Building Cloudlagom: Balancing Innovation and Cloud Costs with AI
I’m a software enthusiast and a digital nomad. I enjoy experimenting with software and exploring digital products across various categories, similar to window shopping in a mall. My passion for computers began early. I spent most of my time playing games and creating fun assets using paint and PowerPoint.
In primary school, I was introduced to coding. I remember programming in computer graphics and building simple HTML interfaces. My computer teachers introduced me to different tools and strengthened my foundation, enabling me to understand paradigms and new concepts even now. In high school, I was forced to choose computer science as a major despite my interest in biology. Later, I pursued a computer science engineering course from Anna University. I never regretted taking an interesting course. I learned a lot about cloud and distributed computing, data mining and science, AI, and mobile engineering.
During my university years, I built my first startup and started consulting projects. I also developed projects for my seniors to support their final-year projects and created apps for small and medium-sized businesses. When I couldn’t sell my creations, I decided to work for a consulting company. There, I learned pre-sales, which involves selling technical solutions or products to customers. It wasn’t actual selling but rather enabling sales by understanding technical requirements. For instance, I built proof of concepts and inspired customers that my solution could help them improve their business operations. Believe me, it’s an interesting area to work in because you learn to engineer software solutions (design, develop, and deploy) for different business cases and interact with customers, sharing your experiences and solving their pain points. It’s like having two mangoes with a stone. From the beginning, I focused on improving my research and engineering skills in the data and AI areas, without fancy titles. I knew this would be the future in early 2015.
Later, I was allowed to lead AI engagement for the company, developing an Enterprise AI product for 400,000 consultants and their customers with a small team of five, mostly constrained by limited resources. Most of the team consisted of fresh graduates. I was tasked with training and building the product, which was undoubtedly a challenging endeavour. I had to help them grasp the fundamentals of technology, which was difficult at the time because there were no adequate learning resources available, such as videos and course content for Data Science and AI. During that period, I created some content to support their learning journey, which was both enjoyable and demanding. Later, I demonstrated the value of the product that my team and I had built. The company sponsored my team’s expansion, hired senior professionals, and established a dedicated team focused on AI research and product development. I had the privilege of meeting many great people during that time, some of whom became close friends. I am grateful for those connections.
Before embarking on this AI suite project, I had experience working on optimisation solutions for power plants aimed at improving energy efficiency and reducing the release of harmful gases into the environment while adhering to compliance standards. I also developed recommendation engines for commerce customers and data mining and statistical models for banking customers. We launched low-code AI tools for business users, which helped accelerate the development of AI systems. However, shortly after that, the senior sponsors at the organization retired, leading to a significant reorganization within the company. This change forced me to relocate to work with the cloud business division of the company. I chose Google Cloud as my preferred platform because I am passionate about data, AI, and innovation, which are the core principles of Google Cloud. I moved from India to Scandinavia to assist customers in designing and developing solutions on Google Cloud. I gained expertise in a wide range of data engineering, data science, and AI tools, including Databricks, BigQuery, Driverless AI, Vertex AI, and Sagemaker.
I had always been entrepreneurial, so I decided to leave the consulting company that offered me diverse opportunities in India and Scandinavia to join a small consulting startup as a Principal Consultant with the goal of becoming a partner. When I joined, the company was small and focused solely on cloud advisory and project management, with only a handful of employees. However, within a few months, we were able to grow to 15 people thanks to the investment from the management company, a sister company that helped us secure more clients because many of their clients became ours. Cloud technology is transformative, and so are our clients. After a year, I joined the company, which was acquired by another consulting company in Stockholm with over 4,000 consultants. Our unique selling proposition was that we were mostly hybrid consultants, meaning we could work on both management and technology problems, which aligned with the new company that acquired us. I continued to focus on cloud and AI consulting, leading AI initiatives in the new company and also helping to expand the Google Cloud Partnerships for them. While I was comfortable with the team, resources, and opportunities to grow my aspirations, the challenges were not particularly demanding, so I decided to leave the company in Sweden and move to London, UK.
And another reason was my marriage. Last summer, I married a UK citizen and had to decide between staying in Sweden or moving to London. While my wife preferred living in London, I wanted to support her decision, so I left Sweden and moved with her. After moving to London, I didn’t find any exciting opportunities that aligned with my interests or passions. Throughout my career, the only consistent challenge I faced in the software industry was the grey area surrounding software costs. This issue was also prevalent among most of my developer and architect friends, especially since we were in the midst of the cloud era. In this era, most software development and deployment activities took place in the cloud, and the teams responsible for these activities were concerned about the costs they were accountable for. This realisation sparked an idea in me: what if we could solve the grey area of eliminating the worry about costs for developers and architects using AI agents? That’s how Cloudlagom was born.
Lagom, a Swedish concept meaning “the right amount,” has inspired Cloudlagom, your AI companion for building cloud resources in a balanced manner that aligns with your business needs. Developers and architects can now rest assured that Cloudlagom will handle cloud costs, eliminating the need for manual intervention. My goal is to make Cloudlagom publicly accessible, ensuring its usability and impact on users. Our software will exclusively focus on optimising cloud costs, outperforming any other solution in the market. Ultimately, Cloudlagom aims to bridge the gap between business contexts and cloud product knowledge, providing a comprehensive understanding of cloud opportunities. Currently, cloud vendors’ AI excels in managing their cloud products but cannot comprehend business contexts and effectively resize opportunities accordingly. This is where Cloudlagom’s potential lies.
As a founding member of the company, I will be dedicated to overseeing company operations, product engineering, sales, and marketing. I plan to create valuable content, including blogs, videos, and other resources that benefit both users and the company. I aspire to gain insights into cloud users’ experiences and develop strategies to enhance their relationship with cloud costs. Additionally, I aim to provide AI-powered insights and foster Cloudlagom’s growth as a trusted partner for our customers.
If you’re here, thank you for taking the time to read my essay. I truly appreciate your support, and I’m excited to continue writing about Cloudlagom in the future.
