better car people case study
Scaling Voice & Chat AI agents for Better Car People’s Automotive Platform
The Client Project
Better Car People specializes in providing support to customers seeking technical services for their vehicles through agents and chatbots.Â
By optimizing their AI systems, ClickIT improved conversational accuracy, enhanced multilingual voice interactions, and streamlined support workflows, enabling faster issue resolution and more efficient customer interactions
Requirements
We boost the AI capabilities of their core platform, focusing on improving conversational workflows, voice-to-text accuracy, and debugging capabilities.
Custom Voice-to-Text Model
Custom Text-to-Voice Solution
Generative AI Nodes Optimization
Optimize API Usage via Classification
Improve Niche-Specific Recognition
Debugging & Workflow Visibility
Implemented Services
ClickIT engineers joined the Better Car People team. They improved the platform’s built-in AI and custom models for automotive use. The focus was on better conversations, higher voice accuracy, and more efficient workflows for agents and end users.
- Optimized the Core platform's generative AI nodes, applying advanced prompt engineering for better contextual responses.
- Built custom ASR (Whisper-based) and TTS models trained with automotive terminology to handle multilingual voice interactions.
- Integrated classification logic to filter and route car-related conversations, reducing unnecessary API calls.
- Developed workflows for custom form generation and management within Core's CMS.
- Improved Smart Assist debugging tool to make troubleshooting faster and more efficient.
Our Tech Stack
JavaScript
Python
AWS
Kore.ai
Next JS
MySQL
LLaMA 3.1
Gemini
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The Results
The collaboration remains ongoing, with a dedicated team supporting continuous improvements across the platform:
- 2 AI Engineers
- 1 NLP Engineer
- 1 NET Developer
The impact improved both system performance and team capabilities:
- Improved conversational accuracy across voice and chat interactions
- Enhanced recognition of automotive-specific terminology and entities
- More efficient AI workflows, reducing unnecessary API usage and improving response times
- Stronger internal capabilities, enabling the team to design and deploy generative AI nodes independently