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Artificial Intelligence(AI) is innovating healthcare sector

We are under the spell of the Fourth Revolution or the digital revolution. The ability of technology to help the humankind is empowering each day. With AI, Machine Learning, IoTs, and Virtual Reality we are witnessing a diminishing line between man and machine. While the machine is helping man to live luxuriously, it has also extended its help in saving lives. 
The use cases of Artificial Intelligence[AI] in healthcare are fascinating – be it Robotic Surgery, digital consultation, managing medical records over a blockchain network or a virtual nurse assisting you. AI in health is assisting machines to sense, analyze, act, diagnose and help in the clinical and administrative task in a hospital.

Let’s explore in detail on how AI is helping humans to stay healthy and save lives.

Assisting Patient at Every Step

An AI app/product could effectively scan the medical records and help in diagnosing the particular disease, minimizing chances of human error. Based on the prescriptive analysis, the AI software could aid real-time case prioritization. It can precisely analyze actions and predict the risk associated with specific clinical procedures.
AI programs could also help in providing personalized services based on patient data and moods. In fact, an AI app can also recommend the best doctor as per your medical record. AI can be a helping hand for many expectant mothers, with continuous monitoring and ability of early diagnosis.

Several wearable devices and health apps are assisting customers in keeping track of their health. Health apps like Cure.fit help customers to order healthy food and keep tabs on their daily workouts. People can also book appointments and buy medicines through apps like Practo. 

 

Reaching New Heights in Research and Development

Collecting data samples of all the patient in a clinic/hospital, applying big data techniques and deep learning technology could help in extracting meaningful information. Such information could be used to study pattern for a disease or about an individual.
Genetics and study of genes are one of the most crucial jobs in healthcare, with AI the study could be exhaustive and precise resulting in impactful drugs and medicine. Applying medical intelligence could help in understanding the connection between drug and disease at the root level.

Helping Hospitals with Pricing, Risk, and Operations

In need of a marketing strategy that highlights the pain points, lessons learned, target segment and market perception? AI could help you. It can present you a unique strategy that helps in modeling competitive pricing charts,understanding market risk and structuring market data into meaningful actions. Rehauling of your repetitive tasks or back office could be achieved by implementing Robotic Process Automation[RPA] into your system.

With voice-enabled chatbots and video conferencing chatbots, customer queries and appointment booking can be facilitated in private clinics and healthcare sectors 

 

Virtual Nurses, Healthcare Bots

Are you in need of the second opinion from the country’s best doctor at the convenience of your home? AI can help you with Digital Consultation. Or you need a nurse who helps in keeping track of your medicines and food; Virtual Nurse is on his way. Or you need help in picking the best diagnostic center based on your health records? Or you need help in what are the side effects of a drug? Healthcare bots are in for the rescue.

All of this may sound like a sci-fi movie being watched, but now is a possibility with AI and machine learning technology.

Other significant innovation is the chatbot. Chatbots help in raising alarms during life-threatening incidents and save the needful. During an emergency situation, a call made by the chatbot to the needy’s family/ friends or a health center can help the suffering person.

Write us at hello@mantralabsglobal.com to know how we are helping healthcare businesses through AI technology.

Check out the webinar on ‘Digital Health Beyond COVID-19: Bringing the Hospital to the Customer’ on our YouTube channel to know more about how the digital health industry is disrupting the traditional ways of healthcare. 

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What’s Next in Cloud Optimization? Can We Optimize Costs Without Sacrificing Performance?

Not too long ago, storing data meant dedicating an entire room to massive CPUs. Then came the era of personal computers, followed by external hard drives and USB sticks. Now, storage has become practically invisible, floating somewhere between data centers and, well, the clouds—probably the ones in the sky. Cloud computing continues to evolve, As cloud computing evolves, optimizing costs without sacrificing performance has become a real concern.  How can organizations truly future-proof their cloud strategy while reducing costs? Let’s explore new-age cloud optimization strategies in 2025 designed for maximum performance and cost efficiency.

Smarter Cloud Strategies: Cutting Costs While Boosting Performance

1. AI-Driven Cost Prediction and Auto-Optimization

When AI is doing everything else, why not let it take charge of cloud cost optimization too? Predictive analytics powered by AI can analyze usage trends and automatically scale resources before traffic spikes, preventing unnecessary over-provisioning. Cloud optimization tools like AWS Compute Optimizer and Google’s Active Assist are early versions of this trend.

  • How it Works: AI tools analyze real-time workload data and predict future cloud resource needs, automating provisioning and scaling decisions to minimize waste while maintaining performance.
  • Use case: Netflix optimizes cloud costs by using AI-driven auto-scaling to dynamically allocate resources based on streaming demand, reducing unnecessary expenditure while ensuring a smooth user experience.

2. Serverless and Function-as-a-Service (FaaS) Evolution

That seamless experience where everything just works the moment you need it—serverless computing is making cloud management feel exactly like that. Serverless computing eliminates idle resources, cutting down costs while boosting cloud performance. You only pay for the execution time of functions, making it a cost-effective cloud optimization technique.

