Every major technology cycle gets remembered for the problem it solved. Search solved access to information. Social media solved access to people. Ride-hailing solved access to transport. Each of these started as a niche bet on an underserved problem before becoming infrastructure.

We believe the next decade belongs to a problem nobody in AI has been willing to name directly: the growing distance between people who love each other.

This is not a sentimental claim. It is a market thesis, and the numbers behind it are large enough that we think any investor evaluating the AI hardware space should be paying attention.

The demographic setup

India is home to an estimated 140 million citizens aged 60 and above, a number projected to more than double by 2050. This is not a slow-moving trend confined to one country. Globally, roughly 270 million people live away from their country of origin, with India’s own diaspora accounting for more than 18 million of that figure. Add to this a structural shift the World Health Organization has flagged as a genuine public health concern: chronic loneliness in older adults, now linked in multiple studies to accelerated cognitive decline.

Put plainly, the population of people separated from someone they love, by distance, by time zones, or by death, is not a niche. It is one of the largest underserved emotional and economic categories in the world, and almost no category-defining hardware company exists inside it yet.

Industry analysts project the AI companion device market to reach approximately USD 12 billion by 2030. That number reflects software assistants, chat companions, and general-purpose conversational AI. It does not yet account for a category we believe is structurally different and currently has no dominant player: physical, dedicated devices built specifically around presence, memory, and emotional continuity, rather than productivity or entertainment.

That gap is where iAVATARS sits.

What we have built, and why it is defensible

iAVATARS is an AI hardware company. Our core devices, the iA VLA Basic and iA VLA Pro, are tabletop displays that let a person interact with an AI-generated avatar of someone they love, whether that person lives far away or is no longer alive. The experience is powered by iSoul 1.0, our proprietary AI engine, which is built to render a recognisable, emotionally resonant likeness of a real person rather than a generic conversational character.

Three design decisions separate this from a typical AI consumer product, and each one matters to how we think about defensibility.

First, our devices function fully offline, with all personal data, including voice recordings, video, and interaction history, stored locally rather than in the cloud. This is both a genuine privacy advantage and a practical necessity, since many of our target users are elderly individuals in regions with inconsistent internet access.

Second, we filed early on intellectual property. iAVATARS holds a Patent Cooperation Treaty application pending simultaneously across five jurisdictions: the United States, the European Union, India, Australia, and New Zealand. Filings of this breadth are unusual for a company at our stage, and that was deliberate. Categories that have never existed before are vulnerable to being replicated by larger, better-capitalised companies the moment they are proven out. We chose to absorb the cost and complexity of filing early rather than risk that outcome.

Third, we have prioritised on-the-ground validation over lab demos. Over the past month, our team has been visiting old age homes across Mumbai, not to sell a product, but to sit with residents, document their stories, and understand what presence genuinely means to someone who has gone months without seeing a family member. We have deliberately withheld device demonstrations during these visits. The relationships and the qualitative insight came first. One resident told our team she had simply forgotten what her daughter’s laugh sounded like. That single sentence has shaped more of our product roadmap than any formal research sprint could have.

Why this matters for capital allocation

Hardware-AI companies face a familiar set of investor hesitations: longer development cycles, higher capital intensity, and slower paths to revenue compared to pure software plays. We do not think those concerns are wrong. We think they are exactly why the category remains open.

Capital flowing into Indian AI startups has grown substantially over recent years, with funds increasingly seeking differentiated, IP-backed ventures rather than incremental software layered on top of existing large language models. A five-country patent position, a working offline-first product, and a validated emotional use case is a different risk profile than a chatbot wrapper, and we believe it should be evaluated as such.

We are not asking anyone to underwrite an idea. We are asking investors to underwrite a category that the underlying demographic and public health data suggests is already large, already growing, and currently has no dominant hardware player.

Where we go from here

Our near-term focus is threefold: deepen institutional partnerships with senior living communities and hospice networks, expand validation through continued on-ground engagement, and build toward a wider commercial release on the back of the product insight this outreach has generated.

We are building this because we believe the feeling of presence is worth solving for on its own terms. We also believe that when you solve a problem this large, this underserved, and this structurally defensible, the business case follows the human one rather than competing with it.