L&T Sufin and MongoDB's disruptive partnership accelerates transformation of B2B Industrial trading

L&T SuFin leverages MongoDB's flexible document model and scalability to revolutionize B2B e-commerce for industrial products and services.

In an interview with DataQuest, Bhadresh Pathak, CEO, L&T Sufin, Nabarun Sengupta, CTO, L&T Sufin, and Himanshumali, Solution Architect Leader at MongoDB, shed light on the game-changing partnership between L&T Sufin and MongoDB. L&T Sufin, an integrated B2B e-commerce platform for industrial trading, aims to address the challenges faced by MSMEs in sourcing industrial suppliers digitally and cost-effectively. With MongoDB's document-centric database technology and scalable infrastructure, L&T Sufin has unlocked new levels of flexibility, efficiency, and developer productivity, empowering businesses in the industrial sector.

Excerpts:

Could you please give a brief introduction about L&T SuFin and what does L&T Sufin do?

Bhadresh Pathak: L&T-SuFin is an integrated B2B e-commerce platform for buying and selling industrial products and services. Backed by L&T – India’s leading manufacturing, building & construction company with a presence in over 50 countries, L&T-SuFin aims to transform the B2B marketplace. It enables businesses, especially MSMEs, to source their industrial suppliers pan-India digitally and cost-effectively."

The idea of creating L&T Sufin came about when we realized the absence of a B2B platform for industrial supplies. While there are platforms for lead generation, there was no platform that catered specifically to industrial supplies at the B2B level.

In the B2B environment, handling transactions and trade is more complex compared to the B2C environment. L&T Sufin addresses the challenges that arise in the trade of industrial supplies at the B2B level, with a focus on MSMEs.

What kind of problems is L&T trying to solve in the industry within this ecosystem?

Bhadresh Pathak: Traditionally, buyers would spend a lot of time and effort identifying leads and making numerous calls to find the products they need. L&T Sufin simplifies this process through a request for quotation (RFQ) system. Buyers can generate RFQs to identify products with technical specifications and request quotations from multiple suppliers. They can then compare the quotes, product availability, and technical specifications to make an informed decision.

For suppliers, it's essential to know the credentials of the buyer, their credit terms, and payment methods. L&T Sufin handles these details through the RFQ, acting as a contract between the buyer and the supplier. The platform ensures trust and verification for all buyers and sellers, which is especially valuable for MSMEs. Transactions are securely facilitated through nodal accounts, where payments are received and then sent to the seller. The platform also manages the logistics of delivering goods from sellers to buyers.

Additionally, L&T Sufin addresses the working capital requirements of trading on the platform by providing customized financing options through banking and NBFC partners. It serves as a one-stop-shop for digital trade requirements, utilizing data seamlessly and transparently to facilitate rational decision-making. Solving these problems sets L&T Sufin apart.

Tell me about the partnership between L&T and MongoDB and why L&T Sufin decided to partner with MongoDB?

Nabarun Sengupta: From the start, we had diverse players on our platform, including logistic providers, finance providers, and counterparties in the MSME sector. We needed to develop functionality rapidly and ensure scalability. Given the scalability requirements and complexity of the sector, we realized that a relational database was not the most efficient choice.

The RFQ functionality, a vital part of our platform, naturally fit into a document-centric model. We decided to use a NoSQL database, and MongoDB's community edition was our initial choice. However, building and managing a cluster of nodes for scalability required significant in-house engineering expertise. That's when we discovered MongoDB Atlas, a database service offering flexibility, agility, scalability, and security. Atlas provided all the benefits we needed, including encryption

What are your core focus areas behind this integrated platform?

Bhadresh Pathak: From a business standpoint, our core focus areas behind the integrated platform are to address the inefficiencies in supply chains. We aim to improve the transparency of data, links, and trade terms in the supply chain ecosystem. By connecting all entities involved in the supply chain through a common platform, we enable seamless data flow. This allows each partner to access relevant data, resulting in efficient operations and a comprehensive understanding of the supply chain status. Our platform offers flexibility by providing separate modules for logistics, financing, payments, and other factors. This flexibility allows us to offer tailored packages that meet the unique requirements of different customers.

Nabarun Sengupta: Our platform provides logistics and finance services as part of our core offerings. These services can be availed independently, and we have designed the architecture to isolate different domains using microservices. At the database level, the logistics and order management data models are separated from the rest, and integration is achieved through events using MongoDB's event type support or messaging middleware. This approach enables plug-and-play integration of multiple services, allowing customers to consume them either as a whole or individually.

How has MongoDB enabled L&T to solve the challenges that they mentioned?