  • How it works: Serverless computing platforms like AWS Lambda, Google Cloud Functions, and Azure Functions execute event-driven workloads, ensuring efficient cloud resource utilization while eliminating the need for constant infrastructure management.
  • Use case: Coca-Cola leveraged AWS Lambda for its vending machines, reducing backend infrastructure costs and improving operational efficiency by scaling automatically with demand. 

3. Decentralized Cloud Computing: Edge Computing for Cost Reduction

Why send all your data to the cloud when it can be processed right where it’s generated? Edge computing reduces data transfer costs and latency by handling workloads closer to the source. By distributing computing power across multiple edge nodes, companies can avoid expensive, centralized cloud processing and minimize data egress fees.

  • How it works: Companies deploy micro data centers and AI-powered edge devices to analyze data closer to the source, reducing dependency on cloud bandwidth and lowering operational costs.
  • Use case: Retail giant Walmart leverages edge computing to process in-store data locally, reducing latency in inventory management and enhancing customer experience while cutting cloud expenses.

4. Cloud Optimization with FinOps Culture

FinOps (Cloud Financial Operations) is a cloud cost management practice that enables organizations to optimize cloud costs while maintaining operational efficiency. By fostering collaboration between finance, operations, and engineering teams, FinOps ensures cloud investments align with business goals, improving ROI and reducing unnecessary expenses.

  • How it works: Companies implement FinOps platforms like Apptio Cloudability and CloudHealth to gain real-time insights, automate cost optimization, and enforce financial accountability across cloud operations.
  • Use case: Early adopters of FinOps were Adobe, which leveraged it to analyze cloud spending patterns and dynamically allocate resources, leading to significant cost savings while maintaining application performance. 

5. Storage Tiering with Intelligent Data Lifecycle Management

Not all data needs a VIP seat in high-performance storage. Intelligent data lifecycle management ensures frequently accessed data stays hot, while infrequently used data moves to cost-effective storage. Cloud-adjacent storage, where data is stored closer to compute resources but outside the primary cloud, is gaining traction as a cost-efficient alternative. By reducing egress fees and optimizing storage tiers, businesses can significantly cut expenses while maintaining performance.

  • How it’s being done: Companies use intelligent storage optimization tools like AWS S3 Intelligent-Tiering, Google Cloud Storage’s Autoclass, and cloud-adjacent storage solutions from providers like Equinix and Wasabi to reduce storage and data transfer costs.
  • Use case: Dropbox optimizes cloud storage costs by using multi-tiered storage systems, moving less-accessed files to cost-efficient storage while keeping frequently accessed data on high-speed servers. 

6. Quantum Cloud Computing: The Future-Proof Cost Gamechanger

Quantum computing sounds like sci-fi, but cloud providers like AWS Braket and Google Quantum AI are already offering early-stage access. While still evolving, quantum cloud computing has the potential to process vast datasets at lightning speed, dramatically cutting costs for complex computations. By solving problems that traditional computers take days or weeks to process, quantum computing reduces the need for excessive computing resources, slashing operational costs.

  • How it works: Cloud providers integrate quantum computing services with existing cloud infrastructure, allowing businesses to test and run quantum algorithms for complex problem-solving without massive upfront investments.
  • Use case: Daimler AG leverages quantum computing to optimize battery materials research, reducing R&D costs and accelerating EV development.

7. Sustainable Cloud Optimization: Green Computing Meets Cost Efficiency

Running workloads when renewable energy is at its peak isn’t just good for the planet—it’s good for your budget too. Sustainable cloud computing aligns operations with renewable energy cycles, reducing reliance on non-renewable sources and lowering overall operational costs.

  • How it works: Companies use carbon-aware cloud scheduling tools like Microsoft’s Emissions Impact Dashboard to track energy consumption and optimize workload placement based on sustainability goals.
  • Use case: Google Cloud shifts workloads to data centers powered by renewable energy during peak production hours, reducing carbon footprint and lowering energy expenses. 

The Next Frontier: Where Cloud Optimization is Headed

Cloud optimization in 2025 isn’t just about playing by the old rules. It’s about reimagining the game entirely. With AI-driven automation, serverless computing, edge computing, FinOps, quantum advancements, and sustainable cloud practices, businesses can achieve cost savings and high cloud performance like never before.

Organizations that embrace these innovations will not only optimize their cloud spend but also gain a competitive edge through improved efficiency, agility, and sustainability. The future of cloud computing in 2025 isn’t just about cost-cutting—it’s about making smarter, more strategic cloud investments.

At Mantra Labs, we specialize in AI-driven cloud solutions, helping businesses optimize cloud costs, improve performance, and stay ahead in an ever-evolving digital landscape. Let’s build a smarter, more cost-efficient cloud strategy together. Get in touch with us today!

Are you ready to make your cloud strategy smarter, cost-efficient, and future-ready with AI-driven, serverless, and sustainable innovations?

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