Convin, an AI-powered conversation intelligence platform for call centre setups, recently launched its advanced Large Language Model (LLM), with 7 billion parameters. This model is specifically designed to improve the business output and resolve the unique challenges of customer-facing teams such as sales, support, and collections.
Convin’s new LLM addresses these gaps and significantly outperforms leading models like GPT-3.5 by 40% and GPT-4 Turbo by 20% in accuracy, according to the company.
Trained on over 200 billion tokens and supporting 35+ Indian and South Asian languages, including codemixed variations, the model ensures precise transcriptions, zero to low hallucinations, and contextual understanding. It reassures businesses of a critical advantage in delivering high-quality, culturally sensitive customer interactions.
“Traditional language models often fail to deliver accurate results, but purpose-built models such as Convin LLM produce better results and are more accurate. By addressing major challenges such as agent inefficiencies, call centres can improve handling time, response time, and inconsistent customer experience. This streamlines processes and enhances customer satisfaction by providing precise, data-driven insights and predictive analytics. As a result, call centres realize a substantial cost reduction and new revenue generation,” Atul Shree, CTO of Convin, said.
The process begins by identifying specific objectives related to inefficiencies in the contact centre setup and selecting relevant data sources. Data is then collected and preprocessed to ensure high quality, including filtering, deduplication, and tokenization.
Pre-training on this cleaned dataset helps the model understand linguistic patterns and adapt to different languages. Finally, the model undergoes fine-tuning with task-specific labelled data, refining its parameters to predict labels accurately and deliver optimal performance.
With the enhanced capabilities and efficiencies introduced by this model, Convin anticipates a 200% increase in customer acquisition and a 3X boost in overall revenue for 2024-25.
