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Digital Transformation Is Not A Sprint, But A Fast Marathon: Shoaib Mohammad, Founder & CEO, Lumiq

Digital Transformation Is Not A Sprint, But A Fast Marathon: Shoaib Mohammad, Founder & CEO, Lumiq

  • In terms of technology, there are issues related to rising concerns of data security and compliance in the cloud adoption in the financial services sector.

“Our ready-to-use products, platforms and accelerators help power customer outcomes and deliver digital efficiencies faster”

Shoaib Mohammad

About a decade ago, Shoaib was in the US, and he got acquainted with the emerging concept of digital-first new world companies. To be specific, here, data took a front seat in terms of driving business outcomes and a lot of impetus was given to data collection and leveraging it to generate business value. However, that was not the case in India, where traditional businesses were seen taking baby steps towards becoming tech-driven enterprises.

Hence, Lumiq was born — a data and analytics company that powers data-driven decision-making with AI and machine learning solutions for financial enterprises. Shoaib Mohammed, Founder and CEO at Lumiq, stepped in to bring this mindset to businesses and help Indian enterprises adopt the same practices that digital-first companies had.

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“Our strategic focus is to go deep into one vertical. So, we started with insurers and then nimbly expanded to banks – stretching seamlessly into an array of financial services. This is critical as nuances of business or domain knowledge is key to grasping how the data can be analysed and monetised,” said Shoaib.

The Growth Trajectory

In August 2021, this Noida-based startup received funding of $2 million from Info Edge Ventures, which the company plans to utilise in pushing the company’s sales growth, enhancing product offerings, and expanding its global footprint, especially in the US and South-East Asia. Moreover, as Shoaib says, Lumiq has more than 30 enterprises as clients for whom they are the go-to partners for data-related initiatives. Lumiq has developed over 70 ready-to-deploy AI/ML data models and is live on 20 cloud data platforms of financial enterprises. In addition, the company has analysed over 1 billion customer interactions and influenced more than 100 million customer journeys. 

Adding a feather to its cap, the startup was awarded the AWS Specialty Partner of the Year 2021 Award for data, analytics, and machine learning. The company believes that they have achieved this feat through their consulting-led prescriptive analytics approach with API driven integration for most business platforms. This is helping customers drive business transformation faster and more efficiently.

Lumiq’s USP

“We started Lumiq with a vision to be the one-stop shop for any data-driven initiatives for our clients”

Lumiq’s customers include leading insurers, banks, and NBFCs. Financial enterprises are looking for two things – processes to improve customer experience and profitability. Hence, the startup built its solutions for financial service providers who want to take a proactive approach for handling and optimising their data. As a result, not only does it accelerate the confluence of AI, BI and DI (Data Interchange or Data-as-a-Service) operations in an FSI organisation, but it also helps to monetise data insights. 

“At a time where a data analytics project can take anywhere from six months to even years, our agile teams help build and deliver ready to deploy models in 100 days, helping customers drive quicker business outcomes,” said Shoaib.

Lumiq solutions help remove data-driven innovation roadblocks that arise from siloed data and the lack of skill and experience. This includes:

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  • Lumiq’s ready-to-use emPower platform and accelerators help power customer outcomes and deliver digital efficiencies faster. This allows the company to have a faster GTM strategy and stronger ROI and helps them build a knowledge repository clubbed with proven products, accelerators, and use cases.
  • The company has adopted an end-to-end approach from organising data to model development, deployment, and governance. This focus across data engineering, data science, and ML-Ops has ensured that business value creation is continuous and there are successful transformations. 
  • To ensure easy adoption and understanding of model recommendations, it has embedded transparency and explainability into its solutions. For example, take Drishti – an intelligent document processing and automation solution, the company uses the UNET model and the RotNet architecture for the pre-processing stage. Combining these with ML services like Amazon Textract and then loading their own proprietary AI models, powered by its data platform, the startup provides the customer with a unified solution – from point zero to the final output.
  • In addition, providing this as an API integrated system ensures solving a problem with the least interference to the existing workflows. 

Tech behind 

Lumiq operates in three key areas: data science, data engineering, and operations, including DevOps and MLOps.

  • The data engineering teams are conversant with leading cloud platforms like AWS, GCP and Azure and adept at leveraging the cloud-native architectures. The technology stacks in data engineering include Kafka, CDC tools like DMS, Spark, typical databases (both RDBMS, NoSQL, Graph or Time Series) and cloud warehouses of the likes of Redshift.
  • The emPower data platform is built on a Lego block kind of architecture with the option to bring in virtually any new technology.
  • The data science stack leverages Python, TensorFlow, Keras, PyTorch and KubeFlow.
  • The operations teams operate with Kubernetes, Docker, Jenkins, Ansible, and Prometheus. Application stack typically consists of Java, Node.js and React/Angular. 

Challenges and the way ahead

Talking about the challenges, Shoaib said: “Our challenges mostly originate from business, technology and talent standpoints. One of our key challenges is to scale and drive non-linear growth. Having said that, it doesn’t mean we are not increasing our headcount. However, talent acquisition in these times is a perennial challenge that is often accompanied by attrition.”

In the domain that the company operates in, besides standalone skills, it is also difficult to get full-stack engineers on board, and that’s a challenge the whole ecosystem faces currently. In terms of technology, there are issues related to rising concerns of data security and compliance in the cloud adoption in the financial services sector. This explains why data-driven tech adoption is relatively slow, especially in the financial services sector. 

“We believe that digital transformation is not a sprint, but a fast marathon, and we are confident that with our business knowledge, domain expertise and technology, we are well-prepared to take these challenges head-on,” concluded Shoaib.

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