Caylent, an AWS Premier Tier AWS Partner and leader in cloud modernization and AI-driven delivery, announced the launch of Caylent Accelerate for Cloud Migration, a new approach for helping customers migrate to Amazon Web Services (AWS). Purpose-built for migrations from VMware, Google Cloud Platform, and Microsoft Azure to AWS, the new offering combines AI-powered delivery, an output-based model, and built-in resiliency and cost optimization to deliver immediate customer value while achieving up to a 40% reduction in migration timelines.
A Modernized Migration Experience
Caylent Accelerate for Cloud Migration shifts migration from a technical task to a business result by combining automation, proven methodology, and AI:
- AI-Powered Delivery: Dependency mapping, code conversion, and migration planning powered by AI reduce risk and migration timelines by up to 50%.
- Output-Based Model: Customers pay only for workloads that are successfully migrated to and validated in AWS, not time spent.
- Resiliency by Default: Every migration includes a disaster recovery strategy aligned to customer RPO/RTO requirements.
- Cost Optimization Built In: A post-migration cost baseline, rightsizing recommendations, and strategies for taking advantage of AWS Savings Plans are delivered at no extra cost, ensuring immediate ROI.
From assessment through to validation, Caylent Accelerate for Cloud Migration applies AI to increase accuracy and speed. During migration and validation, AI automates AWS Application Migration Service configuration, translates VM metadata into optimized AWS launch templates, and simultaneously generates Terraform infrastructure-as-code to ensure environments are future-ready. In testing and optimization, AI-driven health checks and dependency validations minimize downtime and reduce errors. By enabling greater parallelization across workloads, Caylent Accelerate helps customers migrate at scale with velocity and confidence.
Part of the Caylent Accelerate Portfolio
Caylent Accelerate for Cloud Migration is the second offering in the Caylent Accelerate portfolio, joining Caylent Accelerate for Database Modernization. Together, these solutions give organizations a faster, more predictable path to eliminate technical debt and modernize with AWS.
The portfolio, built on Amazon Bedrock, reflects Caylent’s commitment to building AI-powered, output-driven methodologies that reduce risk, speed delivery, and ensure long-term value realization. Each Accelerate solution is designed to address critical modernization challenges while lowering the barrier to entry for enterprises looking to evolve with AWS.
Caylent Accelerate for Cloud Migration addresses the top challenges enterprises face today: according to McKinsey, nearly 4 in 10 companies experience migration delays of more than a quarter, and Gartner reports that 69% of organizations overspend their cloud budgets. By combining AI-enabled planning with hands-on delivery, leveraging various AI and AWS services including AWS Transform for VMware, Caylent helps customers reduce CapEx tied to data center renewals, cut OpEx from escalating VMware costs, and redirect resources toward innovation.
Sean Curran, Head of IT at Nationwide Appraisal Services
Caylent Accelerate for Cloud Migration’s AI-powered discovery quickly pinpointed our true migration needs, reducing migration time by 40%. With automated IaC generation and a generative AI testing suite, Caylent is ensuring a smooth transition of our critical systems to AWS, modernizing our infrastructure, retiring VMware licenses, and setting us up for long-term success beyond migration.
Lori Williams, CEO of Caylent
Caylent Accelerate for Cloud Migration reflects how we are changing the way services are delivered. Our approach fuses deep technical expertise, purposeful AI automation, and the experience of delivering migrations at scale. As AWS’s Global Migration Partner of the Year, we know that success is more than just workloads migrated, it’s about ensuring customers are positioned to unlock value quickly and sustain it long term.
