Uber for freight
· run by AI
In car shipping today, middlemen — dispatchers and brokers — take a cut of every deal. We're replacing them with AI, step by step, across the whole chain, and keeping that markup for ourselves. And we can make the service cheaper at the same time: AI slashes the cost base and raises quality to a level no human can match.
We move in stages: first we collect orders automatically, then post them ourselves to the existing carrier marketplaces; next we remove the broker, then the dispatcher, and deal directly with trucking companies and owner-operators. An AI named Sarah runs the whole process around the clock — for the shipper, driver and receiver it feels like Uber for freight. Car shipping (a $10.5B market) is only the start: next come box trucks, then semis, then all other freight. The entire US freight market is $900B+. The goal: become the #1 platform — 5% → 25% → 60% of the market. At the start the founder runs it solo; with the first revenue we build the team — thanks to AI, $100M in annual revenue is reachable with 50 people or fewer. This will happen inevitably — the only question is who does it first.
Within a few years, the middleman who lives on phone calls will be gone. The only question — will you take the market, or will someone take yours.
AI is already cheaper than a human
Dispatchers and brokers on the phone are expensive. AI does the same work 24/7 for pennies — and better.
We've seen this before
Travel agents, video rental, taxi dispatch — middlemen vanished the moment a platform arrived. Freight is next.
It's inevitable
The question isn't 'if' — it's 'who builds it first'. If not us, then others. And they'll take your customers.
Decide too late and another platform takes your customers — and your margin disappears. Invest in QuickShip now and you're on the side that takes the market, not the one that loses it.
Sarah collects orders automatically
A call, a web request or an ad → the AI answers, prices the move and takes a deposit.
The tech is nearly free (the first working version cost ~$5). Capital only pays for ads (customer acquisition) and founder / staff salary. The business is profitable even on a small investment — it fits a small investor too, from $150K.
The broker and dispatcher disappear as a class
The way Uber connected rider and driver directly, QuickShip connects shipper, driver and receiver — with no middleman layer. One interface, AI prices the move, matching is automatic, the money is held on the platform until delivery.
No broker middleman
The shipper, driver or receiver starts the deal themselves — whoever starts it pays a transparent platform fee.
No manual dispatch
Uber-style AI matching: drivers online with geolocation, the load goes straight to the right ones — no calls, no phone haggling.
Trust at the platform level
The platform holds the payment and releases it to the carrier only after delivery is confirmed; plus GPS tracking and ratings — you trust the platform, not a broker.
Cars first, then everything else
A layer that's costly and universally hated
Middlemen take 15–40%
The broker takes 10–35% on top, the dispatcher another 10–12% (often more) off the driver. Pure markup for phone calls.
Lowball, then hike
The #1 complaint of 2026: quote a low price to win the booking, then add $200–800.
Ghost carriers
No-show pickups of 24–72h are 'normal'; delays stretch into weeks.
Phone-tag spam
'Free quote' resells your contact to dozens of brokers — calls for days.
Everyone hates the layer
Customers, drivers and dispatchers — each juggles 4–7 systems and hates the middleman.
Manual labor
Payroll eats ≈79% of a broker's gross profit; 10–30 manual steps per order.
A small start — a huge prize
The US car-shipping market, 10M+ cars a year. We start here.
The entire US freight market. The same middleman-free mechanism — across all freight.
of carriers run a single truck; 91.5% run ≤10. Ripe for consolidation.
Auto market per IBISWorld; US freight per ATA (industry revenue). Estimates.
We fill market after market — earnings add up
Each circle is a freight market, sized by its volume. We take ~60% of the market (the goal is to become the leader), our earnings are shown above each circle. Once one market is filled we move to the next; platform earnings add up at the top.
Market sizes and shares are targets, not a guarantee. Car shipping is the first market; the same middleman-free AI mechanism carries over to box trucks, semis and all other freight.
Full automation instead of human middlemen
Sarah
A voice AI agent: warm, multilingual. Walks the customer one question at a time, prices the move, closes on a deposit — 24/7, no salary. Replaces the sales desk.
A team of AI agents
An AI director assigns tasks to manager agents (operations, finance, tech, marketing…), who pass them to worker agents. Replaces dispatch, sales, claims handling and billing. ~$180/mo vs $5–8K per person.
Call → booking in a minute
Sarah runs the conversation, prices the move and closes on a deposit — no human, 24/7, in the customer's language.
