About the Company

Everest AI 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

At the time, Everest AI had been using the Google Distance Matrix API to calculate distances and ETAs for customer fleets. However, this proved to be a bad fit. Google’s rigid pricing model caused two problems:

  • Excessive cost
    Everest AI was 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 Google’s fixed pricing, 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 Google’s Distance Matrix API was ill-suited to their business needs, Everest AI began the search for alternative solutions. 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 Everest AI 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
    Google’s API came with the industry-standard 25×25 matrix size. Ours, on the other, supports matrices of up to 5,000×5,000 elements, enabling Everest AI 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 Google, 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 Everest AI’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 Everest AI. 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, Everest AI 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 from Google to NextBillion.ai was a resounding success. With our Distance Matrix API, Everest AI:

  • Benefited from a predictable and sustainable cost structure, gained greater control over their expenses and achieved a 30% reduction in API costs.
  • Have 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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