Himanshumali: At the core of MongoDB is the document model, which provides the flexibility needed to address L&T's challenges. MongoDB supports various data models, including key-value store, relational, graph, and geospatial data, all accommodated within the document model. This flexibility is crucial for L&T, as different product information with varying specifications and fields can be stored in a single data collection. Creating structured databases for such dynamic data would be challenging with traditional approaches.

Additionally, MongoDB Atlas, our platform, relieves customers like L&T from the manageability and operational aspects of their databases. It allows them to focus on improving their capabilities and business rather than worrying about database management. Atlas provides scaling capabilities, including storage and auto scaling, ensuring seamless scalability based on workload demands. High availability is maintained, and scaling and upgrades occur without downtime due to the three-node architecture of Atlas. These capabilities have provided significant benefits to L&T in terms of manageability, scalability, and maintaining a high-performing database.

What is MongoDB's product focus, and how are you deploying new-age technologies to your products and solutions?

Himanshumali: MongoDB is more than just a core database; it's a data platform that manages the end-to-end lifecycle of data. In addition to storing data, MongoDB Atlas, our platform, provides search capabilities that enable customers to find the right data efficiently. It includes typo tolerance and autocomplete features to enhance the customer experience.

We focus on addressing evolving industry needs by continuously improving our products and solutions. For instance, we have enhanced search capabilities by introducing faceted search, allowing searches across different categories. We have also added a "more like this" feature to improve search functionality. Another area of focus is real-time analytics, and we have introduced capabilities such as a columnar index for long-term analytics. This index enables analytics on specific fields across different documents. These improvements and new features aim to address customer requirements and offer a comprehensive data platform for a wide range of use cases.

Can you name some industry leaders who have successfully implemented your solution, how they have benefited from it, and what pain points they came to you with?

Himanshumali: We have a diverse range of customers from various sectors, including health tech, edutech, digital natives, and large enterprises, who are using MongoDB. One notable customer is myBillbook, a startup focused on digitizing SMBs for their payment and account payables needs. They have implemented MongoDB with our realm database, which serves as our mobile database. This implementation allows their users to capture bills or account payables and receivables on a mobile device and seamlessly sync it to Atlas, our back-end platform. The bidirectional sync feature in Atlas has made it extremely convenient for them to use. In fact, myBillbook is one of the largest customers globally for our mobile database. We have similar success stories across various industries, with different customers utilizing MongoDB for different use cases.

Can you discuss some of the latest developments that companies should pay attention to right now?

Himanshumali: We regularly release newer versions of our database, and last year we launched MongoDB 6.0. In a few months, we'll be introducing MongoDB 7.0, which will be an enhanced version with several improvements. Some of our key focus areas include enhancing search capabilities. Over the past year, we have added faceted search, enabling users to search across different categories. For instance, in an e-commerce application or marketplace, searching for a product will yield results from various relevant categories. We have also incorporated a "more like this" feature in our search functionality. Additionally, we are concentrating on dense vector search, which further enhances the search capabilities.

Another significant focus area for us is real-time analytics. We have introduced capabilities to support real-time analytics and have incorporated a columnar index to enable long-term analytics on MongoDB data. This column index allows users to select specific fields from different documents and perform analytics on those fields. These are some of the prominent changes and improvements we are actively working on.

Furthermore, we recently launched the relational migrator, which assists in migrating from traditional relational databases to MongoDB. It can be considered as an ETL (Extract, Transform, Load) tool that facilitates connection with relational databases. The migrator provides a user interface for mapping the data, and once the mapping is finalized, the migration from a relational database to MongoDB becomes possible.

How have the results for L&T SuFin improved after adopting the MongoDB platform?

Nabarun Sengupta: Our data infrastructure's manageability has significantly improved. Previously, we had full-time employees dedicated to managing the database infrastructure and ensuring scalability. With MongoDB, we have achieved greater efficiency in this aspect.

Another major benefit we have experienced is enhanced developer productivity. MongoDB seamlessly integrates with middleware infrastructure, making it easier to develop code, make changes to our model, and evolve our business capabilities. Compared to our previous experience with a relational platform, our developer productivity has improved by at least 50-60%. The flexibility and speed of change provided by MongoDB have positively impacted our choices and outcomes.

Is there anything else that the MongoDB team would like to add?

Himanshumali: Our goal is to enable a wide range of use cases to run on MongoDB so that customers don't need to add niche technologies to their stack or spend time on complex ETL processes between different technologies. Managing and maintaining multiple technologies adds unnecessary overhead and complexity. We are focused on expanding the capabilities of our platform to provide customers with a seamless experience throughout the entire data lifecycle on MongoDB. Our product roadmap is aligned with this objective, and we strive to continuously improve and meet the evolving needs