Sirdab X: How AI helped Us Build a Dynamic Pricing Model

At Sirdab, we’ve always believed that logistics pricing shouldn’t be a black box. Yet in the trucking industry, especially across the GCC, pricing remains largely informal, inconsistent, and difficult to scale.

Therefore, we built an AI-powered pricing model that learns from real-world data to generate fair, fast, and dynamic pricing. It’s not perfect yet, but it’s a massive step toward bringing structure to one of the most chaotic parts of the logistics stack.

The challenge: freight rates are broken by default

If you’ve worked in logistics, you know this story too well:

Prices are often calculated manually — over WhatsApp, through word-of-mouth, or based on one dispatcher’s gut feeling. There’s little consistency, and even less transparency.

• Quotes take too long — and often don’t reflect real-time market conditions
• The same route might be priced 30–40% higher depending on the day
• Seasonal spikes, vehicle shortages, and backhaul availability are often missed

This creates friction, slows down deals, and results in poor margins, for both clients and providers.

Our approach: build a model that learns from the market

We worked with over 50 freight providers, including shippers, carriers, and dispatchers, to analyze real freight behavior across different geographies, truck types, and volumes.

Using that, we built a dynamic pricing model powered by machine learning, built to:

• Ingest new data daily: actual trip rates, vehicle availability, and route-specific patterns
• Predict pricing based on distance, historical rates, seasonality, and supply-demand dynamics
• Generate instant quotes through our app, including for remote areas, unusual loads, or off-peak timings

Instead of relying on fixed tables or best guesses, our model adapts in real time.

How it works: logic + data + learning

The model uses a mix of structured inputs (distance, truck type, origin-destination pair) and real-world rate feedback to predict a price that balances:

• Market reality (what carriers will accept)
• Margin protection (based on internal cost benchmarks)
• Speed to quote (pricing a job in seconds, not hours)

We also layer in dynamic rules like:

• Add-ons for remote or high-risk areas
• Need for laborers for loading and unloading
• Layovers & waiting times
• Adjustments based on load urgency or pallet count

And because every trip logged in the system feeds the model, it only gets better over time.

The results: faster quotes, smarter pricing, better margins

✅ 100%+ of standard lanes now priced in under 5 seconds

✅ Improved pricing accuracy for repeat clients and routes

✅ Faster conversion due to reduced back-and-forth on pricing

✅ Higher partner trust, since pricing reflects real supply dynamics

Why this matters

Pricing is one of the most overlooked pain points in logistics — yet it drives everything from customer experience to profitability. With AI, we’re finally giving it the structure it needs.

At Sirdab, we’re not just automating freight — we’re building a learning logistics system that gets smarter with every shipment, every quote, every lane.

Are you a shipper or logistics partner tired of pricing delays and inconsistencies? Let’s talk. Our AI-powered pricing engine might be exactly what your operation needs to scale.

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