Most enterprises running on AWS are operating at a fraction of what their investment can deliver. Environments that were built for speed grow into cost, security, and architecture debt. AI initiatives stall because the data foundation underneath them was never designed to support production-grade workloads. Migrations complete but modernization never follows.
Futran Solutions is an AWS Advanced Tier Services Partner and AWS Managed Service Provider. We help organizations across financial services, insurance, healthcare, and other regulated and high-growth sectors build AWS environments that are secure, cost-governed, and ready for the AI workloads that matter to their business.
Our AWS practice covers the full lifecycle of enterprise cloud delivery. Each service line below links to a dedicated page with detailed scope, engagement models, and client outcomes.
Most organizations approach cloud migration as a lift-and-shift exercise. The infrastructure moves, but the cost, complexity, and technical debt move with it. We approach migration differently. Before any workload moves, we assess its architecture, its cost profile, and its suitability for cloud-native redesign. The result is an AWS environment that performs better than what you left behind, not just a copy of it in a different data centre.
We migrate on-premises infrastructure, legacy applications, and data platforms using a structured wave methodology designed to eliminate downtime for business-critical systems. Our work spans simple server migrations and complex multi-account, multi-region enterprise transitions.
Data is the raw material for every AI workload your organization wants to run. It is also the area where most AWS environments are least prepared. Fragmented storage, inconsistent data quality, and architectures that were designed for reporting rather than machine learning are the most common reasons AI initiatives stall before they reach production.
We build AWS data platforms using Redshift, Glue, Lake Formation, S3, and Databricks on AWS that give organizations a governed, scalable foundation for analytics and AI. Our data engineering work is built around your actual data assets and your actual business questions, not a generic reference architecture.
Operating an AWS environment at an enterprise scale requires continuous vigilance: cost management, security posture, patching, capacity planning, incident response, and architecture evolution as your workloads change. Most internal IT teams do not have the AWS-specific depth to do all of this at the standard an AWS MSP operates to.
As an AWS Managed Service Provider, we operate your AWS environment to a formally validated standard. Our managed services practice provides 24×7 monitoring, defined SLAs, monthly cost reviews, proactive security posture management, and a named team with full context of your environment and your business priorities.
The speed at which your development teams can deploy software safely is a direct competitive differentiator. Long deployment cycles, inconsistent environments, and manual release processes create risk and slow the pace of product delivery. We implement AWS DevOps environments that bring your deployment frequency up and your release risk down.
Our DevOps work covers CI/CD pipeline design using CodePipeline, CodeBuild, and GitHub Actions, infrastructure as code using Terraform and CloudFormation, container orchestration using ECS and EKS, and GitOps practices that give your platform team consistent, auditable control over your AWS environment.
Security on AWS is not a product you purchase. It is a set of architectural decisions, operational practices, and governance controls that must be built into your environment from the start. Organizations that treat security as an afterthought spend more to fix it later and carry ongoing risk in the interim.
We implement AWS security architectures aligned with the AWS Well-Architected Framework security pillar, CIS AWS Benchmarks, and the compliance requirements of the industries we serve. Our security work covers identity and access management, network architecture, encryption, logging and monitoring, threat detection using GuardDuty and Security Hub, and automated compliance remediation using AWS Config and AWS Security Hub.
AWS environments drift over time. What was a well-designed architecture two years ago may now carry cost inefficiency, security gaps, or reliability risks that were introduced incrementally. A formal AWS Well-Architected Review identifies exactly where your environment stands against the six pillars of operational excellence, security, reliability, performance efficiency, and cost optimization.
As an AWS Well-Architected Partner, we conduct formal Well-Architected Reviews and deliver prioritized remediation roadmaps with clear business impact estimates. Organizations that complete a Well-Architected Review with us typically reduce their cloud cost by 20 to 35 percent in the first 90 days of remediation.
