EndorsedendorsedOngoing

AI-Powered Search Engine App for Automotive Tech Company

Services Covered:

Mobile Application DevelopmentAI and Machine LearningCustom Software Development
Project hero — replace with case study imagery
Industry
Industry

Automotive

Duration
Duration

75 months

Budget
Budget

50K - 199K

Client Size
Start Date

1 May 2020

Team Size
Team Size

1-5 Employees

Engagement Model
Engagement Model

Offshore

Project Capability Score (PCS)

gauge meter
74/100
Good

Project Capability Score (PCS) estimates how capable Xmartlabs is of successfully delivering a project like this, based on its past experience, track record, and ability to handle similar work. Learn more about PCS


Client

Confidential

mapSanta Rosa, United States of America

Project Summary

Xmartlabs developed native iOS and Android apps and ML/NLP features for an automotive technology company’s AI-powered search engine. The team used Java and Swift for mobile, and Python, PyTorch and Scala for ML and backend components. The app has been launched to both app stores and has 15 customers; Xmartlabs continues to maintain environments and add functionality.

Key Challenges

  • Develop native mobile apps for iOS and Android.
  • Implement machine-learning and natural language processing features for an AI-powered search engine to improve automotive technician workflows.

Project Deliverables

  • Native Android app (Java)
  • Native iOS app (Swift)
  • AI-powered search engine with voice and touch command functionality
  • Machine learning and natural language processing components and middleware support
  • Environment maintenance and versioning

Project Solution

Xmartlabs was responsible for native Android and iOS development, using Java for Android and Swift for iOS, and handled coding and versioning for the mobile clients. They also contributed machine-learning and natural language processing work using Python, PyTorch, and Scala. The vendor maintains environments, supports increasing app functionality, and works alongside the client’s middleware team.

Project Outcome

  • Launched the app on both iOS and Android app stores with 15 customers.
  • Most bugs are fixed within a day; systemic issues take up to a week to resolve.
  • Client reports high satisfaction with speed, quality, documentation, and adherence to budget and timelines.

Platforms

  • MobileMobile

Tech Stack

  • PythonPython
  • JavaJava
  • SwiftSwift
  • ScalaScala
  • PytorchPytorch

Client Endorsement

Overall Review Rating

5star5 out of 5 stars

Timeliness

Cost Rating

Willing to Refer

Quality of Deliverables

The product has been launched on both iOS and Android app stores, and it currently has 15 customers. Internal stakeholders are happy about Xmartlabs. They’re attentive and provide high-quality work. Their resources handle bugs well, and the team has proven to be highly dynamic and creative.

Bryan Levenson

Founder & CEO, CYTK.io at Confidential

Note: This endorsement is based on publicly available client feedback from external review sources.

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