consulting Services follow a structured, AI-assisted delivery methodology designed to surface those problems early.
Here is exactly how it works.
01
Discovery & AWS Assessment
We audit your existing infrastructure, workload portfolio, AWS account structure, cost posture, security configuration and compliance status. The deliverable is an honest picture of what is actually running, what it actually costs and where the highest-risk findings are.
02
Architecture & Strategy
We design the target AWS architecture and migration strategy with the trade-offs documented honestly. Service selections justified by workload requirements. FinOps and security controls designed in from the start.
03
Proof of Concept & Landing Zone
We validate critical assumptions on a contained workload and stand up the AWS landing zone: multi-account structure through AWS Control Tower, identity and access baseline, network topology, observability stack and FinOps tagging before committing to full rollout.
04
Build, Migration & Deployment
Our engineers execute builds and migrations in phased waves with zero-downtime patterns, data integrity checks at every checkpoint and rollback procedures that have actually been tested against production-like conditions.
05
Optimization & Hardening
We tune the AWS environment for cost, performance and security, and harden the compliance posture to the standard your industry actually requires, not the generic CIS benchmark nobody ever fully implements.
06
Managed Operations & Continuous Improvement
We provide continuous 24/7 monitoring, FinOps oversight, security posture management, incident response and quarterly architecture reviews as an ongoing operational practice. Or we hand the environment over cleanly to your in-house team with the documentation and training to operate it confidently.
Flexible Engagement Models to Hire Our AWS Cloud Consulting Team
Your AWS engagement does not fit a template and the contract should not either. The right way to hire AWS Cloud Consulting expertise depends on your scope, your timeline and your in-house operational maturity. Three models, all built for cloud-era delivery speeds.
You need AWS engineers who know your environment as well as your in-house team, building for your roadmap and not splitting attention across five other clients. The Dedicated Team model gives you a fully embedded AWS unit working exclusively on your architecture, your tooling and your business outcomes.
- Right for you if
You are running a complex AWS transformation over six months or more, managing a large multi-account estate, scaling AI workload operations or augmenting your in-house cloud team without the cost and lead time of full-time hires.
- What you get
Hand-picked AWS architects, cloud engineers, SREs and security specialists working only on your environment. Sprint planning, on-call rotations and incident response run on your calendar and your tooling. AI-assisted engineering is built into how the team ships, not bolted on later.
- Economics
Monthly retainer. No surprise invoices, no scope-creep billing. Team composition flexes as your AWS roadmap progresses
Typical profile
3 to 10 engineers
6-month minimum
Scales with 30-day notice
Not sure which model fits your Strapi project?
Most mid-market companies start with one and evolve int
Ready to Build on AWS the Right Way?
Building AWS Cloud Foundations for the Businesses That Will Define the Next Decade. The companies investing in well-architected AWS environments now, with AI services designed in and FinOps operated as a practice rather than a quarterly cleanup, will not be the ones re-platforming, explaining cost overruns or reconstructing audit evidence two years from now.
Industries We Deliver AWS Cloud Services For
AWS engineering looks different across industries. The compliance posture, the uptime tolerance, the data residency constraints and the AI workload requirements all change what a well-architected AWS environment actually looks like. These are the verticals where we operate production AWS environments and know what the work really involves.
HIPAA-compliant AWS architectures with PHI-segmented VPCs, Macie for sensitive data discovery, CloudTrail audit logging that holds up under OCR review, change management evidence collected automatically and the reliability discipline that telehealth, EHR-integrated and clinical workflow applications demand. We have deployed healthcare workloads on AWS in production. We know what HIPAA compliance looks like in a live environment, not just in the AWS HIPAA whitepaper.
Explore MoreHIPAA-compliant AWS architectures with PHI-segmented VPCs, Macie for sensitive data discovery, CloudTrail audit logging that holds up under OCR review, change management evidence collected automatically and the reliability discipline that telehealth, EHR-integrated and clinical workflow applications demand. We have deployed healthcare workloads on AWS in production. We know what HIPAA compliance looks like in a live environment, not just in the AWS HIPAA whitepaper.
Explore MoreFrequently Asked Questions
Honest answers to the questions every CTO, head of infrastructure and head of engineering asks before they hire an AWS Cloud Consulting partner. If something is not covered here, our solution architects will walk you through it on a discovery call. No sales pitch, no fluff.
Look beyond the AWS Partner tier and the certification count. The right AWS Cloud Solutions Provider asks more questions than it answers in the first conversation about your workload architecture, your incident history, your cost trajectory and what an outage actually costs your business. Evaluate engineering depth in the discovery phase, transparency about trade-offs between AWS services, honest FinOps thinking rather than vendor advocacy for the most expensive compute tier and whether they push back constructively when a simpler service fits better. Anyone who recommends specific AWS services before they have understood your workload is not the right partner.
