India Gets 1 Billion Spam Calls a Month. Equal AI Is the Answer That 1 Million Indians Are Already Using.
India is one of the most spam-called countries in the world. Telecom Regulatory Authority of India data consistently places India among the global leaders in unsolicited commercial calls — everything from financial product sales and loan offers to insurance pitches, real estate inquiries, and outright fraud attempts. For the average Indian smartphone user, the phone call that arrives from an unknown number carries an almost automatic suspicion: is this someone I need to speak to, or is this another interruption to dismiss?
Keshav Reddy noticed this friction and decided that AI could resolve it. Not by blocking calls — blocking creates its own problems, as the occasional genuine unknown caller gets lost alongside the spam. But by screening calls: understanding who is calling, why they are calling, and presenting that context to the user before they decide whether to answer.
In October 2025, Equal AI launched India's first AI call assistant with exactly this capability. The platform intercepts calls from unknown numbers, engages the caller with an AI voice, establishes the caller's identity and purpose, and presents a summary to the user who can then decide to answer, call back later, or decline. Spam calls are identified and filtered. Legitimate callers get through. And the user regains control of something that had become a daily irritant at the scale of hundreds of millions of Indians simultaneously.
On June 12, 2026, Equal AI announced it had raised $30 million in a Series B funding round co-led by Prosus Ventures and Tomales Bay Capital, the same two firms that co-led the $10 million Series A in November 2024. Total funding across all rounds: $42 million. The round also included participation from Valiant Fund, Think Investments, PhonePe founder Sameer Nigam, Zubin Bharti Mittal from the Airtel family office, Skyflow AI co-founder Anshu Sharma, Meta India and Southeast Asia Vice President Sandhya Devanathan, and CtrlS Datacenters Chairman Sridhar Pinnapureddy.
The strategic investor list is as revealing as the financial terms. PhonePe's Sameer Nigam brings deep knowledge of what it takes to build a consumer product with mass adoption in India. Sandhya Devanathan's participation as Meta's most senior representative in the India and Southeast Asia region reflects a strategic view that Equal AI is building infrastructure adjacent to the platforms and networks that Meta operates. The Airtel family office's involvement connects Equal to the telecom infrastructure dimension of the call intelligence problem. These are not passive capital allocators. They are domain validators.
The Company That Started as Infrastructure and Became a Consumer Product
To understand what Equal AI has become, you first have to understand what it was built to be.
Keshav Reddy founded Equal in 2022 with a founding thesis that sat at the intersection of India's digital public infrastructure and the growing enterprise need for consent-driven data sharing. Before founding Equal, Reddy had spent years as a venture investor, backing companies including CRED, Upstox, Hive, Genies, and Chipper Cash. He had a front-row seat to how consumer technology companies in India and emerging markets scale, and he came to Equal with a specific conviction about where the next infrastructure gap was.
India's digital public infrastructure — Aadhaar, UPI, DigiLocker, account aggregator frameworks — had created the technical foundations for consent-based data sharing at national scale. The problem was that most enterprises could not access that infrastructure easily. Banks, insurers, lenders, telecom operators, and digital platforms all needed to verify user identity, access financial data, and process KYC requirements with user consent — but the technical complexity of integrating with 50-plus identity databases and thousands of API providers was a barrier that most organisations could not efficiently overcome internally.
Equal built the platform that sat in the middle: aggregating access to more than 50 identity databases and 4,000-plus API providers, providing a single integration point for enterprise customers that needed to verify users, share data with consent, and process KYC at scale. The platform now serves more than 350 enterprise customers across banking, lending, insurance, telecom, and digital platforms. It processes over 1 billion transactions annually. KYC success rates run at 97 per cent. It has powered 101 million user interactions to date.
This enterprise business is profitable, sticky, and structurally important. But it is also, by its nature, invisible to the consumer. It is the plumbing. The consumer never sees the pipes.
The October 2025 Pivot — and Why It Changed Everything
Reddy has been transparent about the thinking behind the consumer pivot. Equal always intended to build something consumer-facing. The question was which use case to start with. The requirements were specific: a use case that was immediately and obviously valuable, that would build user trust and habit-forming behaviour quickly, and that would create the foundation for expanding into other categories later.
