Companies are racing to integrate AI into their customer experience operations.
Yet despite all the hype, many deployments run into a fundamental problem: machines simply don’t understand the human voice as well as they should.
Accents, background noise, and speech variability often cause AI systems to fail, leading to frustrated customers, call escalation, and loss of trust.
As Sharath Narayana, Co-founder of Sanassays it:
“Ninety-five percent of AI projects have failed. People are very quick to conclude that this is going to completely change everything and then, after six months, they say: ok, this doesn’t work.”
It’s a sad reminder that automation alone doesn’t guarantee a better customer experience. Customers don’t just want speed; they want to be heard and understood.
Old systems, new pressures
Sharath says much of the challenge comes from trying to adapt AI to business systems built decades ago.
“Think about Fortune 500 companies,” he says.
“These companies have been around for a long time. Some of their CRM systems were built on mainframes. No one knows what code was written or who wrote it. You can’t change it overnight.”
While the pressure from boards to “show the impact of AI” is intense, companies are realizing that the biggest bets carry too much risk. Instead, they look for simple, high-impact solutions that deliver visible results quickly.
This is where Sanas finds ground.
From empowering humans to supporting AI
Sanas first made his name by helping human agents communicate more clearly.
By softening accents and eliminating noise, the technology has opened the door to thousands of new CX workers in India and the Philippines.
“We have helped many agents land jobs they would never have had without Sanas,” Sharath says.
“When you lift one person out of poverty, you lift an entire family. That’s when you feel like you’re building AI for good.”
But recently, demand has increased for Sanas to support AI agents as well.
“All of these automation stacks were designed to serve humans,” says Sharath.
“We asked ourselves: ‘If we eliminate misunderstandings between two people, why not also between an AI agent and a human?’ This is where we decided to create our SDK.
Real-world impact
The SDK is already finding powerful use cases:
- Accuracy of transcriptions: “One of the largest transcription companies is using us to improve the accuracy of two-digit ASR,” says Sharath.
- AI call management: A global agent company saw its abandonment rates drop by more than 30 points, thanks to better “turn-taking” (knowing when to pause or speak).
- Synthetic telecommunications call detection: A major telecommunications company is testing Sanas for synthetic calls, abuse and fraud, which previously cost them millions despite abandonment rates of 98 percent.
These are not minor efficiency gains; they result in smoother customer interactions and better business outcomes.
Why speech understanding is important
For Sharath, the key is empathy. Customers want authenticity, not robotic uniformity.
“A lot of companies asked us early on: Can you make everyone look like Sheila from Texas? Our answer was no,” he says.
“We always make a human sound like themselves. Because when there’s realism in the way you speak, that’s where empathy comes in. That’s where confidence comes in.”
This philosophy also shapes Sanas’ new language translation tools, designed to ensure that speakers always “speak as themselves” even when communicating in another language.
A balanced future
Looking ahead, Sharath envisions a balanced role for human and AI agents.
Short calls of less than two minutes can be automated, but for longer or sensitive conversations, the human touch remains essential.
He is firm in his assertion that there will always be a human in the loop, emphasizing the fact that “AI agents are not free” and suggesting that the cost of computing, storage and scaling is often equal to or greater than that of outsourcing.
This makes technologies like Sanas even more critical, as they ensure that humans and AI can interact in a clear, authentic and reliable way.
Building Trust in AI CX
Businesses may not be able to rewrite their existing systems overnight, but they can still take steps to improve customer experiences today.
Speech understanding is quickly emerging as the missing link, bridging the gap between automation and empathy.
And with its SDK now in the hands of some of the world’s largest companies, Sanas is positioning itself as a leader in building that bridge.
“With a robot that can better identify and understand humans, maybe this world could change,” reflects Sharath.
For businesses under pressure to demonstrate the impact of AI without sacrificing customer trust, it’s a future that can’t come soon enough.
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