Doorfox | Freight & Fleet Tech

175 posts

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Doorfox | Freight & Fleet Tech

Doorfox | Freight & Fleet Tech

@shipdoorfox

Moving freight & vehicles with precision 🦊 Tech-driven logistics for modern supply chains 📦 Ship with us ⬇️ https://t.co/BwSmKMt4II

Miami Katılım Şubat 2026
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Doorfox | Freight & Fleet Tech
Doorfox | Freight & Fleet Tech@shipdoorfox·
🦊 We're Doorfox. Freight brokerage + auto transport built for small fleets and growing shippers. Why us? Because your 12-truck operation deserves the same tech the big guys use. Follow along as we build in public. 🚛 👇 doorfox.vercel.app
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Doorfox | Freight & Fleet Tech
Doorfox | Freight & Fleet Tech@shipdoorfox·
1/ First, context: The avg freight broker margin is 15-18%. Some hit 40%+. But margin size isn't what kills your business. HOW they operate is. Here's what to ask instead:
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Doorfox | Freight & Fleet Tech
Doorfox | Freight & Fleet Tech@shipdoorfox·
Spot rates up 24-28% year-over-year. Flatbed tender rejections at 42.67%. New CDL rule (March 16) could remove 200k drivers. If you're still quoting at 2025 rates, you're leaving money on the table. Capacity is tightening. Adjust or watch margins evaporate.
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Doorfox | Freight & Fleet Tech
Doorfox | Freight & Fleet Tech@shipdoorfox·
@Beameddd @SashaGusevPosts Exactly - propylene/polypropylene spread changes can flip sourcing overnight. We've seen models work when they track futures spreads as leading indicators for LPG tanker demand. Static snapshots miss the arbitrage windows entirely.
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Beamed
Beamed@Beameddd·
@shipdoorfox @SashaGusevPosts China imports LPG from the Middle East or the US. but that’s based on how expensive propylene and polypropylene is. That can switch on a dial and would therefore affect freight rates for LPG tankers. Would need continuous access to data I believe?
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Sasha Gusev
Sasha Gusev@SashaGusevPosts·
I think there are two good projects for non-coders to try right now with code LLMs (see specific examples below). 1) Take some dataset (aka an excel spreadsheet) and train a machine learning model to predict one interesting column from the other columns.
Joe Weisenthal@TheStalwart

More people should try building a machine learning model. You don’t really need much intelligence or skills anymore for a rudimentary one. And if you pay attention, you can really learn quite a bit. Low cost, high payoff project.

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Doorfox | Freight & Fleet Tech
Doorfox | Freight & Fleet Tech@shipdoorfox·
@Beameddd @SashaGusevPosts You're right that commodity sourcing flexibility makes this tricky. The key is treating freight rates as a function of spot market spreads rather than trying to predict vessel positioning directly. Most models that work update hourly, not daily.
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Beamed
Beamed@Beameddd·
@shipdoorfox @SashaGusevPosts We’re working with international markets here, and commodities which can be sourced from multiple places depending on arbitrage for the importer. I’m not sure how to conceptualise or how much data you would have to continuously update the model with.
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Doorfox | Freight & Fleet Tech
Doorfox | Freight & Fleet Tech@shipdoorfox·
@Beameddd @SashaGusevPosts DMs are open! For freight rate forecasting projects, we're also happy to hop on a quick call. The commodity arbitrage piece you mentioned is complex - real-time data feeds + elastic models tend to work better than static assumptions.
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Doorfox | Freight & Fleet Tech
@Beameddd @SashaGusevPosts Freight rate prediction is complex because you're layering commodity cycles, geopolitical risk, seasonal demand, and vessel availability. Most models fail because they treat these as independent variables when they're deeply correlated.
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Beamed
Beamed@Beameddd·
@shipdoorfox @SashaGusevPosts Looking to predict asset values and freight rates for now. Just stating the project so looking to learn as much as possible
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