Chemical sourcing is rarely straightforward. Specifications are highly technical, supplier markets are fragmented, and category managers are often balancing thousands of materials at once.
In this Provider of the Week episodeof the ProcureTech Insider podcast, I talk with Dheev Arulmani, COO and co-founder of Valdera, about how the company is applying AI and proprietary chemical data to modernize sourcing workflows for raw materials and specialty chemicals.
What does Valdera do today, and how has the solution evolved over time?
“Valdera is an AI sourcing platform built from the ground up, specifically for chemical and raw material procurement teams.
What we do is partner directly with procurement organizations of manufacturers to help digitize the whole end-to-end sourcing workflow of these very specialty materials. So we manage everything from ingesting very specific details and specifications of the material through supplier discovery, the routing and RFQ process, the market intelligence, and the qualification and onboarding of a new supplier.
When we started the business about five years ago, Valdera was very much a data science and machine learning company. We tried to build and amass the largest data set of chemical specifications in the world.
What we've been able to do is apply this AI layer on top of this huge proprietary data set of chemical specs that we've built to empower some of that data to be that much more impactful.”
What differentiates Valdera from other procurement technology providers?
“Chemicals are a whole different beast.
There are infinite permutations of specifications, different chemical structures, different properties, different regulatory requirements depending on the industry, and different logistics requirements.
What we realized is that you have to build the data infrastructure, the AI, from the ground up specific to this industry. And we're the only ones in this space that have built that technology, the workflow, the data, everything to partner directly with category managers of these categories.”
How are procurement roles evolving in the chemical and raw materials space?
“A lot of category managers historically have had deep chemicals knowledge. They've been PhDs, they have chemistry backgrounds.
What this is evolving to is a very different type of profile of the next generation of folks that might not have the technical knowledge, but have a lot of the process capabilities and the ability to go drive impact.
A big part of what we're trying to do is enable technology to bridge that gap between the technical knowledge of these sophisticated materials and the capabilities of these teams.”
How does AI help procurement generalists operate in a highly technical category?
“A lot of the AI agents and tools and the capabilities that we've built are meant to help folks understand the technicalities of a lot of these materials in a way that historically you needed a PhD to do.
We're trying to ingest all of that information. We're trying to use agents to compare the specifications, the certifications, the packaging in a way that historically was done by comparing two spec sheets side by side.”
What recent product capabilities are you most excited about?
“What we've recently launched is an AI layer that will ingest the entire spend that a category manager owns, proactively use our proprietary data and what we're seeing in the market, in addition to public data like trade data, to say, ‘Hey, look, the market is moving rapidly in this material. You have a contract that's coming up for renewal. By the way, you're a single source. This is a material that you should be focused on.’
We've also built agents to ingest spec sheets, estimate tariffs, estimate logistics, automatically give feedback to suppliers, and help negotiate and compare very technical specifications when the quotes come back.”
What business outcomes are customers achieving most consistently?
“The way we think about it is that there are three verticals of impact with an overarching layer of efficiency.
The three layers of impact that we're seeing are cost, risk, and innovation.
On the cost side, it's how do we expand the supplier network and use market intelligence and benchmarking to drive down costs?
On the risk side, a big part of our value prop is, how can we go find offsets in the market, either with the same exact technical specifications or functional offsets?
And then from an innovation perspective, a lot of the work that we're doing is helping partner with R&D and technical organizations to accelerate innovation and bring products to market faster.”
What advice would you give organizations implementing procurement technology?
“Start small, prove the value, and scale.
The customers that have seen the biggest impact the fastest are folks that have said, ‘Hey, look, we're going to move very quickly. We're going to test a very small scope. We're going to validate that value, then scale up.’
That’s the model that we've seen to be most impactful across our entire customer base.”
What’s next for Valdera?
“We want to take Valdera from that sourcing and market intelligence layer and go really vertically deep into category management, market intelligence, should-cost modeling, and really ingrain into that workflow all the way end to end of a category manager's day.
We want to be the platform that they open first thing in the morning to figure out which materials they should be focused on all the way through going to market, qualifying suppliers, and bringing them on.
Where you'll see Valdera evolve is to become the entire end-to-end operating system for a category manager in this space.”
