From beta to 8 million conversations a month
Ringg AI builds voice AI agents that handle customer conversations 24/7: sales outreach, support queries, and resolution calls across industries. They launched in February 2025 after six months in beta. Within a year, they hit 8 million conversations per month.
That kind of growth didn't just test their product. It tested every layer of the stack they chose. And for voice AI, the hardest layer to get right is the one nobody sees: the core that connects, routes, streams and orchestrates every call in real time.
The question that filtered out most providers
Ringg's evaluation was built around a single question: if they grew 10x hereon, will this provider hold up?
They tested multiple providers. Most couldn't answer that question with confidence. At Ringg's scale, a dropped call isn't a minor inconvenience. It's a broken promise to an enterprise customer. Siddharth needed a partner that could guarantee that 10,000 concurrent calls could become 50,000 or 100,000 at any given moment.
“When we are promising success to our end customers, it's super important that our platform never fails. And so the underlying offering that we use for our voice agents becomes super critical.”
Why Plivo
The problem most people underestimate
Here's something Siddharth thinks the market doesn't appreciate enough: voice AI is fundamentally a realtime voice problem. Every conversation is a continuous flow of audio data, in both directions, across thousands of parallel connections simultaneously. The AI models get the attention, but it's the platform managing those streams that determines whether the experience holds up or falls apart.
This is where Plivo's experience of building and scaling a voice platform shows. Ringg runs at 99.99% uptime with sub-500ms end-to-end latency across their full voice AI stack, even at their current scale.
“I don't know how much people appreciate the fact that the entire premise of voice conversations is built on streaming bytes, and not everyone has perfected that, in a sense that Plivo has.”
Tool-calling that works at scale, not just in demos
One of the key reasons enterprises choose Ringg is their tool-calling success rate. When a voice agent needs to check an order status, pull up an account, or trigger a workflow mid-conversation, it has to call the right tool at the right time, every time. A missed or delayed tool call doesn't just create a bad experience. It breaks the agent's ability to resolve the conversation.
Siddharth sees this as inseparable from the infrastructure underneath. Stable audio streams and consistent low latency mean the agent hears the customer accurately and responds within the conversational window where a tool call makes sense. When the infrastructure is unpredictable, the entire chain, from speech recognition to tool execution to response, starts to break down.
Capabilities that arrive before you need to build them
What turned Plivo from a provider into a partner for Ringg was watching the platform evolve in the same direction they were heading. Noise cancellation shipped as a bundled capability inside the platform, saving Ringg from deploying and managing a separate model. WhatsApp agentic communication arrived out of the box.
For a team scaling at Ringg's pace, every capability that arrives pre-built is one less integration to manage, one less vendor to evaluate, and one less failure point in the stack.
“A vendor is someone who just gives you one solution and then runs away. When we think of a partner, they are also building in the same space with the same pace that we are.”
The result: growth without rearchitecting
With Plivo underneath, Ringg's engineering team focuses entirely on making their voice agents smarter. They aren't debugging connectivity issues, managing audio quality across regions, or re-evaluating providers every time they hit a new scale threshold.
The confidence shows up in the promises they make to customers: enterprise-grade availability, consistent call quality at any volume, and the ability to 10x without changing the stack.
“Plivo has given us that confidence to promise to the end customer that 10,000 can become 50,000 or a lakh at any given point of time.”
What's next
Ringg is building toward conversational memory. Today, every call starts fresh. Siddharth wants returning customers to be recognized, with context from previous conversations carried forward so agents can pick up where they left off. They're also expanding into multi-step agentic workflows and cross-channel communication.
It's the kind of roadmap that only works if the infrastructure underneath keeps pace. So far, it has.