Infrastructure management consumes engineering capacity that your teams could be using to build product. AWS Lambda, API Gateway, Step Functions, EventBridge, and the broader serverless ecosystem allow organizations to run sophisticated workloads without the operational overhead of managing servers. We design and build serverless architectures that are event-driven, cost-efficient, and observable at production scale.
AWS provides the most comprehensive AI infrastructure available in enterprise cloud today, from foundation models through Bedrock to custom machine learning through SageMaker, document intelligence through Textract, and conversational AI through Lex. We help organizations design AI workloads that are connected to real enterprise data, governed for production deployment, and built to scale beyond a pilot.
Our AWS AI Competency designation reflects validated delivery capability across these services. We have built production AI systems for insurance claims automation, financial document intelligence, healthcare data processing, and AI-assisted operations across multiple sectors.
Credentials in the AWS partner ecosystem are not simply awarded. They require validated delivery capability, certified personnel, and demonstrated client outcomes reviewed by AWS. Here is what each of our designations means for an organization evaluating an AWS partner.
Fewer than 150 firms globally hold AWS MSP status. It is the highest validated designation for AWS operations, requiring formal assessment of delivery processes, tooling, security practices, and client outcome evidence. When you engage an AWS MSP, you are working with a firm whose operating model has been independently reviewed by AWS.
Advanced Tier status reflects sustained delivery performance across AWS client engagements. It requires a minimum number of certified practitioners, verified revenue threshold, and client satisfaction scores reviewed by AWS. It is the tier that separates firms with proven delivery track records from those that are simply registered.
This competency is awarded to partners who have demonstrated production-grade delivery of AI workloads on AWS, including validated case studies reviewed by AWS. It means our team has built real AI systems for real clients using SageMaker, Bedrock, and related services, not just theoretical knowledge of these platforms.
Membership in this program authorizes Futran to conduct formal AWS Well-Architected Reviews, the structured assessment process AWS uses to evaluate cloud environment quality across five pillars. This is the mechanism through which we deliver our free AWS Environment Assessment.
This competency validates delivery capability for small and medium business workloads on AWS, where the architecture and cost optimization requirements differ significantly from large enterprise environments. It expands the range of organizations Futran can serve effectively on AWS.
These service-specific designations reflect validated delivery volume and quality across individual AWS services. Each one represents a pattern of successful client delivery in that specific area, not just certification. Collectively they confirm the breadth of hands-on AWS expertise our teams carry.
Free AWS Environment Assessment
We assess your current AWS environment against cost efficiency, security posture, AI readiness, and Well-Architected principles. Two weeks. No obligation. Delivered as a prioritized business-impact roadmap for your leadership team.
PRISM — ‘Platform Readiness and Intelligence Scoring Method’ by Futran Solutions
Futran holds AWS MSP status, AWS AI Services Competency, and Advanced Tier Services Partner designation. These are not marketing badges. Each required documented delivery evidence reviewed by AWS. When you evaluate us against other AWS partners, ask them how many hold all three. The answer will be a short list.
Organizations that come to us after a failed AI initiative almost always have the same diagnosis: the AWS environment was not designed for AI workloads. Data is fragmented. Governance is incomplete. Security controls were not built for model training or inference at scale. We build AWS environments with AI readiness as a first-order design requirement, not a retrofit. This is reflected in the 50-plus production AI workloads our teams have deployed on AWS.
AWS environments without cost governance grow unpredictably. The average organization running AWS without structured FinOps practices overspends by 30 to 40 percent relative to their optimized baseline. We embed cost governance, tagging standards, Reserved Instance planning, and monthly cost reviews into every managed services engagement. The 35 percent average cost reduction our clients see is not a projection. It is a measured outcome from the environments we have operated and optimized.
We have deep delivery experience in financial services, insurance, and healthcare. These are sectors where AWS architecture decisions carry compliance, regulatory, and data sovereignty implications that generalist cloud partners often do not understand until they encounter them in a live engagement. Our teams know the Duck Creek data model, the HIPAA workload requirements, the SOC 2 audit trail expectations, and the financial services security frameworks that govern work in these industries. We also bring this architectural discipline to engagements in manufacturing, retail, energy, and technology sectors where clients require the same rigor without the specific regulatory overlay.