Spam call management emerged as the answer. It is a problem that affects virtually every Indian smartphone user. It is a problem that existing solutions — call-blocking apps, Do Not Disturb registrations, manual screening — have addressed imperfectly for years. And it is a problem that AI is specifically well-suited to solve, because the solution requires real-time conversational intelligence: the ability to engage a caller naturally, extract information about their identity and purpose, and present that information accurately in a format a user can act on in seconds.
The Equal AI call assistant does not work by blocking calls at the network level or by matching numbers against known spam databases. It works by actually talking to the caller — by using conversational AI to conduct a brief interaction that establishes who is calling and why, in real time, before the user sees anything. The result is a layer of intelligent call context that neither the telecom network nor any existing app can provide.
The product launched in October 2025 in beta across Delhi NCR. Within eight months of its public launch, it had crossed 1 million monthly active users and 350,000 daily active users. The company had set an internal target of reaching 1 million daily active users by mid-2026. The monthly figure has already exceeded that threshold. The daily figure is approaching it.
TechCrunch, in its coverage of the Series B, noted one specific strategic decision that distinguishes Equal AI from some of its global counterparts: the deliberate choice not to build on WhatsApp or any third-party messaging platform. Prosus's portfolio includes Luzia in Spain and Zapia in Latin America, both of which were affected by Meta's ban on third-party AI bots on WhatsApp — a platform dependency risk that Equal AI explicitly avoided by building around calls and its own app rather than piggybacking on a messaging platform.
The Unusual Funding Structure — and What It Signals
The Series B has a structure that TechCrunch flagged as still uncommon in Indian startup financing: the $30 million round is divided into three tranches, with Equal AI carrying a different valuation at each stage depending on whether it hits predetermined performance targets. This approach allows the company to advertise the highest valuation achieved across the tranches, even if most of the equity was sold at a lower one — a quirk that Equal AI declined to resolve by providing specific valuation figures.
The tranche structure reflects the milestone-contingent logic that sophisticated investors apply when backing companies at the stage where user adoption and monetisation are still being demonstrated rather than confirmed. Prosus and Tomales Bay are not simply betting on where Equal AI is today. They are creating a structure that aligns their risk exposure with the company's execution against specific targets.
Iqbaljit Kahlon, Founder and Managing Partner of Tomales Bay Capital, described the investment in terms that frame the entire consumer AI opportunity in emerging markets. The geography of ambition has shifted. The most interesting consumer AI products of the next decade are not being built in San Francisco. They are being built for the billion people who carry a smartphone and whose relationship with technology is primarily voice, not text.
That framing — voice over text, emerging markets over Silicon Valley — is the thesis that Equal AI's product directly embodies. The AI call assistant is not a text-based product. It is a voice product, built for a country where the phone call is still the dominant mode of communication for a majority of users, where voice AI has to work across accents and languages and conversation styles that are fundamentally different from the training environment of most Western AI systems, and where the spam call problem is acute enough that a solution which actually works will build habitual daily use faster than almost any other consumer category could.
What the $30 Million Is Building
The capital deployment plan extends Equal AI's ambition well beyond call management.
The company's stated vision is to become India's AI assistant for everyday needs — a comprehensive lifestyle concierge that handles not just calls but financial services, shopping, communication, and daily tasks. Thiago Viana, Global Co-Head of Prosus Ventures, described this as building an AI lifestyle concierge for 100 million Indians — the scale at which a daily-use AI assistant becomes embedded infrastructure rather than an optional application.
The path to that scale runs through the call assistant's success. Every user who adopts Equal AI for call screening is a user whose trust Equal has begun to earn. Every interaction that Equal AI handles on a user's behalf — identifying a caller, filtering a spam call, summarising a business inquiry — is a data point that makes the assistant smarter and more valuable for that specific user over time. The contextual memory that accumulates across millions of daily interactions is the foundation on which the expanded lifestyle concierge capability will be built.
The enterprise infrastructure business continues to operate independently and profitably, providing the financial stability that funds the consumer expansion without requiring the company to raise capital merely to sustain its existing operations. The combination — a profitable enterprise business and a rapidly growing consumer product with strong early retention signals — is the profile that growth-stage investors find most credible at this stage of the AI adoption curve.
Equal AI is building for the Indian user who picks up every call with suspicion, who has been interrupted by spam hundreds of times and has learned to treat the unknown number as an adversary. The product's promise is straightforward: let the AI answer first. You decide what to do with the information it brings back.
One million Indians a month have already decided they like that arrangement. Thirty million dollars says there are many more to come.
