MEC x UiPath x Peak
Optimize every quote. Unlock margin at scale.
Hey, MEC.
Pricing is now one of the biggest levers left to unlock margin and growth across your business. With thousands of engineered-to-order quotes, deeply embedded OEM relationships, and a highly distributed manufacturing footprint, MEC’s pricing challenge isn’t a lack of data, but turning complexity into consistent, repeatable decisions.
MBX, value-based pricing and supply chain productivity will drive your next phase of margin expansion and deleveraging.
Why price optimization, and why now?
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Huge financial impact
Small gains in win rate and realized price drive $10–20m+ in incremental margin at MEC’s scale
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Handle capacity constraints
AI prioritizes RFQs so estimating teams focus on high-probability, high-value work instead of low-return quotes
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Stop leaving money on the table
Static pricing ignores customer behavior and competitive dynamics, causing lost deals on some quotes and margin leakage on others
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Treat each quote differently
AI learns from part, process, and commercial attributes to optimize pricing at the individual quote level, not averages
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Your data is ready
APEX and Paperless Parts create the clean, structured data foundation required for advanced pricing models to work at scale
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AI with control and governance
Pricing recommendations respect margin floors, contracts, and approval rules, ensuring consistency across plants
How do we do this?
Achieve better win-rate and better margin by dynamically optimizing pricing of every quote using AI.
Three key areas of optimization unlocked for MEC…
As soon as a quote is recieved, understand how likely you are to win it so estimators can prioritize their workload and win more
When finalizing the price for each part and the overall quote, leverage a powerful set of AI models to find the perfect price to win the deal whilst maximizing margin
Automatically scan existing agreements, performance against those agreements, and flag when re-quoting should be triggered to unlock further revenue and margin
Every quote is different. And optimizable.
While each RFQ has a unique identifier, the components that actually determine price and win probability are highly repeatable. MEC’s quotes share stable signals across material, geometry, manufacturing route, cost structure, and commercial context. Even when the part itself has never been quoted before.
Peak’s pricing models learn from this rich “part signature” data, representing each quote as a combination of CAD-derived features, process steps, and commercial constraints. Using similarity modelling, the system identifies comparable historical jobs and predicts how changes in price will impact both win probability and margin for that specific quote.
This allows MEC to optimize pricing at the individual quote level, balancing win rate and profitability within defined guardrails, rather than relying on cost-plus formulas, static bands, or SKU-based averages that can’t reflect real market behavior.
Where do we fit in your world?
WATCH: Agentic Commercial Pricing in action
We've got a proven track record
Delivering results for Heidelberg Materials, Nissan, and Hain Celestial
Heidelberg Materials x Peak x UiPath
Learn how Heidelberg Materials’ UK division are saving thousands of hours annually, optimizing margin and improving conversion rates.
Any questions?
I’m Chris, VP Strategy & Partnerships at Peak, a UiPath company. We know that MEC has always been at the forefront of innovation with UiPath — now let’s turn quoting into your next big growth lever. Get in touch with me to learn more about what’s possible.