Ringg, a voice and chat agent platform, has implemented OpenAI's GPT-5.6 models to power its multilingual enterprise agents, achieving significant improvements in customer service efficiency and cost-effectiveness.
Ringg's AI agents achieve 65% call resolution using GPT-5.6
The company reported that migrating certain real-time workloads from GPT-4.1 to GPT-5.6 Luna reduced model costs by approximately 90% while maintaining required quality and latency. Ringg's agents now handle more than 7 million connected calls per month, with customers reporting an average customer satisfaction (CSAT) score of 4.8.
Ringg's platform uses different versions of the GPT-5.6 model for specific tasks:
- GPT-5.6 Luna: Used for real-time voice and chat traffic.
- GPT-5.6 Terra: Handles post-call analysis, including summaries and sentiment classification.
- GPT-5.6 Sol: Supports evaluation, prompt improvement, and model-as-judge workflows.
The agents are capable of resolving up to 65% of routine customer inquiries without human intervention. Real-world applications include India's Policybazaar, where 67% of calls are handled without human intervention, reducing response times from 8–12 minutes to under 60 seconds. Additionally, healthcare platform Practo achieved an 85% first-call resolution rate following deployment.
Ringg's orchestration layer enables these agents to perform multi-step workflows by interacting with CRMs, ticketing platforms, and internal APIs. The company is also developing browser agents using OpenAI's computer-use capabilities to automate processes such as KYC (Know Your Customer) and IT troubleshooting.
Sources
- Ringg’s AI agents resolve up to 65% of customer calls with OpenAI （OpenAI News, 2026-09-23）
- Ringg