AI-Powered Ringg Platform Resolves 65 Percent of Calls
The Ringg platform uses OpenAI models to resolve up to 65% of customer calls for large enterprises while reducing costs.
Voice and chat agent platform Ringg is successfully resolving up to 65% of customer service calls for large enterprises in India by integrating OpenAI models.
Search for Solutions Against Increasing Call Volumes
As call volumes increase in customer service operations, businesses typically resort to increasing staff numbers, which drives up the cost and complexity of each interaction.
Voice and chat agent platform Ringg observed this problem closely while working with large consumer businesses in India and noticed that companies struggled with manual systems.
Integration of OpenAI Models and Cost Advantage
Following these experiences, Ringg built an enterprise agent platform with OpenAI models at its core, bringing together voice, chat, WhatsApp, and web channels.
Migrating suitable real-time workloads from the GPT-4.1 model to the GPT-5.6 model reduced model costs by approximately 90% while providing the required quality and latency.
Using Different Models for Various Tasks
Ringg utilizes models such as GPT-5.6 Luna for real-time interactions to interpret customer requests and direct workflows.
The company distributes workloads among OpenAI models according to task requirements; GPT-4.1 manages general traffic, while other versions handle analysis and evaluation processes.
Successful Results Achieved with Corporate Clients
Policybazaar managed to handle 67% of calls without human intervention while reducing the average response time to under 60 seconds.
Practo achieved an 85% first-call resolution rate, while Groww resolved 72% of incoming queries entirely through self-service.