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Looking Ahead: Using AI to Build Dynamic Cost Models
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Looking Ahead: Using AI to Build Dynamic Cost Models

Provide your email address to download Muir AI's white paper on how the changing supplier and product landscape requires innovative approaches for should-cost analysis.

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Scale Should-Cost Analysis with Muir AI

When talking with customers and partners about Muir’s product should cost capabilities, we are often met with the question, “What’s a climate tech company doing with should cost analysis?” Muir’s technology capabilities allow us to go beyond emissions, to enable customers to truly understand their products.

As you may have seen in some of our previous posts, the technology we have developed at Muir was created to enable our customers  to better understand their products and supply chains, whether they be sustainability professionals, product designers, procurement specialists, or supply chain managers. 

At Muir, we take a holistic view of product intelligence. We want our customers to know the materials being used, where upstream materials might be coming from, the product’s impact on the environment, and what is driving its cost. This is why we are continuously building new product-level insights for our customers - to fully enable our customers to optimize they products they buy and manufacture. 

We understand that managing cost is most-often at the forefront of every decision a company makes - and without granular product-level cost insights, companies lack the insight to invest in new products or redesign existing ones, they might leave money on the table during supplier negotiations that could be better used elsewhere. This is why historically many companies have used cost-models or performed should-cost analysis - to understand their products and make more informed decisions that extend the life of their products and company. 

But this is getting harder. Products are becoming more and more complex, and it's becoming increasingly difficult to ascertain what is in a product and where its components are coming from, both of which have large impacts on cost models. 

This is why Muir has developed its own Cost Model capabilities in the Muir Platform. We are harnessing the power of advanced AI and deep insights into product materials, manufacturing processes, sourcing locations, and pricing, to create a dynamic solution that enables our customers to rapidly perform should-cost analysis on their products.  

Download our paper, Looking Ahead: Using AI to Build Dynamic Cost Models, to learn more about our approach and reach out to our Muir AI team if you would like to see this technology in action!

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