Ringg's AI Solutions Cut Customer Call Costs and Response Times
With AI agents resolving up to 65% of customer calls, Ringg leverages OpenAI's GPT-5.6 to redefine customer service efficiency and satisfaction, addressing the growing demands of modern businesses.
Key Facts
- Ringg's AI resolves 65% of calls, enhancing efficiency and reducing human labor costs significantly.
- Migrating to GPT-5.6 cut model costs by 90%, improving financial performance and scalability.
- Policybazaar saw response times drop 88%, showcasing competitive advantage through faster service.
- Practo's 70% cost reduction highlights the financial benefits of AI in operational workflows.
- Ringg's context layer enables seamless multi-channel interactions, indicating a strategic market shift.
Summary
Summary
Ringg, a voice and chat agent platform, faced challenges in managing increasing call volumes for large consumer businesses in India. By deploying OpenAI's GPT-5.6, Ringg built a multilingual agent system that resolves up to 65% of customer calls without human intervention, achieving significant cost reductions and improved response times.
Background
Ringg operates in the customer service technology industry, focusing on voice and chat solutions. Before the deployment of AI agents, Ringg's clients struggled with high call volumes and inefficient manual systems, leading to increased operational costs and complexity in customer interactions.
Challenge
The primary challenge was to efficiently handle rising customer call volumes while maintaining service quality and reducing costs. Traditional scaling methods, such as hiring more agents, were not sustainable.
Solution
Ringg implemented an enterprise agent platform utilizing OpenAI's GPT-5.6 to power multilingual agents across various channels, including voice, chat, WhatsApp, and web. This system migrated suitable workloads from the previous model, GPT-4.1, to GPT-5.6, achieving a 90% reduction in model costs while ensuring high-quality service and low latency.
Results
Ringg's AI agents now handle over 7 million connected calls each month, resolving up to 65% of customer inquiries autonomously. For clients like Policybazaar, the average response time improved from 8–12 minutes to under 60 seconds, an 88% reduction. Practo achieved an 85% first-call resolution rate with response times under three seconds, and operating costs decreased by 70%. Groww resolved 72% of inbound queries related to IPOs and options through self-service, with an average handling time of two minutes.
Key Insights
Businesses can leverage AI to enhance customer service efficiency and reduce operational costs. Implementing a robust orchestration system that integrates various tools and models can significantly improve response times and customer satisfaction. Continuous testing and model evaluation are essential for maintaining high performance in AI deployments.
Customer Testimonial
“OpenAI has been highly responsive when we’ve needed support with model migrations. The dedicated Slack support and access to the core engineering team help us move quickly with less engineering uncertainty, ship faster, and expand what our agents can accomplish.” — Ringg Team
Entities Mentioned
Companies
Products
Technologies
Key Concepts
Definitions
- AI agents
- Automated systems that interact with customers through various channels to resolve inquiries without human intervention.
- orchestration system
- A framework that manages the flow of information and actions across different tools and platforms during customer interactions.
- customer satisfaction (CSAT)
- A measure of how products and services meet customer expectations, often represented as a score.
- model evaluation
- The process of testing AI models against historical data to assess their performance and identify areas for improvement.
- multilingual agents
- AI agents capable of understanding and responding in multiple languages to cater to diverse customer bases.
Use Cases
- →Handling customer inquiries via voice and chat
- →Booking healthcare appointments
- →Processing insurance claims
- →Conducting Know Your Customer (KYC) processes
- →Providing IT troubleshooting support
- →Facilitating onboarding for platforms
Frequently Asked Questions
How does Ringg's AI improve customer service?
Ringg's AI agents can resolve up to 65% of customer calls without human intervention, significantly reducing response times and operational costs. This allows businesses to handle more inquiries efficiently.
What are the cost benefits of using Ringg's AI agents?
By migrating workloads from GPT-4.1 to GPT-5.6, Ringg has achieved a cost reduction of approximately 90% for certain tasks. This makes it a more economical solution for customer service operations.
How does Ringg ensure the quality of its AI models?
Ringg tests its models using historical conversations and simulated customer flows to identify weaknesses. This continuous evaluation process helps improve the performance of its AI agents.
What industries can benefit from Ringg's AI solutions?
Ringg's AI solutions are beneficial across various industries, including insurance, healthcare, and finance. Companies like Policybazaar and Practo have successfully implemented Ringg's technology to enhance their customer service.
What is the role of OpenAI in Ringg's technology?
OpenAI provides the underlying models, such as GPT-5.6, that power Ringg's AI agents. These models help ensure high-quality interactions and efficient handling of customer requests across multiple channels.