DPW New York: How Valdera's AI Reimagines Sourcing Workflows

On 3-4 June, some of procurement's most influential leaders and innovators gathered for DPW New York 2026, the US instalment of one of the largest procurement and supply chain technology events on the calendar. 

The event was delivered under the 'RECODE' theme, focused on the shift from AI adoption to meaningful and strategic execution. 

Over the next decade AI adoption and innovation will continue at pace, with competitive advantage coming not from whether or how companies adopt AI, but how the redesign their operating models and organisational structures around it.

For procurement professionals, this shift means rethinking decision making, harnessing new technologies and building a AI blueprint for the future. 

Procurement Magazine discussed this and more with Dheev Arulmani, Co-founder and COO at Valdera, a sourcing platform for chemicals and raw materials that empowers businesses to build the future of sustainable and branded products. 

Dheev told how and why the company was founded, how it helps tackle persistent challenges in direct materials procurement and why the business takes a vertical approach to AI in procurement. 

What were you seeing in the industry that made Valdera a real prospect?

The chemical industry is absolutely ginormous. It feeds into literally everything in this room – everything that we touch, but it's been extremely antiquated in the way that buyers interact with suppliers. 

We thought there has to be a way to use modern tech, data science, AI to really bring this to the 21st century. 

It's been operating in such an antiquated way for so long – hundreds of thousands of suppliers on one side, thousands and thousands of buyers on the other side, and a lot of opacity in the market that prevents those relationships from happening effectively.

How does Valdera work in that context and in terms of those challenges? 

Valdera is an AI operating system built specifically for chemical and raw material procurement and designed to digitise the entire workflow of a category manager that's owning one of these categories. 

Essentially, we ingest their total raw material spend, creating a control tower of all of the materials they're buying, their suppliers, their specifications, creating that repository, and then applying a market intelligence layer on top of it. 

This allows us to say what's actually happening in the external world, see where new suppliers are entering and what's happening to specific trade prices of specific materials. 

This allows us to identify gaps relative to your current spend on specific materials and, where you see gaps, to actually enable you to take action on that, going to market, doing supplier discovery, routing, quoting, evaluating the logistics tariffs all the way through qualification of a new material.

Why have these challenges persisted in direct material procurement?

When you think about the world of procurement technology, especially on the indirect side, there's so much fantastic tech out there. 

With the direct side, if you think about finished goods like pipes, fittings or pumps, it’s a very different world to that of chemicals and raw materials. 

You have infinite permutations of specifications, different chemical structures, properties and regulatory requirements depending on whether something is going to pharma, industrials, personal care or more. 

It means you really have to build the data architecture, the AI models and everything else from the ground up for this industry.

What primary outcomes do businesses see when working with you?

If you think about where we're driving value, it really comes down to how we can have 10 to 50 times a category manager's capability in the chemicals and raw materials space. 

That ultimately comes down to questions like where are we able to drive bottom-line cost savings, whether that's through market intelligence or qualifying a new supplier? 

It’s also about how we are able to drive innovation as early in the R&D process, a new product development cycle and also find who's capable of producing what? 

Sustainability is a big part of this, particularly finding offsets to very specialty materials.

What is Valdera’s core philosophy when it comes to AI in the procurement space?

If you think about AI in the procurement technology landscape, everybody is taking a horizontal approach, which works extremely well in the indirect side, but fails when you get into specialty materials like chemicals, ingredients and so on. 

A big part of our vision is how to flip the script and take a verticalised AI approach for what is a very targeted industry.

We're deeply focused on the chemical and raw material space in a verticalised way by trying to digitise everything, from ingesting your spend into a category manager, applying that market intelligence layer, doing the supplier discovery and sourcing of the material all the way through qualification, negotiation and onboarding that supplier. 

What do the next three to five years hold for the business?

Valdera’s evolution will be around how we move from enabling category managers to actually directly owning and managing spend as well. 

Many of our customers want us to take a big chunk of their spend and agentically automate a large part of that workflow all the way from tracking what's happening internally, applying that external market data and then, where we see gaps, actually running those sourcing events and driving action on that. 

That’s how we see Valdera is how do we actually continue to automate and digitise that entire workflow in a way that we can almost be a managed operating model of a chunk of spend.