End-to-end AWS Cloud Development Services cover architecture and Well-Architected reviews, cloud migration assessment and execution, application development on AWS services, DevOps and CI/CD pipeline engineering, data platform and analytics, security and compliance management, cost optimization and FinOps, managed operations and 24/7 monitoring, AI and generative AI development on Bedrock and SageMaker, and quarterly architecture reviews. The best engagements also include a genuine assessment before any architecture decisions are locked in because the choices made in week one shape your AWS bill for years.
A focused AWS engagement, a migration assessment, a security hardening sprint or a specific workload build: $15,000 to $75,000. A mid-complexity AWS transformation with application migration, DevOps setup and compliance hardening: $100,000 to $400,000. An enterprise AWS program covering multi-account architecture, AI workload operations and ongoing managed services: $400,000 to $1.5M or more. The number that matters is not the engagement cost. It is the total cost of ownership on AWS three years out, which is where good architecture pays back and bad architecture quietly compounds. We provide detailed estimates after an assessment. We do not give a number before we can stand behind it.
FinOps is operated as a continuous practice built into the AWS environment from day one, not reviewed at the end of the quarter when the bill has already landed. Tagged resources, budgeted accounts with anomaly detection through AWS Budgets and Cost Anomaly Detection, Compute Optimizer recommendations acted on and not just acknowledged, reserved instance and savings plan analysis on a defined cadence and Cost Explorer used as an operational tool. Most clients see 25 to 40 percent reduction in their underlying AWS spend within the first six months. Not from cutting capacity. From cutting the waste the original architecture quietly accumulated.
AWS security is a daily operational practice, not a quarterly review. Continuous posture management through Security Hub, threat detection through GuardDuty, sensitive data discovery through Macie, vulnerability assessment through Inspector, configuration compliance through Config and network protection through WAF and Shield. IAM governance with least-privilege policies, Secrets Manager for credentials, and compliance controls for HIPAA, PCI-DSS, SOC 2, ISO 27001 and GDPR operated as a continuous posture with evidence collected automatically. When your auditor arrives, the evidence pack is already assembled.
The full suite. Amazon Bedrock for foundation model access including Claude, Llama, Titan and Mistral, with Knowledge Bases for RAG architectures and Agents for agentic workflows. SageMaker for custom model development, training pipelines, model registries and managed inference endpoints. Rekognition for computer vision, Textract for document extraction, Comprehend for NLP, Polly for text-to-speech, Lex for conversational interfaces, Kendra for enterprise search and Personalize for recommendation systems. We operate these as production-grade AWS AI Development Services with the monitoring, cost governance and evaluation discipline that production AI actually demands.
AWS Generative AI Solutions built on Amazon Bedrock give you access to foundation models from Anthropic, Meta, Mistral, Amazon and others through a single managed API, with enterprise-grade security controls, private model customization through fine-tuning and continued pre-training, and the governance layer that regulated industries require. Whether you need it depends on your roadmap. If AI-powered features are on your product or operational roadmap within the next twelve months, designing your AWS architecture with Bedrock as a first-class component from the start is significantly cheaper than retrofitting it later. The AWS Cloud AI Solutions worth building now are the ones that do not need rebuilding when the next model generation ships.
Three models: Dedicated AWS Team for long-term, evolving AWS programs, Time and Material for iterative modernization and exploratory builds and Fixed Cost for well-scoped, budget-defined AWS projects. When you engage us as your AWS Cloud Consulting partner, we recommend the model honestly based on your situation, not based on which one is most profitable for us.
Yes, that is most of what we do. We start with a takeover assessment covering architecture, cost posture, security configuration, IAM hygiene, operational practices and accumulated drift. You get an honest picture of what you have inherited from a previous AWS partner or an in-house team that has since moved on, and a clear remediation roadmap. The takeover is phased: monitoring and observability first, then runbooks, then on-call handover, then optimization.
A single workload migration to AWS: 4 to 8 weeks. A mid-complexity migration with application refactoring, data migration and DevOps setup: 3 to 6 months. A full enterprise data center exit to AWS across multiple business units: 9 to 18 months, executed in waves. We provide milestone-based timelines in writing before migration begins and we plan cutover windows your business can actually operate within.
A Time and Material or Dedicated Team engagement can typically begin within 1 to 2 weeks of contract signature, starting with the discovery and assessment phase. Fixed Cost engagements begin with a 2 to 4 week scoping phase before the build starts. We will tell you the honest timeline at the start, not the optimistic one we cannot deliver.
Yes. Many of our clients run AWS as their primary cloud with Azure or Google Cloud for specific workloads, regulatory reasons or because an acquisition brought a different cloud estate with it. We design and operate multi-cloud architectures that use AWS where it earns its keep and acknowledges its limits honestly. Multi-cloud adds real operational overhead. We help you decide when that trade-off is worth making and operate the result when it is.
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Insights on AWS Cloud Services
Curated insights, comparisons and best practices on AWS architecture, FinOps, Well-Architected reviews, Bedrock and generative AI on AWS, security and the operational disciplines that separate well-run AWS environments from the ones that generate surprise bills and 2 a.m. pages.
