Firemind in Telecommunications

Transforming telecommunications

Transforming telecommunications


Scaling infrastructure and resources to meet network capacity 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 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.

Stay at the forefront of industry trends and leverage the latest advancements in AWS cloud technology

We’re here to revolutionise your telecom business in the cloud. With our expert guidance and cutting-edge solutions, Firemind empowers telecom companies to harness the full potential of Amazon Web Services (AWS) and achieve unprecedented growth and efficiency. We collaborate closely with businesses to design and implement tailored solutions that enhance network scalability, optimise performance, and drive cost savings.

Case Study

Matching Vodafone’s global product records with over 85% accuracy

“Firemind is a a great partner in executing our digitalisation strategy. We have implemented BI & ML solutions in AWS, that have proved instrumental with our Supply Chain visibility, driving actions as response to the global industry challenges all with a dedicated team working with us, to deliver the best solutions for the business.”

Asmoro Utomo

Analytics Lead & Operations Analytics Manager

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Understanding the telecom industry

Cloud technology is revolutionising the telecom industry by enabling virtualisation, infrastructure sharing, and Network as a Service (NaaS). It offers improved scalability, flexibility, and cost efficiency, allowing you to quickly deploy and manage network services. Cloud-based solutions enhance the telecom experience through innovative services, data analytics, and insights. With reduced upfront investments and optimised resource utilisation, cloud technology is transforming the telecom industry by enabling agility, cost savings, and adaptation to the evolving digital landscape.



The global network function virtualisation (NFV) market is projected to reach $70.57 billion by 2026.

Network as a Service


Network as a Service (NaaS) market is expected to grow from $5.4 billion in 2020 to $21.7 billion by 2025.

Infrastructure sharing


Infrastructure sharing among mobile network operators can result in cost savings of up to 35% in network deployment and network operations.

Scalability and flexibility


Of telecom organisations reported improved scalability and flexibility as a result of adopting cloud technology.

Customer experience


Of telecom operators believe cloud services will improve customer experience, leading to increased customer satisfaction and loyalty.

Cost efficiency


Cloud adoption in the telecom sector can reduce capital expenditure by up to 50% and operational expenditure by up to 40%.

Explore our case studies and insights

Introduce AI to your business

Unlock the transformative power of AI/ML in telecom 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.

Telecom use cases by solution area

Accelerate your telecom 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 telecom 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.