Suppliers Singapore Nextbillion.ai
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Nextbillion.ai

Enabling Enterprise AI Mapping solutions for the world
Singapore
Marina South
2019
Private
< $10m
11 - 50
Open website
NextBillion AI believes centralized mapping technology is a thing of the past. One map doesn't fit all. Every customer, use case, geography is different, and at Nextbillion AI we build custom mapping API's for enterprises in a way that’s never been done before. Decentralized, modular, custom map stack for hyperlocal business. They provide enterprises with location tools and API's that help them adopt an AI-first approach while solving all their map-related business issues
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Provides mapverse Data on the AI Platform, and Customizable APIs and SDKs. They power complex mapping applications within last-mile delivery, telematics, food delivery, ride-hail. The solution is customizable to be hyper-local and pinpoint accurate for difficult to solve enterprise use cases.
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Nextbillion.ai is a provider of Industrial IoT infrastructure as a service (iaas), and application infrastructure and middleware technologies, and also active in the transportation industries.
Technologies
Infrastructure as a Service (IaaS)
Cloud Computing
Application Infrastructure & Middleware
API Integration & Management
Use Cases
Transportation Simulation
Functions
Logistics & Transportation
Industries
Transportation
Services
Software Design & Engineering Services
Nextbillion.ai’s Technology Stack maps Nextbillion.ai’s participation in the infrastructure as a service (iaas), and application infrastructure and middleware IoT technology stack.
  • Application Layer
  • Functional Applications
  • Cloud Layer
  • Platform as a Service
    Infrastructure as a Service
  • Edge Layer
  • Automation & Control
    Processors & Edge Intelligence
    Actuators
    Sensors
  • Devices Layer
  • Robots
    Drones
    Wearables
  • Supporting Technologies
  • Analytics & Modeling
    Application Infrastructure & Middleware
    Cybersecurity & Privacy
    Networks & Connectivity
Technological Capability
None
Minor
Moderate
Strong
Number of Case Studies4
Grassdoor Boosts Efficiency and Cuts Costs with NextBillion.ai’s Distance Matrix API
Grassdoor's primary challenge was to calculate accurate ETAs and optimize routes for last-mile and on-demand deliveries. The company needed a Distance Matrix API that could handle large API call volumes at scale, run at high throughput and low latency, and be cost-effective. The existing Distance Matrix APIs in the market had limitations, such as a matrix size limited to 25*25 elements, which was insufficient for optimizing a large number of deliveries for Grassdoor's large-scale operations. The cost of these existing APIs was also a concern as they proved expensive and the problem worsened as Grassdoor scaled up. The company was also looking for ways to improve operational efficiency in terms of increased throughput and reduced latency as they scaled.
AI Company Builds Country Scale Maps in 3 Months: A Case Study
A leading AI cloud computing company was faced with the challenge of creating a large scale, end-to-end mapping solution for the entire UAE within a span of three months. The company needed to build high precision, country scale maps with rapid refresh rates, a task that is both expensive and extensive. The process involved building a map at a UAE level, adding 50+ custom attributes, performing quality checks and conflict resolution, and constantly maintaining and refreshing map data. The company also needed to derive map data intelligence from multiple imagery sources, which was a time-consuming process. The data structures used by different routing and navigation engines like OSRM and others vary by routing engine type. The client needed map data that could easily integrate with their existing routing and navigation engines.
Enhancing Delivery Efficiency with Custom Mapping Solution: A Case Study on a Top US-Based Food Delivery Company
The leading food delivery company in the US was facing challenges in keeping up with the growing demand and customer expectations. The company was striving to meet its ambitious growth goals without compromising on the quality of service. The existing mapping solutions were rigid and did not cater to the company's specific needs. The company required a more tailored mapping solution that would help them achieve more efficient and on-time deliveries, provide more accurate Estimated Time of Arrivals (ETAs), and reduce costs on Maps APIs.
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