Greetings for the day. Thank you for joining today's session where we will explore how platform engineering can bridge the gap between the promise of digital transformation and its actual impact. I'm marnic a platform architect. Meet my co-presenter. Hello, I'm Trata, and I'm a student as well as a digital transformation enthusiast. We bring prospective from both the business and technology sites. So we look at transformation not just as a buzzword, but as an operating model that delivers scale, agility, and resilience. Digital transformation leads every corporate agenda, but many organization finds that the impact is very limited. Why? There are many reasons to it, but just to quote a few. One of the reason is there are too many silos, duplications, and a legacy complexity that exist in the organization's ecosystem. They struggle to scale cost efficiently. There is often a lack of agility that prevents launching new products faster and quickly. So while business demands speed and innovation, technology often gets drawn in complexity, that's where platform engineering provides a digital platform. So now what is a platform? A platform is more than technology. It's a reusable digital foundation. It abstracts away complexity, standardizes how we operate and accelerates innovation. Think of it like town planning. Instead of building random houses, we design roads, utilities, and rules that let the city grow efficiently. Similarly, platforms enable business and engineering teams to build at speed and scale types of platforms. We break platform strategy into four categories. Engineering platform it as a service for developers. This is about developer efficiency. By offering self-service infrastructure pipelines and monitoring, we reduce friction and repetitive tasks. Developers can then focus on building business value instead of plumbing. It's about moving from firefighting to value creation. Second business capabilities platform business as a service for speed and agility. Think of this as the business engine, instead of fragmented IT solutions, business capabilities are bundled as reusable services. This allows rapid product launches, agility in responding to change, and a modular architecture that embraces continuous transformation. Data, platform data as a service, empowering insights and experimentation. Data is the oil of modern enterprises. A data platform enables discovery, creation, and consumption of data products. With proper governance, with real type pipelines, it drives insights, experimentation, and decision making. This is how organizations unlock data-driven culture at a scale. Customer experience platform journey as a service, enabling consistent and personalized experiences. Here, the focus shifts to the end user. A CX platform unifies the customer journey across channels. One profile, consistent personalization, seamless onboarding of partners. It's about delivering one brand, one experience, irrespective of channel or partner ecosystem. Each there builds on the other, creating a full stack digital backbone. Platform thinking is not about building one of tools or isolated think systems. It's about designing reusable capabilities that can be shared across the enterprise. Delivery infrastructure. Instead of every team setting up their own CICD pipelines, cloud accounts, and monitoring, the platform team provides them as a ready to use secure foundation, API, and architecture remediation service boundaries, gateways, and even driven architectures are made consistent, so product teams don't reinvent governance every single time. Self-service data. Data is packaged as products, clean, discoverable, and ready for consumption. Teams no longer hunt for data sets. They simply subscribe to them, experimentation and telemetry. New ideas can be tested safely with real time telemetry, feature toggles and control roll. So innovation becomes responsible and scalable. Customer touch points, every customer interaction. Whether web app or partner portal feels seamless because platforms ensure consistency in the personalization, routing, and content strategy. So the outcome delivering faster, build ecosystems, gain insights, experiment responsibly, consistent experience. This is the power of platform thinking. It shifts organizations from fragmented delivery to enterprise wise scalability and resilience. So what is digital transformation? This evolution is the journey just from simply convert to automate, to transform. So now let's discuss this three terms, which are often used interchangeably. Digitization, convert analog to digital. It's just like scanning paper. Digitalization, automate existing workflows and digital transformation. Reman reimagining how business creates and delivers value with technology at the core. Now let's discuss why platforms matter. For digital transformation, a system centric approach slows us down. Applications are siloed, integrations are brittle. A platform approach changes the game. Speed and agility through self-service capabilities, scalability and resilience via cloud native foundations simplification. So teams focus on business value and innovation at scale, unlocking new business models and revenue systems. Now I hand over to my core speaker to talk about this particular problem statement in the healthcare domain. Now, so far, we have understood the various terminologies about what is platform thinking approach, and what is platform engineering along with digital transformation. Now, let's understand and pick up a use case in a healthcare domain, which is related to the invoice processing, and how do we apply what we have learned so far to this problem statement to digitally transform their business? Here goes the use case. So medical invoicing today is highly manual, paper driven and error prone processing, which processes over a million of documents weekly with a significant dependency on human effort. Each invoice requires manual. Physical verification of signature and stamps and manual forwarding to claims management team and various other departments for further processing. This results in a heavily manual operations that demands significant number of full-time resources for end-to-end processing the claims. Area is growing in the various geographies. As you say, the market size is significantly large in the North America, Europe, AsiaPac Pacific. Now, while we have understood the current state of this problem, how are we tackling this problem in the today's world? Let's understand what kind of inefficiencies it brings. To the system first, it brings lot of operational inefficiencies in a way that, first, the invoice processing consumes substantial manual hours on a monthly basis. Second, this leads to the high susceptibility to data entry errors and fraudulent claims. Third, there is a limited accessibility and a real time visibility to stakeholders. Fourth, this has increased cost to serve. Reimbursements and reduce provider satisfaction. In addition to that, there is also a challenge associated with scalability and susceptibility. The current system cannot