Arvind Rao
Customers today are asking for more than just products or services; they want experiences that are seamless, personalized, and intelligent—delivered faster than ever. Businesses are stepping up, but the truth is that technology is carrying the weight of these expectations. And, platforms1 have emerged as the backbone of this connected world. But building platforms that can support the demands of speed, scale, intelligence, and trust isn’t straightforward. When done right, platforms can set new benchmarks.
Speed: Faster and Smarter Without Cutting Corners
Exceptional speed in enormous uncertainty is not easy. A large American consumer goods corporation faced a frustrating challenge: processing vast datasets from retail partners took up to five hours. Five hours is an eternity in a fast-moving world —time they simply couldn’t afford. By rethinking their approach with a next-generation platform, that time shrank to 34 minutes. Another process, previously a two-hour ordeal, now takes just 24 minutes.
Another leading US bank2 reduced their KYC time from weeks to days and now has the capability to process 1 million documents a month. These are not marginal gains by any measure, especially since it is also about freeing up time to focus on strategic priorities rather than firefighting.
So how can one achieve this?
- Automation as a Foundation: With Kubernetes enabling auto-scalability and resiliency, operations were optimized to adjust dynamically to demand.
- Streamlined Access Management: Integrated Identity and Access Management (IAM) ensured that the right people had the right access at the right time, eliminating bottlenecks and boosting efficiency.
Scale: Designed for Growth
What is scaling? Is it handling more users or transactions? Handling higher volumes? Yes. But for enterprises, it is also about managing the increasing complexity of interconnected systems, data, and workflows. We need to do this in a way that’s sustainable, and efficient, while also reducing infrastructure requirements and delivering better outcomes. Platforms that scale effectively don’t just survive under pressure and don’t just survive today. They need to be agile, future-ready, and responsive to fast-changing circumstances.
Here’s what makes scalability possible:
- Real-Time Observability: Every system, every service, every transaction is monitored. This level of visibility3 means potential issues are identified and resolved before they can disrupt operations.
- Reusable Components: By building a library of modular, reusable solutions4, enterprises can replicate success without reinventing the wheel, reducing costs and accelerating deployment timelines.
Smart: Intelligence as the Core Enabler
The platforms of yesterday were built to automate. The platforms of today are built to think. Intelligence embedded at every layer transforms platforms from tools into enablers of growth and innovation.
Here’s what that looks like:
- AI-Augmented Decisioning: Enterprises face countless repetitive but critical decisions—like matching customer data or mapping product categories. AI takes on the heavy lifting, handling 90% of these decisions while escalating edge cases to humans. And with a “learning cache” capturing decisions, the system only gets smarter over time.
- Multimodal AI: Insights don’t just come from numbers on a spreadsheet. Platforms that integrate text, images, audio, and video unlock deeper, richer insights that were previously out of reach.
- Agility in AI Adoption: The AI ecosystem evolves daily. Platforms must integrate new models, like Google Gemini or Llama, without disrupting workflows—ensuring enterprises always have access to the best tools available.
Safe: Building Trust into Every Layer
Speed, scale, and intelligence mean nothing if enterprises can’t trust the systems delivering them. Trust is non-negotiable, and it comes from embedding safety into every layer.
Here’s how trust is built:
- Responsible AI Practices: From identifying bias to ensuring explainability, every AI decision must be transparent and auditable.
- Agentic Governance: With agentic AI, where multiple bots collaborate on tasks, governance ensures alignment with enterprise objectives. Misaligned automation is simply not an option.
- Deployment Flexibility: Whether running in the cloud, on-premises, or hybrid environments, the platform must maintain consistent security and performance.
Without trust, platforms fail to deliver their promise. With safety, platforms enable enterprises to confidently embrace innovation.
Safety is where the conversation about platforms often ends, but let’s ask the next big question: what does it take to architect a platform capable of delivering on these ambitious promises? It’s one thing to talk about speed, scale, intelligence, and safety, but achieving them requires a deliberate and thoughtful design.
At the core of any great platform are four critical layers5: the data layer, the AI layer, the process layer, and the experience layer. Each layer plays a vital role in creating a cohesive, high-performing system. The data layer ensures that vast amounts of information are processed rapidly and reliably, acting as the platform’s foundation. The AI layer transforms raw data into actionable insights, leveraging advanced models to make intelligent predictions and automate key decisions. The process layer translates this intelligence into orchestrated workflows, managing complexity while maintaining efficiency. Finally, the experience layer is where it all comes together, providing users with a seamless and intuitive interface that drives engagement and delivers value. Together, these layers create a platform architecture that is robust yet flexible, powerful yet intuitive.
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A Future Powered by Platforms
Speed, scale, intelligence, and safety aren’t separate goals. They are interconnected pillars of a successful enterprise platform strategy. When these elements come together, they create a foundation for exponential transformation.
Take digital observability. Expanding from task mining to conversational mining, platforms are now turning unstructured data like emails, chats, and social interactions, into actionable insights.
Or look at document AI. Platforms that process millions of documents in parallel aren’t just streamlining workflows; they are enabling entirely new use cases, like automating compliance audits or simplifying global supply chains. What was once impossible becomes routine. One of the largest telecom companies6 in the world was overwhelmed with their tower rental contracts. And, with the right Document AI capabilities they were able to get an accurate view of the contracts, were in a better position to negotiate, and scored $21 million in savings.
The future belongs to platforms that are dynamic ecosystems—evolving with the needs of the businesses they support.
Disclaimer Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the respective institutions or funding agencies.
- https://www.edgeverve.com/ai-next/forrester-edgeverve-thought-leadership-paper/
- https://www.edgeverve.com/ai-next/case-studies/leading-bank-reduces-kyc-turnaround-time/
- https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/tech-forward/building-the-cloud-ready-enterprise-network
- https://www.mckinsey.com/capabilities/quantumblack/our-insights/ai-for-it-modernization-faster-cheaper-and-better
- https://www.edgeverve.com/ai-next/
- https://www.edgeverve.com/ai-next/case-studies/unparalleled-accuracy-delivers-stellar-business-outcomes/
