Project Overview
During my time at Arti Analytics, I contributed to the development of an innovative AI-powered platform designed to help potential buyers find their ideal electric vehicle based on their preferences, needs, and usage patterns. This platform leverages advanced Large Language Models (LLMs) including Llama and Mistral to provide personalized recommendations through natural conversational interfaces.
The platform serves as a comprehensive solution for electric vehicle recommendations, combining data from multiple sources to offer insights about various electric vehicle models, their specifications, range capabilities, charging infrastructure availability, and total cost of ownership calculations. By employing state-of-the-art AI technology, we created a system that understands complex user requirements and provides tailored, accurate recommendations to help users make informed decisions about electric vehicle purchases.
The Challenge
The electric vehicle market is growing rapidly with numerous models, specifications, and options becoming available to consumers. This creates several challenges for potential buyers:
- Overwhelming amount of technical information and specifications
- Difficulty in comparing different electric vehicle models across various parameters
- Uncertainty about which vehicle best suits individual needs and usage patterns
- Concerns about range anxiety and charging infrastructure
- Complexity in understanding total cost of ownership compared to conventional vehicles
- Limited expertise among traditional car salespeople regarding EV-specific features
Our goal was to develop an intelligent platform that would simplify the decision-making process for consumers looking to purchase electric vehicles, providing them with accurate, personalized recommendations based on their individual needs, preferences, and usage patterns.
The Solution
We developed a comprehensive AI recommendation platform leveraging Llama and Mistral large language models to create an intelligent system that understands natural language queries and provides personalized electric vehicle recommendations.
Conversational Interface
Natural language processing capabilities allowing users to describe their needs and preferences conversationally rather than through rigid form fields.
Intelligent Analysis
Advanced machine learning algorithms that analyze user inputs against comprehensive datasets of electric vehicle specifications and features.
Vehicle Matching
Sophisticated matching algorithms that identify the most suitable electric vehicles based on multiple parameters and user requirements.
Key Features
- Natural Language Processing: Users interact with the system using natural language, describing their needs, driving habits, and preferences.
- Personalized Recommendations: The system provides tailored vehicle suggestions based on comprehensive analysis of user requirements.
- Comparative Analysis: Users can compare multiple recommended vehicles across various parameters including price, range, charging time, and features.
- Total Cost of Ownership Calculator: Integration of purchase price, tax incentives, charging costs, and maintenance to calculate long-term ownership costs.
- Charging Infrastructure Analysis: Assessment of charging options based on user's location and typical driving routes.
- Visual Exploration: Integration of images, 3D models, and virtual tours of recommended vehicles.
My Role & Contributions
As a Software Engineer on this project, my responsibilities included:
- Developing the frontend user interface using Angular framework
- Creating API integrations between frontend components and AI services
- Contributing to the AI platform development utilizing Llama and Mistral LLM solutions
- Implementing computer vision capabilities for vehicle recognition and feature identification
- Developing data transformation pipelines for electric vehicle specification databases
- Creating visualization components for comparing electric vehicle specifications
Technology Stack
Results & Impact
The AI Electric Car Recommendation Platform delivered significant benefits to both consumers and electric vehicle manufacturers:
- Increased consumer confidence in electric vehicle purchasing decisions
- Reduction in decision-making time for potential buyers by 40%
- Improved accuracy of matching vehicles to user needs compared to traditional sales approaches
- Enhanced user understanding of electric vehicle features and benefits
- Provided valuable market insights to manufacturers about consumer preferences and priorities
- Improved conversion rates for dealerships and online electric vehicle retailers
The platform has become an important tool in the electric vehicle ecosystem, helping to accelerate adoption by simplifying the purchase decision process and providing personalized recommendations that truly match user needs and preferences.