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Understand cost, navigate tariffs.
Drive deeper intelligence into product design cycles.
Scaled PCFs and reduction insights.
Determine your full supply chain and its cost.
Baseline your footprint and decarbonize.
Building Product Intelligence.
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Oct 2025
We're brining the power of Muir's models to the masses. Product teams waste weeks building custom cost models, managing sourcing decisions and iterating on design decisions, only to repeat the process for every new line or supplier. Now with Muir's database you can autonomously generate a model for any product, for free in minutes.
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We're launching a public models database—a searchable collection of pre-built analytical tools that calculate supply chain costs, carbon footprints, and trade risks. A "models database" in this context means a library of ready-made calculations that answer questions like "What does this aluminum part cost if I source it from Vietnam instead of China?" or "How much CO2 does my product generate across its entire supply chain?"
Even better, you can add to it! Check it out yourself.
https://models.muir.ai/
Think of it like having a growing library where the collective group is building thousands of common supply chain scenarios. Instead of wondering the impact or strategy behind a particualr product, you can pull up a Muir model that already incorporates regional pricing data, emission factors, and tariff rates.
The database contains thousands of calculation frameworks covering three areas: cost, carbon, and trade risk. Each model includes documentation about where the data comes from, how the calculations work, and when it was last updated.
We've built cost models for over 500 materials and components, broken down by manufacturing region. These aren't just raw material prices—they include processing costs, typical order minimums, and logistics considerations.
For example, the aluminum extrusion model shows different cost structures for Chinese, German, and Mexican suppliers:
Most carbon tools stop at your direct suppliers, but that's where the story just starts getting interesting. The majority of a product's emissions often happen further back—at the raw material stage or in intermediate processing. Our models trace emissions through multiple supplier tiers, from the factory that assembles your product all the way back to the mine that extracted the raw ore.
When you're evaluating a steel component, you see emissions from the stamping facility, the steel mill, and the iron ore mining operation. This matters because a steel part from a coal-powered Chinese mill has a completely different carbon profile than the same part from a hydroelectric-powered Norwegian mill.
Trade policies change constantly, and keeping track of duty rates across different product categories and countries is nearly impossible without dedicated help. The database includes current tariff rates for thousands of product categories and major trade corridors. You can quickly compare what a component costs when sourced from different countries after accounting for import duties, and you can model scenarios for potential policy changes.
Every model goes through a review process where we verify data sources, test calculations against known examples, and document any assumptions. We keep complete version history so you can see exactly when a model was updated and what changed. This transparency helps you decide whether a model fits your specific situation and gives you confidence when presenting results to stakeholders.
People use the models database to answer complex questions that would otherwise require days or weeks of custom analysis. The pre-built frameworks dramatically cut the time from question to answer.
Product designers can evaluate material swaps and process changes in real-time instead of waiting for procurement to gather quotes. When you're deciding between injection-molded plastic and die-cast aluminum for a housing, you can instantly see how that choice affects unit costs at different production volumes. This enables smarter design decisions early in development when changes are still easy and inexpensive to make.
Finding which parts of your supply chain contribute most to your carbon footprint means tracing emissions through multiple tiers of suppliers. The database lets you map your bill of materials to emission factors at each production stage, automatically calculating your Scope 3 footprint and highlighting the biggest contributors. You might discover that 60% of your product's emissions come from a single raw material—information that tells you exactly where to focus your reduction efforts.
When geopolitical tensions or natural disasters threaten a key supply region, you need to quickly evaluate backup options. The database enables rapid "what-if" analysis where you can model the cost, carbon, and lead time implications of shifting production to different countries. This helps you build resilient supply chains by understanding your alternatives before a disruption forces your hand.
We've designed multiple ways to access the database depending on how you work. All methods connect to the same underlying data, so you get consistent results whether you're browsing in a web app or pulling data through an API.
The public tier provides free access to core cost and carbon models with monthly updates and standard query limits suitable for individual users and small teams. Enterprise plans add advanced models, weekly updates, higher API limits, priority support, and options for private cloud deployment. Organizations with strict data security requirements can also license the database for on-premises installation.
Most platforms require you to build your own analytical models using their data sources, which means significant upfront work before you can answer even basic questions. Muir AI provides thousands of pre-configured models you can use immediately, then customize if needed. This dramatically reduces time-to-insight, especially for teams without dedicated data science resources.
Generic emission factors that treat all "steel" or "plastic" the same miss significant variations based on production methods and energy sources. Our models distinguish between different grades, processing techniques, and geographic origins. Steel from a coal-powered Chinese mill has a very different carbon profile than steel from a hydroelectric-powered Norwegian mill—and that level of detail enables more accurate footprinting and better identification of reduction opportunities.
Sustainability and procurement teams often work in parallel, optimizing for different objectives without clear visibility into the trade-offs they're making. The database automatically shows both cost and carbon implications of every decision, enabling you to find solutions that improve both metrics or make informed choices when trade-offs are necessary.
We're continuously expanding the database with new model types and data sources based on user feedback and emerging supply chain challenges.
We're adding models that calculate water consumption and circularity scores alongside cost and carbon metrics. Water models will account for both direct water use in manufacturing and the water stress levels of production regions, helping you identify products that pose water-related risks. Circularity models will evaluate how easily products can be disassembled, what percentage of materials are recyclable, and the availability of recycling infrastructure in target markets.
Every quarter, our research team conducts systematic reviews of existing models to verify that underlying data sources remain current and calculation methods reflect best practices. We prioritize based on usage frequency and recent market changes—so models for materials affected by new regulations or significant price movements get reviewed first.
The models database represents our commitment to making supply chain intelligence accessible and actionable for organizations of all sizes.
Want to see how the models database applies to your specific products and supply chain? Schedule a personalized demo where we'll walk through your bill of materials, show you relevant models, and discuss how Muir AI can support your cost and sustainability goals.
Your specific product information remains completely private and is never shared with other users or incorporated into public models. The database contains generalized industry models based on anonymized data and public sources—not individual company information. When you apply models to your products, all calculations and results stay within your account with enterprise-grade security.
Enterprise plans include options for private cloud deployment in AWS, Azure, or Google Cloud environments you control, as well as on-premises installations for organizations with strict data residency requirements. Private deployments give you complete control over data location and access while still receiving regular model updates from Muir AI.
The public tier provides free access to core cost and carbon models covering common materials and components, with monthly data updates and standard API rate limits suitable for individual users. Enterprise plans add advanced models for water and circularity, weekly data updates, higher API limits, priority support, custom model development, and deployment flexibility.
Yes, we actively encourage community contributions that improve the database's accuracy and coverage. You can submit updated emission factors, regional cost data, or entirely new models through our contribution portal. All submissions undergo validation by our research team before integration—we verify data sources, test calculations, and ensure documentation meets our standards.
Public tier users receive monthly updates to cost and tariff models. Enterprise customers get weekly updates, and critical changes like major tariff announcements or significant commodity price movements trigger immediate updates across all tiers. Each model displays its last update date and data source vintage, so you always know how current your analysis is.
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