About the Company

The customer is a young, quickly growing US-based startup that offers AI-driven trucking logistics solutions to help its customers enhance fleet operations. The company currently operates in the United States, Canada and Mexico, and serves a fleet of 60 trucks across its customers.

The Problem

The distance matrix API the client had been using to calculate distances and ETAs for customer fleets was a bad fit for their needs. They faced two problems:

  • Excessive cost
    They were making heavy and frequent use of the API — to the order of millions of calls and tens of millions of distance matrix elements each month. With the API’s fixed pricing model, this was an expensive affair for the startup. 
  • Future threat
    Inflexible pricing posed a significant risk for such an early-stage company with unpredictable growth and usage patterns. If they were to acquire more customers or have a few months of erratically high usage, costs would skyrocket instantly.

With it being clear that this API was ill-suited to their business needs, The client began the search for an alternative distance matrix API. Their criteria included:

  1. Cost efficiency
  2. Cost predictability
  3. Room for operational growth
  4. API response time

It wasn’t long before they found NextBillion.ai.

The Solution

When the client approached us, it was immediately apparent that NextBillion.ai’s Distance Matrix API aligned quite well with their requirements. Here’s what made the difference:

  • Scalability
    Most APIs offer the industry-standard 25×25 matrix size. Ours, on the other hand, supports matrices of up to 5,000×5,000 elements, enabling them to calculate ETAs and distances between 5,000 origins and 5,000 destinations in a single call! This boosted their confidence in our ability to scale up alongside them.
  • Truck profiles
    Unlike their existing solution, NextBillion.ai’s Distance Matrix API has truck profiles, allowing for more finely tuned and optimized truck-specific routing. Our system accounts for variables like truck dimensions, weight and type of cargo for more efficient and regulation-compliant routes.
  • Customized pricing
    One of the most important factors in the client’s decision was our flexibility in building a customized pricing quote that would suit them, given the expected volume of API calls. We tailored an asset-based pricing model that let them decide how many trucks would be used each month, helping accurately predict costs. 
  • Low latency
    With the large number of API calls being made and the scope for rapid business expansion in the short term, raw speed was important to the customer. NextBillion.ai’s low-latency Distance Matrix API ensured quick responses to keep up with time-sensitive use cases and future scaling requirements.
  • Ease of integration
    Our APIs are easy to implement, and they play nice with other tech systems. This meant that the client would not need to overhaul their existing infrastructure or invest excessive resources to get our solution running. With just a few lines of code, they were up and running in no time. 

After a brief testing period, the company was keen to move NextBillion.ai’s Distance Matrix API into their production environment. The solution was seamlessly integrated into their stack with the help of our support team, who walked the client through every step of the process and aided adoption of the API.

The Outcome

The transition to NextBillion.ai’s solution was a resounding success. With our Distance Matrix API, the client:

  • Benefited from a predictable and sustainable cost structure, gained greater control over their expenses and achieved a 30% reduction in API costs.
  • Has already grown their operations and are well positioned to sustainably expand even further without concern for evolving business requirements.
  • Enjoyed a significant enhancement in API response times, enhancing real-time decision-making capabilities for their customers’ trucking operations.

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