How Shravani Limited Cut AWS Costs and Secured $10,000 in Activate Credits with Cloudvisor
The Client
Shravani Limited is a UK-based technology company building purpose-driven digital platforms that combine innovation with social impact. Their flagship product, CarerNest.com, connects families with trusted, DBS-checked carers through a verified digital marketplace — making home care more accessible, transparent, and affordable.
CarerNest now serves early users across the UK, with a growing number of families and carers onboarding to the platform.
Founded in St Helens by Harish S. Agawane and Jyoti Kamble, the company is also developing VideoAvatar.ai (AI media automation) and UKRailLive.co.uk (real-time rail app focused on accessibility). CarerNest aims to reduce care costs while increasing earnings for carers and helping address the UK’s care shortage.
- Industry:Technology, Information and Internet
- Company Size:1-10
- Country:United Kingdom
“Cloudvisor helped us transform our early AWS setup into a scalable, cost-efficient infrastructure. Their guidance on GPU workflows and credit optimisation allowed us to focus on building technology that truly makes a difference in people’s lives.”
Challenges
- Managing GPU-heavy workloads efficiently
- Rising cloud costs due to unoptimised infrastructure
- Need for secure, scalable architecture across multiple AI platforms
- Limited monitoring, cost visibility, and security setup
- Required guidance on credit utilisation, architecture best practices, and compliance
Shravani Limited was scaling several AI-driven products simultaneously, which amplified both technical complexity and operational risk. Their GPU-intensive workloads required more efficient optimisation to avoid performance instability and unnecessary spending. At the same time, ensuring security, visibility, and proper configuration across AWS services became increasingly challenging as their platform grew. The team also needed expert support to align architecture with best practices and manage credits effectively, all while focusing on product development and launch timelines.
Solutions
Cloudvisor supported Shravani Limited in optimising their AWS environment and strengthening the foundation for their AI-powered platforms. The team received hands-on guidance across infrastructure setup, GPU workload optimisation, and AWS credit utilisation. Cloudvisor also improved visibility, security, and monitoring across their stack, enabling Shravani to stabilise deployments and accelerate product development.
Guiding AWS Activate application
Helped the team navigate the AWS Activate credit process to unlock funding for early infrastructure needs.
Structuring AI infrastructure
Designed and implemented an architecture using AWS Batch, SageMaker, and Lambda to support AI model training and deployment.
Optimising GPU workloads
Provided hands-on support to improve performance and reduce inefficiencies in GPU-heavy processes.
Improving security setup
Enhanced the team’s security posture with better configuration, access controls, and best-practice alignment.
Enhancing monitoring and visibility
Strengthened cost visibility and system monitoring to help identify issues earlier and improve operational stability.
Cloudvisor’s ongoing support allowed Shravani Limited to shift their focus back to innovation and product delivery while maintaining a reliable AWS foundation.
AWS Services Used
- Amazon SageMaker
- AWS Batch
- AWS Lambda
- Amazon S3
- Amazon DynamoDB
- Amazon CloudWatch
- AWS IAM & Security Hub
Results
After optimising their AWS environment with Cloudvisor, Shravani Limited achieved significant improvements across cost efficiency, deployment stability, and platform scalability:
40% lower infrastructure costsStabilised spending through workload optimisation and improved visibility.
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Additional credits securedUnlocked $10,000 in AWS Activate credits to support the growth of their AI platforms.
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Successful launch of CarerNest.com MVPDelivered a reliable infrastructure foundation that supported their first major product rollout.
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Onboarded early carers and familiesEnabled real users to join the platform and begin interacting with the service.
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Stabilised AI model deploymentImproved performance and consistency across GPU-heavy workflows.
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Recognition in the St Helens StarGained visibility for digital innovation in community care.