Our AI Delivery Hub gives us the engineering depth to staff and sustain complex, multi-workload AWS programs without the capacity constraints that smaller AWS partners encounter. When an engagement grows, we scale with it. When AI workloads require specialized practitioners in SageMaker, Bedrock, or custom ML, we have them available without a lengthy recruitment cycle.
AWS is rarely the only technology environment an enterprise runs. Organizations with a Microsoft estate, Salesforce, ServiceNow, Databricks, or Snowflake alongside their AWS infrastructure benefit from a partner who can work across those boundaries. Our practice spans AWS, Microsoft Azure, and the major data and application platforms that enterprise AWS environments connect to. We design integrations that work rather than creating handoff problems between different specialist teams.
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We begin with a structured assessment of the current environment, covering workload inventory, cost profile, security posture, and AI readiness. For each workload, we evaluate whether the right path is lift-and-shift, refactor, re-platform, or retire. The output is a sequenced modernization roadmap with business impact estimates for each phase. We do not treat modernization as a single event. For most organizations, it is a 12 to 24 month program of continuous improvement, and we operate the environment throughout that period as an AWS MSP.
Yes. We regularly step into AI programs that have stalled or are not reaching production. The most common causes are data architecture that was not designed for AI workloads, governance gaps that create compliance risk when models are deployed at scale, and an underestimation of the MLOps work required to keep a model performing after initial deployment. We assess the current state, identify the specific blocking issues, and build a path to production. Our AWS AI Services Competency reflects the breadth of delivery experience we bring to this work.
Cost governance on AWS is an architecture discipline, not a cost-cutting exercise. We apply structured FinOps practices from the first day of an engagement: tagging standards, budget alerts, Reserved Instance and Savings Plan planning, and rightsizing recommendations based on actual utilization data. For managed services clients, we conduct formal monthly cost reviews and identify optimization opportunities proactively. Clients who move from an unmanaged or lightly managed AWS environment to our MSP model typically see 30 to 35 percent cost reduction in the first 90 days without any reduction in performance or availability.
Our security architecture work is aligned with the AWS Well-Architected Framework security pillar, CIS AWS Benchmarks Level 2, and the specific compliance requirements of each sector we serve. For financial services clients, this includes SOC 2 alignment, PCI DSS where applicable, and financial services regulatory frameworks relevant to their jurisdiction. For healthcare clients, HIPAA technical safeguards are implemented as standard. For insurance clients, we apply the same rigor with specific attention to data residency and the audit trail requirements of claims and underwriting environments. For clients outside regulated sectors, we apply the AWS security baseline as a standard starting point and adjust based on their specific risk profile.
We agree on success metrics before any engagement begins, not after. The metrics that matter most to our clients fall into four categories: cost efficiency measured against a pre-engagement baseline, reliability measured as availability and mean time to recovery, deployment velocity measured as frequency and lead time for changes, and AI readiness measured as the number of AI workloads that reach production within the engagement period. We report against these metrics monthly and adjust our work if any metric is tracking below target. This is what being an AWS MSP means in practice: accountable delivery against defined outcomes, not best-effort support.
AWS is our primary and most credentialed cloud practice. For organizations that run workloads across both AWS and Azure, or that have AWS infrastructure connected to Microsoft 365, Dynamics 365, or other Microsoft services, we bring a single delivery team that understands both environments. We do not design AWS and Azure in isolation and then attempt to bridge them after the fact. The integration architecture is designed from the start. This is increasingly important as organizations deploy AI workloads that span cloud providers and require governed data movement between them.
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Futran Solutions is an Equal Opportunity Employer
We do not discriminate based on race, color, religion, sex, national origin, age, disability, veteran status, or any other legally protected status.
