Firemind in Retail

Drive retail success with your cloud projects


Scaling infrastructure and resources to meet customer traffic fluctuations.

Cost effective

No upfront investment. Pay on a subscription or pay-as-you-go basis.


Experiment with GenAI and innovative technologies without upfront investment.

AWS Retail Competency Partner

We're a recognised AWS Retail Competency Partner, highlighting our experience working with businesses in the retail sector.

Unlock retail success with Firemind and AWS cloud solutions

Whether you’re looking to modernise your cloud operations, or build new scalable, resilient and cost effective infrastructures, Firemind is the partner for you. Our years of experience working with AWS and the retail sector has given us in-depth knowledge and experience in deploying future proof cloud solutions.

Case Study

We helped Autone achieve over €2 million Y-Combinator funding

“The best experience I ever had was working with Firemind at one of the world’s largest retailers. Seeing how fast they’re able to help us move, and their sheer competence across a wide variety of different factors, really made me fall in love with these guys.”

Harry Cheslaw

Technical Co-founder

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Understanding the retail landscape

The retail sector is undergoing a significant transformation with the integration of cloud technology. Cloud solutions are revolutionising how retailers operate, enabling them to embrace scalability, agility, and cost-efficiency.

With cloud computing, retailers can seamlessly manage and analyse vast amounts of data to gain actionable insights, optimise inventory management, and personalise customer experiences.

E-commerce & marketplaces


The growth of e-commerce has been remarkable. By 2026, 24% of all retail purchases are expected to take place online, highlighting the cloud requirement scaling needed to support such growth.

Mobile payment users


Mobile sales have boomed since Covid-19, with sales set to exceed $510 billion worldwide by 2024. This will mean over 1 billion users worldwide.

Omnichannel retailing


Omnichannel shoppers have a higher lifetime value. According to a Harvard Business Review study, omnichannel customers have a 30% higher lifetime value compared to those who only shop through one channel.

Customer personalisation


Over 84% of all shoppers value personalisation options within e-commerce, maintaining their loyalty for repeat business.

Immersive technology


Research by Gartner predicts that by 2024, 70% of enterprises will be experimenting with immersive technologies (AR & VR), driving a $20 billion market.

Smart retail


According to McKinsey, IoT use cases in retail can generate $410 billion to $1.2 trillion in economic value globally per year by 2025.

Explore our case studies and insights

Introduce AI to your business

Unlock the transformative power of AI/ML in retail 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 deliver personalised recommendations. Stay ahead, exceed expectations, and achieve success with scalable, cost-effective, and agile cloud solutions.

Retail use cases by solution area

Accelerate your retail 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.

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Implement AI into your retail 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.


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.


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.


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.


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.


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.


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.