Built by AI — a new kind of startup math
A typical logistics startup raises $5–50M and hires 30–80 people. QuickShip is built and run by AI — for the cost of compute and a single salary.
Three stages — from broker to platform
Honestly: what's live now, what's planned for the year, and where we're headed long-term. The AI broker isn't the end product — it's the engine that funds the platform.
AI broker — the cash engine
Sarah books a move and takes a deposit; an AI director runs the company. It already works at ~$5 of cost. This is the tool that funds the platform with cash and data.
Full AI broker
Ads → website → Sarah closes the deal → the AI dispatcher posts orders to the marketplaces. Growth from 100 to 500 shipments a month, ~$180 net on each.
An Uber-style platform — no brokers or dispatchers
An app connects shipper, driver and receiver directly. Automatic matching, money held until delivery, GPS, ratings. A platform fee of 8–15% vs the 20–40% the middlemen take.
The entire freight market
The same mechanism carries over to everything box trucks and semis haul: local cargo, full and partial truckloads, general freight — the $900B+ US market. Brokers and dispatchers leave the whole chain, not just car shipping.
From first version to market leadership — and on to all freight
A 10-year plan for the investor: each link in the chain is replaced in turn (dispatchers → brokers → fleets), market share grows 1% → 5% → 25% → 60%, then the whole freight market.
AI broker — the engine
Sarah + a customer app, first paying customers. The job: prove the model works and start bringing in cash and data.
Apps for customers, drivers and fleets
Uber-style, with live vehicle tracking; fleets pay a $30–100 per-truck monthly subscription (paying customers). The driver app is free — it fuels growth.
Dispatcher portal
With our tool a dispatcher runs 30–50 trucks instead of 5–15 — their income grows 2–4×. We automate the work and take 5–10% of their earnings.
Broker portal + our own carrier license
We get our own carrier license and surety bond; we take 10–20% of broker earnings. We begin to dominate the market.
60% of the US car-shipping market
Most car shipping flows through the platform; the whole chain's earnings (customer → dispatcher → broker → fleet) stay with us.
$900B+ freight, ready for driverless trucks
The same mechanism on full and partial truckloads and local freight; orchestrating driverless trucks and robot loaders that legacy players aren't built for.
Years and shares are target guideposts, not a guarantee. The seed round funds the first stage (years 0–1); the rest comes from growth and the next round (Series A).
An edge rivals can't copy
Rivals can't copy this
To copy a near-zero-staff model, a broker would have to shut its own 30–80-person call center and lay everyone off. They won't.
We enter from the bottom
Automation lets us price below the old players. They don't fight for the cheap segment — we enter from the bottom and move up.
Why not another Convoy
Convoy (raised $3.8B) burned cash chasing growth: it moved freight at a loss, made no profit per deal, and ran a thin margin on turnover. We're the opposite: profit on every shipment, an 18% fee at near-zero cost (the company is run by AI). We don't take freight onto our balance sheet — so there's no capital or risk to finance.
The data flywheel
Each loop lowers cost and improves matching and pricing — and lowers cost again.
Software-style margins on every shipment
Our revenue is only the platform fee, not the full price of the move. The carrier's pay passes straight through and isn't our cost. That's why the margin is ~86%. And our 18% take is deliberately below what middlemen charge today (broker 10–35% + dispatcher 10–12%): that gap is enough to make it cheaper for the customer, better for the carrier, and still profitable for us. Room to take more than 18% is upside we keep off the plan.
At first a customer brings in only a little more than it costs to win them (one-off consumer orders), but it grows to ≥3:1 through free traffic and repeat orders from businesses and dealers. The acquisition cost shown is for paid ads — honestly.
3 years: the path to profit
A bottom-up forecast, no unrealistic hockey-stick: everything is 'number of shipments × fee'. Profitable by year 2; founder and staff salaries are included in costs.
Switch scenarios — the table and chart recompute. Volumes are tied to real benchmarks (a small auto broker ≈ 100–500 cars/mo; market leader Montway ~250,000/yr).
| Y1 | Y2 | Y3 | |
|---|---|---|---|
| Cars shipped | 1,500 | 6,000 | 14,000 |
| ≈ trailers (6 cars) | ≈250 | ≈1,000 | ≈2,330 |
| Revenue (18% fee) | $270K | $1.08M | $2.52M |
| Gross profit (~86%) | $232K | $929K | $2.17M |
| Costs | $380K | $670K | $1.10M |
| Operating profit (EBITDA) | −$148K | +$259K | +$1.07M |
Driver — cars × $180 fee. Profitable in year 2.
