Firemind in Healthcare & life sciences
Innovating healthcare delivery with the cloud
Accessible
Securely store and access healthcare data for seamless collaboration.
Scalable
Scalable storage and computing resources to accommodate dynamic data needs.
Recoverable
Data protection with encryption, access controls, backups, and disaster recovery.
AWS Machine Learning Competency Partner
As an AWS Competency Partner in Machine Learning, we are proud to offer specialised ML expertise and solutions that help businesses thrive in the digital age.
Transform healthcare business operations with AWS cloud solutions
Experience the transformative power of cloud technology with AWS in the healthcare industry. With AWS, healthcare organisations can unlock a world of possibilities, revolutionising patient care, operational efficiency, and innovation. Seamlessly store, access, and analyse vast amounts of healthcare data securely and effortlessly.
Case Study
Automated medical record collation using AI/ML
“A massive thing we love about Firemind is the way they’ve communicated with us, it’s been really refreshing talking to Firemind about the technical aspects of the project whilst communicating clearly, without the usual jargon and abbreviations.”
Pete Kilbane
Commercial Director
Understanding the healthcare and life sciences sector
By harnessing the power of the cloud, healthcare providers can access and store vast amounts of patient data securely, enabling seamless collaboration and information sharing across healthcare teams. Cloud-based solutions facilitate real-time access to patient records, diagnostic images, and test results, empowering healthcare professionals to make faster, more accurate decisions.
Data accessibility
80%
Of healthcare organisations reported improved collaboration after adopting cloud solutions.
himss.org
Accelerated research
5x
Faster. Using cloud-based platforms for genomics analysis can reduce the time required for analysis from weeks to just hours.
gartner.com
Scalability
20%
Cost reductions visible whilst improving the ability to manage and allocate resources effectively.
health.org.uk
Secure compliance
74%
Of healthcare organisations experienced improved security after adopting cloud solutions, leading to increased compliance.
cloudsecurityalliance.org
Advanced analytics
67%
Of healthcare organisations reported using cloud-based analytics solutions to derive insights from their data, leading to improved population health management.
frost.com
Remote monitoring
82%
Of healthcare organisations have implemented cloud-based telehealth platforms, leading to expanded access to care, reduced hospital readmissions, and increased patient satisfaction.
americantelemed.org
Introduce AI to your business
Unlock the transformative power of AI/ML in healthcare with Firemind’s cloud solutions. Drive revenue growth, enhance customer experiences, and optimise operations. Leverage AI algorithms and machine learning in the cloud to gain insights, predict trends, and build effective infrastructures. Stay ahead, exceed expectations, and achieve success with scalable, cost-effective, and agile cloud solutions.
Healthcare use cases by solution area
Accelerate your healthcare ML project with our MLOps Platform
With a well-architected and scalable deployment, our framework utilises AWS cloud native services to ensure you only pay for what you use, with a solution that scales with you as you grow.
Implement AI into your industry workflow
Explore & Define
AI Roadmap:
Exploration, applications, & goal setting
We'll explore AI's applications and benefits through research, workshops, and team engagement. This will identify how AI can enhance customer experience, inventory management, demand forecasting, pricing optimisation, and fraud detection. We'll then set clear goals, create a roadmap, and identify specific use cases for integrating AI in your retail operations.
Assess & Develop
Data preparation:
Evaluation & model development
We'll evaluate data sources, plan infrastructure, and aggregate diverse data. Then, we'll develop AI models through machine learning, including algorithm selection, feature engineering, training, and validation. Models will be deployed, integrated, and tested for accuracy and performance.
Refine & Scale
AI expansion:
Monitoring, retraining
& scaling
AI implementation is iterative, involving continuous monitoring, feedback collection, and refinements. Retraining models with more data enhances accuracy and adaptability. After successful initial deployment, expand AI across departments with chatbots for customer support, computer vision for visual product search, and AI-driven recommendation engines.
Get in touch
Ready to begin your next cloud project?
As an AWS all-in consultancy, we’re ready to help you innovate, cut costs and scale, at a rapid pace.
To find out more, provide your details to the right, and a member of our team will be in contact with you.
Explore
Exploration & understanding
Your first step is to explore and understand the potential applications and benefits of AI in your business. We'll conduct research, construct workshops, and engage with your team to gain insights into how AI can drive improvements in areas such as customer experience, inventory management, demand forecasting, pricing optimisation, and fraud detection.
Define
Set your goals
Once you recognise the value of AI, we'll define clear goals and objectives for integrating AI into your retail operations. These goals could include enhancing customer personalisation, improving operational efficiency, reducing costs, or increasing revenue. We'll craft a well-defined roadmap and identify specific use cases where AI can deliver tangible business value.
Assess
Assessment & preparation
AI relies heavily on quality data. We'll assess your existing data sources, identify gaps, and determine the necessary data collection and storage infrastructure. This may involve aggregating data from various systems, such as sales transactions, customer interactions, inventory and/or external sources.
Develop
Model development and deployment
Once the data is ready, we'll develop and train AI models using machine learning techniques. This involves selecting the appropriate algorithms, feature engineering, model training, and validation. The models are then deployed into your retail environment, integrating with existing systems and processes, then tested for accuracy and performance.
Refine
Refinement & improvement
AI implementation in retail is an iterative process. We'll help you continually monitor the performance of AI models, collect feedback, and makes necessary refinements. As more data is collected, the models can be retrained to improve accuracy and adapt to changing market conditions.
Scale
Scaling & expansion
As the initial AI deployment proves successful, you can expand the use of AI across different functions and departments. This could include implementing AI-driven chatbots for customer support, using computer vision for visual product search, or leveraging AI-powered recommendation engines for personalised product suggestions. Whatever you're choice, we have you covered.