Some procurement platforms start with transactions. Samsung SDS Caidentia starts where the real leverage begins: the decisions made long before a purchase order is ever issued.
In this Provider of the Week conversation, host Jyothi Hartley speaks with Imran Shaikh, Head of Pre-Sales and Business Development, about how Samsung SDS Caidentia helps manufacturers move procurement upstream by using BOM-driven visibility, AI-embedded cost intelligence, and cross-functional orchestration to reduce late-stage surprises and improve product outcomes.
Below is a Q&A recap of the highlights of their insight-packed conversation:
What does Samsung SDS Caidentia do today, and how has your solution evolved over time?
“Samsung SDS is an AI-powered, design-to-source-to-pay platform built primarily for direct procurement environments and extends all the way into indirect procurement. What makes us unique is that we start where product decisions are made, not where purchase orders are issued, because most procurement technology platforms focus on source-to-pay. We focus on design-to-source first, because the majority of the cost, the risk, the supply complexity is all locked in during design and industrialization, not during transaction procurement.”
How has customer demand shifted in recent years, and how has that shaped your roadmap?
“Customer demand has specifically shifted from automation to resilience. Speed is still important. Our customers want speed. But structured alignment across functions has become far more critical.
Organizations now ask, how do we reduce late-stage surprises? How do we embed cost intelligence earlier in the design process? How do we close feedback loops faster? How do we reduce volatility during launch?
That’s gone more towards cross-functional visibility, proactive quality validation, and supplier collaboration at the design stage. It's all AI-driven impact and change analysis.”
Where does Caidentia sit within the procurement tech ecosystem?
“We sit between PLMs and ERPs as the orchestration layer. PLM manages product definitions. ERPs manage transaction execution. But industrialization, where design becomes manufacturing reality, is often fragmented. That's where we operate.”
What recent capabilities are you most excited about?
“AI-enabled BOM intelligence and agentic decision support. This is not an ‘AI as a chatbot,’ this is not ‘AI as a dashboard,’ but AI embedded within the workflows to simulate cost impact during design changes, identify supplier risk during the item level orchestration, and detect cross-functional misalignment. Predicting those changes, volatility before launch is important. And that's where our key capabilities are really focused.”
What capabilities do long-standing customers rely on most?
“It’s the structured BOM governance. It's not flashy. It's not headline-grabbing. But our customers consistently tell us that having a well-structured and traceable and cross-functional BOM is transformational for them.
A well-structured BOM becomes a strategic asset. In reality, it reduces rework. It reduces misalignment. It enables early manufacturing involvement. All of this prevents firefighting at the launch stage.”
What new or unexpected use cases are you seeing from leading procurement teams?
“Leading procurement teams are embedding cost intelligence and risk simulation directly into the design phase. One emerging use case is AI-powered quotation analysis.
Instead of manually comparing supplier quotes, our AI quotation analyzer evaluates supplier pricing against should-cost models and historical data… and instantly flags anomalies, overpricing patterns, and risk exposure.”
How does your approach connect procurement’s work to broader business goals?
“Procurement often struggles with perception, being seen as a cost control function. But when procurement teams move upstream into production definitions, it becomes a strategic growth function.
Our platform allows procurement to influence product margin before launch, supplier ecosystem resilience, time to market, stability, and compliance readiness at the core level.
When cost, risk, and supply flexibility are visible inside the BOM, decisions improve automatically. And that's where procurement becomes a strategic contributor and not a downstream validator.”
How does Caidentia integrate with existing systems?
“Caidentia is not a rip-and-replace solution. We are an orchestration layer. We integrate with PLMs; we integrate with ERPs. Integration isn't just technical connectivity for Caidentia. It is the contextual synchronization that makes these systems work together.”
What’s one tip to ensure a smooth implementation?
“We always recommend… start with governance clarity before technology configurations.
Define decision rights early. Standardize the BOM structures, align engineering, procurement, and sourcing workflows, and embed your supply collaboration into the design phase.
If the structure is weak, AI will only accelerate confusion. If the structure is strong, AI compounds value.”
What are the biggest opportunities for procurement technology in the next 12 to 24 months?
“That primarily resides around agentic AI. If responsibly deployed… AI agents will not just analyze data, but operate with that data with governance frameworks to do things like sourcing events triggering, simulate cost alternatives, recommend supplier substitutions, and monitor risk signals across tiers.
We are actively working towards enabling our customers to configure and develop AI agents themselves. Our AI agents are not just universal AI agents. Our AI agents are built for manufacturers specifically and uniquely for different manufacturers, too.”
To learn more about Samsung SDS Caidentia, visit their profile page in the AOP Provider Directory.
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