What the costs are
What the plan is made of
The tech is nearly free — money goes to two levers: ads (we know the cost to win one car) and 1–2 developers to finish the platform faster. Here's how it adds up across the three scenarios.
We pay less to win a customer than we earn from them ($180). Repeat orders (dealers, B2B) and organic traffic lower the cost over time — ad payback is under one shipment.
What we build
The revenue version (Sarah + booking + payment) is ~80% done. The full platform — ≈12–16 person-months:
- Customer app6–8 wk
- Driver app5–7 wk
- Fleet dashboard5–6 wk
- Dispatcher / broker portal11–14 wk
- QuickShip brain + AI agents8–10 wk
- Integrations, backend, security11–14 wk
How many people
- Build1–3 people (founder + 0–2 developers, all AI-assisted)
- Run & maintain3–5 people at $1–2.5M revenue — AI agents run operations
- At scale≤10 people at $10M · ≤50 at $100M annual revenue
The idea, proven for ~$5
No revenue yet — but the AI-run company already runs itself at near-zero cost. All that's left is turning on paid ads and the first enquiries.
AI director live
A self-running AI director: it starts on a daily schedule and sends summaries to Telegram.
Sarah deployed
The voice AI agent (v6.5) is live in production and stays on script.
Processes automated
Booking, payment and posting orders to the marketplaces — all happens automatically.
Brand + domain
QuickShip Auto Transport, quickshipauto.net, Telegram bot.
Payments chosen
Soar Payments — a payment provider specialized in auto transport.
First paying customer
The last step before launch — turn on paid ads and the first commercial enquiries.
AI is entering logistics — and getting funded
HappyRobot
$44M raised (2025), ~$500M company valuation — voice AI for brokers. The well-known fund a16z came in even earlier.
FleetWorks
$17M raised (2025); 10,000+ carriers in ~6 months.
Vooma
$16.6M raised; revenue grew 12.5× — AI agents for brokers.
Uber Freight
~$5.1B revenue, reached breakeven in late 2025; 30+ AI agents.
In 2025 AI took ~53% of global and ~64% of US venture funding. Mature voice AI + costly broker labor = the turning point. QuickShip enters through the segment customers dislike most — and goes after the whole freight market.
Three ways in — for any check
The business is profitable — so any check size works. Minimal for a small investor, aggressive for fast market capture.
| Minimal | Medium | Aggressive | |
|---|---|---|---|
| Raise | $150K | $500K | $1.5M |
| Founder / staff salary | $5K/mo | $9K/mo | $12.5K/mo |
| Ad budget | ~$7K/mo | ~$17K/mo | ~$28K/mo |
| Hires | 0 | +1 | +2 |
| Valuation cap | $750K | $2.25M | $6M |
| Investor ownership | ~20% | ~22% | ~25% |
| Cars/mo by mo 24 | ~300/mo | ~600/mo | ~1,000/mo |
| Revenue/yr | ~$1.26M | ~$2.52M | ~$4.32M |
| Cash-flow positive | ~mo 14 | ~mo 16 | ~mo 18 |
| Strategy | ultra-lean: prove the engine | balanced growth | land-grab → next round |
Where the money goes (any option)
~80% of any round is ads (customer acquisition) and founder / staff salary. The tech is pennies.
What the investor gets
A ~20–25% stake per round: the bigger the check, the bigger the slice — a larger investor funds a more ambitious plan and gets a larger share of the company.
A small check ($150K for ~20%) — a stake in a profitable company at minimal risk. A large one ($1.5M for ~25%) — the path to the next round (Series A) and a return of several times the money. A live example: HappyRobot — the fund a16z came in early, and about a year later the company was valued at ~$500M.
Figures illustrative, not an offer. Round size and terms at the founder's discretion.
"Ship anything" = QuickShip
Cars are the start. The goal — become to freight what Uber became to taxis: the default platform, with no brokers or dispatchers. Market share: 1% → 5% → 25% → 60%+.
Figures are from the internal model and public sources; estimates, not an offer. The project has no revenue yet. Stages 3–4 are the long-term goal, not what's being built right now.