AI is no longer optional in CPaaS: Insights from Sriram Manoharan of CONTUS TECH

In February 2026, a group of technologists gathered in Chennai for a focused discussion on the evolving role of Artificial Intelligence (AI) in Communications Platform as a Service (CPaaS). At the center of the conversation was Sriram Manoharan, Founder and CEO of CONTUS TECH, who offered a clear perspective: AI is no longer an enhancement, it is becoming foundational to how enterprise communication systems operate.

For organizations still evaluating whether to integrate AI into their communication infrastructure, his message was direct. The hesitation, he suggested, is no longer strategic, it is costly.

Here’s what he explained and how:

From Automation to Intelligence: A Shift in Enterprise Thinking

Sriram Manoharan’s journey into digital transformation began long before the current AI wave. With early experience at firms like Wipro Infotech, TCS, and IBM, he spent years building technical and operational expertise before founding CONTUS TECH. Over time, the company has grown into a multi-crore enterprise with a global client base and a team of over 500 professionals.

But his current focus is less about scale and more about direction.

“We use AI to absorb the noise,” he said. “Password resets, order status, balance checks, give it all to AI. That frees so many skilled agents from boring routines.”

This idea reflects a broader shift in enterprise thinking, from using AI purely for automation to leveraging it for intelligent workload distribution. According to him, the real value lies in allowing human teams to focus on conversations that require empathy, judgment, and strategic thinking.

The Fragmentation Problem in CPaaS

For years, enterprises have built their communication systems in silos. Different departments adopted different tools, chat APIs for sales, voice solutions for support, and billing systems for finance. While functional in isolation, these systems often struggle to work cohesively.

Sriram pointed to this as a structural inefficiency.

“When one API fails, other parts of your system might not work. It’s a serious nightmare. Your system cannot forget who a customer is just because one of your bots is facing a minor glitch,” he said.

The industry, however, is beginning to move toward full-stack communication ecosystems, where data continuity and system integration take priority. Instead of fragmented tools, enterprises are investing in unified platforms that support the entire customer lifecycle.

This transition, he believes, is not just technical but strategic.

AI Architecture Is Rapidly Evolving

One of the more nuanced discussions during the session revolved around how AI systems are being architected within CPaaS environments.

A few years ago, even simple customer interactions required multiple disconnected processes, IVR systems, separate booking calls, and repeated data inputs. Today, AI is enabling what Sriram described as “intent-driven computing.”

Instead of responding to commands, systems are beginning to interpret user intent, why a customer is reaching out, what they need, and how urgently they need it.

However, achieving this requires a complex backend. Technologies like Speech-to-Text (STT), Large Language Models (LLMs), and Text-to-Speech (TTS) often operate across different servers, leading to latency and cost challenges.

“Developers these days are implementing single docker containerization. For multi-container apps, you can go with Docker Compose and orchestrate with Kubernetes,” Sriram explained.

Human-Centric AI: Beyond Keywords and Scripts

Another significant shift is how AI systems interact with users. Traditional bots were largely rule-based, responding to predefined keywords. Today, they are increasingly context-aware.

“They are not just looking for keywords. They are trying to understand why the customer is contacting them.”

This includes analyzing emotional cues, frustration, urgency, or expectation, and adjusting responses accordingly. He refers to this as understanding the “emotional weight” of a conversation.

“If your bots do not understand this, stop wasting time and money. Remove them,” he said candidly.

This perspective reflects a growing industry focus on human-centric AI, where effectiveness is measured not just by efficiency, but by the quality of interaction.

AI as a “Super-Assistant,” Not a Replacement

Despite concerns about automation replacing jobs, Sriram positions AI differently, as an enabler rather than a substitute.

Routine tasks, particularly Tier-1 queries like password resets or order tracking, can be handled by AI systems. This reduces operational load and allows teams to operate more efficiently.

In high-stakes environments, the impact can be even more significant. For instance, in use cases like national helplines, AI-assisted workflows have led to measurable improvements.

“AI in CPaaS saves your time, your money, a lot of headcounts and many precious lives,” he stated, referencing real-world implementations where workflow steps were reduced by up to 45%.

The Trust Gap in AI Adoption

As AI systems become more advanced, another challenge is emerging: trust.

Data suggests a gap between perception and reality. While 83% of organizations believe they are transparent about their use of AI, only 38% of users feel the same. This disconnect raises important questions about communication and ethics.

For Sriram, this is an area that requires immediate attention.

“We need to carefully add the guardrails right from the beginning,” he said. “Make ten times sure your AI hallucinates less or acts right when conversing with your customers.”

He also stressed the importance of ethical design, particularly as AI systems become more human-like in their interactions.

“We must focus on the ethical design of our AI CPaaS systems, so businesses can build connections, and not just automation.”

A Transition Already Underway

The broader takeaway from the discussion is that the integration of AI into CPaaS is not a future possibility, it is already in motion. Enterprises are shifting from fragmented tools to unified systems, from automation to intelligence, and from efficiency to experience-driven communication.

Sriram’s viewpoint is less about predicting the future and more about recognizing the present. Organizations that delay adoption risk falling behind, not just technologically, but competitively.

His closing stance is clear: businesses must begin exploring AI now, not as an experiment, but as a core component of their communication strategy.