AI Could Become a New Defense Against Spam Calls in India
Despite years of regulation, penalties, and technological interventions, spam calls and messages remain among the most persistent digital nuisances in the country.
Despite years of regulation, penalties, and tech interventions, spam calls and messages remain one of the most persistent digital nuisances in the country. Unknown numbers constantly flash on screens, showing insurance offers, loan pitches, scams, surveys, delivery updates, and occasionally a real call.
Under the Telecom Regulatory Authority of India’s (TRAI) Telecom Commercial Communications Customer Preference Regulations (TCCCPR), 2018, telecom operators are required to curb unsolicited commercial communications. The regulator has imposed penalties of around ₹141 crore on telcos so far for non-compliance.
And yet, the problem persists.
Telecom operators say that they are being unfairly penalised for a problem they cannot fully control. They insist they are intermediaries, not originators of spam. Commercial communications, they point out, are initiated by business entities and routed through telemarketers. In practice, accountability becomes blurred.
Telemarketers frequently switch operators, enforcement remains inconsistent, and telcos have limited leverage to impose strict conditions without disrupting legitimate traffic. The result is a regulatory system under strain, and consumers caught in the middle.
Against this backdrop, a new class of AI-driven tools is emerging, promising to tackle not just spam but the deeper anxiety around unknown calls. One such startup is Equal AI, founded by Keshav Reddy, which is rethinking the problem from a consumer-first perspective.
“Phone spam is one of the biggest daily pain points for Indians today,” Reddy says. “The government, telecom operators, and OS-level players are all trying to solve it in different ways. But we felt there was space to build something directly for consumers.”
What Sets It Apart
Equal AI’s approach is markedly different from traditional caller ID apps. Instead of merely identifying who is calling, the system focuses on answering a more important question: why they are calling.
When an unknown caller calls, Equal AI’s assistant answers first. The AI speaks to the caller, understands their intent, and then relays a summary to the user, who can decide whether to take the call, ignore it, or respond via instructions typed in real time.
“You can say something like ‘tell them I’m busy’ or ‘ask them to call back later,’ and the AI conveys that,” Reddy explains. “Only after that does the call connect to you, if you want it to.”
Focusing on context instead of just identity is key to Equal AI’s idea.
In a country where quick commerce, OTP verifications, logistics updates, and service calls generate a steady stream of legitimate but unfamiliar numbers, simply labelling a caller is no longer enough.
“Caller ID apps address only one aspect of the issue: identifying the caller,” Reddy states. “You still don’t know the purpose of the call or if it matters to you.”
India’s Official Caller ID System
The timing of Equal AI’s launch coincides with another major development in India’s telecom ecosystem: Caller Name Presentation (CNAP). Introduced by TRAI, CNAP displays the caller’s name directly on the phone screen, sourced from the telecom operator’s database. The wider testing phase began in December 2025, and a phased rollout to consumers is now underway across 4G and 5G networks, with broader availability expected by March or April 2026.
Since CNAP does not require an app or internet access, it has sparked speculation that it could render third-party caller ID apps redundant. However, industry observers note that CNAP, like other solutions, addresses only identity, not intent.
CNAP shows you the caller’s name, but it doesn’t tell you whether the call is important, urgent, or even worth picking up.
“For unknown calls, context is everything,” Reddy says. “Instead of just seeing a name, Equal AI will tell you: ‘XYZ is calling regarding the strategy discussion scheduled this morning.’ That completely changes how you perceive the call.”
This change is important because unknown calls can cause anxiety, particularly with the rise of advanced scams. Many individuals search for phone numbers online, check forums, or simply choose to ignore calls, which can result in them missing important messages. Equal AI aims to present relevant information upfront, thereby reducing both friction and cognitive load.
“We’re acting as an assistant for the average Indian,” Reddy says. “The information is surfaced immediately, and the user decides.”
India is Turning to AI
Since launching a product video last October, Equal AI has seen unexpectedly strong traction. The video crossed 100 million views on Instagram, prompting the company to open its waitlist gradually due to the heavy infrastructure demands of real-time conversational AI.
“This requires serious concurrency, GPUs, and reliability,” Reddy notes.
The growth curve reflects the pent-up demand. The platform started with around 3,000 users in October, grew to 15,000 in November, 50,000 in December, and is expected to reach approximately 100,000 monthly active users in January, without a full go-to-market rollout.
The momentum has continued into 2026, with the platform now recording 383,000 monthly active users in February, while also crossing 100,000 daily active users during the same month. The company is now targeting 750,000 monthly active users by March as it scales adoption further.
The app is currently available on Android, with an iOS version in development.
Equal AI wants its call assistant to do more than just reduce spam. It hopes to help with other tasks in different fields. For example, in financial services, people get many calls about insurance renewals, some relevant and many not. “With Equal AI, you could instruct the assistant to find the best insurance offers for you. That’s what people do anyway, compare prices and choose the best option. AI can do that faster and better.”
Similarly, education and healthcare are call-heavy domains in India, where last-mile coordination still relies heavily on voice communication. From college admissions and loan processing to booking medical appointments, humans remain in the loop, even in digital workflows.
“AI can already search for information,” Reddy says. “But execution still falls on the user. We want to build systems that actually complete the task.”
In this plan, the AI call assistant is just the starting point, a hook that solves an everyday problem while laying the foundation for deeper automation. Over time, the assistant could automatically categorize calls, negotiate options, or complete transactions on the user’s behalf.
What’s Next?
As India tightens regulations, rolls out CNAP, and continues to fine telecom operators, one reality is becoming clear: spam is not just a regulatory failure, but a design problem. Identity alone does not equal relevance. Penalties alone do not restore trust.
Whether AI assistants like Equal AI can meaningfully reshape how Indians currently experience phone calls remains to be seen. But in a landscape where the phone has become both indispensable and intrusive, solutions that prioritize context over mere compliance may tip the balance back in favor of the user.