scale with increasing invoice volumes. There is a dependency on paper-based workflows, which contradicts digital and environmental goals. Inefficient workflows strain, both operational budgets and compliance postures, which leads to claim denials and delay in reimbursements. Now what we are trying to propose is a flow, which is built. Using a platform thinking approach and how we have digitally transformed the entire ecosystem. Let's see, so there are multiple personas which are using this particular digi digitally transform flow for the invoice processing. We have various personas, right from the healthcare organization to the insurance organization. Along with the partner channel, who also helps to analyze and actually process the claims for the healthcare organization as a third party supporters. And in addition, we also have a internal admin and a support team who are using our digital transformation process. The workflow. Now, let's see how the health healthcare organization wanted to, who wanted to. Process the claims via uploading the invoices will happen in this workflow. In the digitally transformed workflow, so first, the healthcare organization uploads a bunch of invoices for claim processing through a web portal interface, which is provided by this invoicing system. Second, the batch of invoices are verified for sanity checks and it'll get stored in a cloud storage. Third, each invoice is scanned via OCR and NLP solutions to extract. The required information, and this is where we actually do the digitalization. The fourth step is extracting the signature and stamps available for each invoice via deep learning solutions and save it again on the cloud storage. Next it moves to the next department wherein the government representative will audit and verify the signature and stamps manually. And provide an approval. Please note that here we have introduced human in the loop so as to avoid any fraudulent at this stage. Upon approval, the invoice batch will be sent to claims department for further processing. The insurance company representative will take the invoices for further validation. And either approve, reject, or ask for more information for the claim processing, and the UpToDate status will be reflected on the web portal. If the claim is approved by insurance company, the payment workflow will be triggered via payment interface and the amount will be credited to the patient's account. If the approver requires any additional information about the invoice, it'll be moved to the on hold status. However, in case the claim is considered as fraud or due to insufficient documentation, it'll be reported as rejected, and this is how the current manual process is entirely digitized using a platform thinking approach along with applying the digital transformation lens. Our strategic focus here is very clear. We move from digitization to digitalization and then entirely transforming the workflow into digital transformation. The shift is from manual to digital transformation, embed AI to detect fraud and ensure compliance, transform the invoicing journey end to end with automation enabling scalability and accuracy. C. Let's also discuss the key milestones in this transformation. This journey unfolds in phases. Start the value stream mapping and launching the e-invoicing platform. Integrate O-C-R-N-L-P and fraud detection. Automate workflows across stakeholders. Deploy real-time dashboards finally expand across networks and geographies. Each milestone builds maturity and unlock measurable value. Let's quickly have a glance at the roadmap. Our roadmap runs as a multi-year program scaling from core implementation to full ecosystem adoption. Importantly, this solution evolve to be an industry agnostic and platform agnostic. This means the lessons from medical invoices we will apply to further extend it to other industries like insurance, retail, as well as finance, and many more. Now let's understand here that how we have enabled the digital transformation using platform thinking lens. Let's consider the same use case that we are discussing now, which was a paper heavy labor intensive and prone to errors. Now applying platform thinking transformation into this we made it digital first and AI enabled workflow. There is a shared ingestion layer for all invoices, whether it is from hospitals, insurance partners, or government entities, which comes through a single digital portal. This ensures consistency and traceability. The customer interacts via two channels. One is a web portal and others a chatbot for submission of their invoices. Second, there is a u reusable data services. So instead of manual entry, O-C-R-N-L-P engines are automating the entire metadata extraction signature, and staff stamp validation process. These services aren't built for one team, but they are reusable across various departments, be it claims compliance, or audit. Third is a validation as a service, the AI models and human in the loop framework. Validates invoices against business rules. The fraud detection and anomaly checks run as a shared capability. Fourth is a claim processing platform wherein we are routing, auditing, approvals, and the entire payment gateways. They run through an orchestrated workflow, which is designed as modular trace and scalable. The final on the top is the experience layer wherein the customer's insurance and the regulators. Get real time status updates via chatbots, as well as real time dashboards to which delivers transparency and trust. The shift is profound. Instead of switching together fragmented workflows, we build a platform backbone. Instead of scaling people linearly, we scale capabilities exponentially. Instead of operational risk, we build compliance into the process. By design, there is a sense of enabling digital transformation through platform thinking, which converts a broken manual journey into a future proof reusable capability stack that can extend beyond medical invoicing to the entire insurance ecosystem. Now let's see how we can define the success. While there are ma many measures through which we can. Define as well as measure the success. We think these are the three important dimensions, which should be definitely considered while we define the success metrics. The first is the customer metrics. Second is the business value wherein we ensure fraud reduction, compliance by design and lower cost to serve. And third, an important aspect of it is an operational metric. Wherein we will measure the system uptime, which is nothing but the availability of the system, the accuracy of the system, fraud detection rates, and the throughput. Success is when customer, business and operations are all aligned on measurable impact. So our message is simple. Platform engineering is the backbone of digital transformation. It bridges the gap between ambition and reality. Enabling organizations to move faster, safer, and smarter. We appreciate your time and attention today. We hope our perspective adds value, and today's session leaves you with fresh insights. Happy learning. Thank you.