The Story
Unveilr AI has raised a pre-seed round backed entirely by Aviral Bhatnagar's ajvc, at a post-money valuation of ₹16.7 crore. The amount was not disclosed. Some early reports described ₹16.7 crore as the sum raised; it is the valuation.
Sanditya Srivastava founded the Mumbai company, which launched in February 2026. An IIT Roorkee graduate, he spent years as a staff AI engineer building retrieval systems and AI agents, according to ajvc, before starting Unveilr. The idea came from his previous venture, a direct-to-consumer AI app that users rated highly and almost nobody found. Looking into why, he found that a growing share of people had stopped searching on Google and were asking ChatGPT instead, and his app never appeared in those answers. Other brands told him the same thing: their customers were asking AI, and they had no idea whether they were showing up.
Unveilr works in what the industry calls answer engine optimisation, getting brands cited and recommended inside answers from ChatGPT, Perplexity, Gemini, Claude, Grok and Google's AI Overviews, alongside conventional search engine optimisation. It is a managed service rather than a software dashboard. Its own team runs each engagement on proprietary AI agents covering research, competitor mapping, audits, content, publishing, outreach, refreshes and tracking, identifying the queries where competitors are being recommended and the sources the assistants draw on. It re-audits every tracked prompt after each major model launch, so that citations lost when a new model ships can be won back.
Engagements start at ₹65,000 a month, scoped on prompt volume, content volume and technical depth, and billed month to month with no lock-in. The company serves B2B and consumer brands in India, the UAE and the United States, and says customers typically see results within the first month. It cites one case: for an Indian B2B legal services platform, it says AI-sourced traffic rose about 4.7 times and leads five times, with ChatGPT citations up 80 percent.
"If a brand isn't one of them, it has lost that lead before its website ever loads," Srivastava said, describing how assistants surface only a handful of names in each answer. He argues that AI agents will increasingly research, compare and eventually buy on users' behalf, which makes inclusion in their recommendations a commercial necessity.
The money goes into expanding the engineering team, building further capabilities for its agents, and growing sales across India, the UAE and the US.
Srivastava said it took less than two weeks from his first conversation with ajvc to a term sheet. Bhatnagar pointed to strong adoption of Unveilr across ajvc's own portfolio as a sign of its general-purpose utility.
Why It Matters
For twenty years, being found online meant ranking. A search returned ten links, a brand fought for a place among them, and third place was worth less than first but still worth something. AI answers break that arrangement. Ask an assistant which accounting software suits a small firm, or which protein powder to trust, and it does not return a page of links. It names three or four, with reasons, and the conversation moves on. A brand outside that handful is not ranked lower. It is absent.
That is the shift Srivastava ran into before he understood it. His previous app had good reviews and users who liked it, and it was invisible, because the people who might have found it had stopped typing queries into Google and started asking ChatGPT. Nothing in his analytics explained the gap, because the conversations where his product went unmentioned happened somewhere he could not see.
Most brands are in the same position, and the first generation of tools built for it addressed visibility directly. They track which prompts mention a brand, how often, in what position and with what sentiment, across the major assistants. That is useful, and it is also, in Srivastava's framing, a dashboard telling a marketing team how often it is mentioned when what the team wanted was traffic, leads and revenue it could point to.
The gap between those two things is why the work is hard. Learning that a brand is missing from ChatGPT's answers is alarming and not, by itself, actionable. The levers that change it are diffuse: the third-party sources the assistants retrieve from, the review sites, forums and comparison articles that shape what a model says, the structure and freshness of a brand's own content, and how all of it shifts each time a model is updated. Pulling those levers is labour, spread across research, writing, outreach and constant re-checking. That is why Unveilr sells the labour rather than the measurement, and why its founder's background is relevant: he spent years building the kind of retrieval systems and agents that now decide which brands get recommended, which is an unusually direct apprenticeship for this particular problem.
The Strategic Read
Start with the number, because it is being misreported. ₹16.7 crore is Unveilr's post-money valuation, not the size of the round, and it matches almost to the rupee the terms ajvc gave Slayd and MoroMaa last month, where ₹1.5 crore bought roughly nine percent. It is the fifth ajvc company StartupFox has covered and the pattern holds: a standard price and a fast decision, here under two weeks from first call to term sheet. Bhatnagar's point about adoption across ajvc's own portfolio also tells you where the first customers came from. That is a sensible way to start, and it is a set of buyers with a reason to say yes; the proof that counts will come from customers with no tie to the cap table.
The category context sharpens the positioning. Two weeks ago Profound, the New York company that has come to define this market, raised $180 million at a $1.8 billion valuation, nearly double its February price, without disclosing revenue. It began as visibility software, and its newer products are agents that research, write and publish. The category is moving from measuring to doing, and Unveilr's argument is that the doing was always the product.
That puts it in the agency business, whatever the technology underneath, and agencies grow with headcount. A ₹65,000 monthly engagement, cancellable any month, is a fair price for a small brand and a modest contract for a venture-backed company. The investment case is that the agents do enough of the work for each new client to cost less to serve than the last. If that holds, it is software with a service wrapper. If it does not, it is a well-run agency with a cap table, and this round's priority on engineering and agent capability suggests the founder knows which one he has to prove.
The promise to be judged on revenue is the right one and the hardest to keep, because attribution in AI search is partial. When an assistant names a brand, many people do not click a link. They search the name or type the address, and the visit arrives looking like direct traffic rather than a referral from an AI. Measured AI-sourced traffic therefore understates the real effect, which makes results harder to verify in both directions. The legal services case study is self-reported and comes without base figures, and one client is a demonstration rather than evidence.
The ground also moves. Citations change with every model release, which is why Unveilr re-audits after each one, and a month of work can be undone by an update. Search engine optimisation went through an arms race in which shortcuts worked until the platforms closed them, and AI companies have every reason to resist being gamed. The approach that lasts is earning genuine presence in the sources the models trust, which is slow, and is the work Unveilr says it does.
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