Is “US-first” still the right default for AI products?
With today’s tools, translation (UI, copy, even video) is no longer the hard part.
What slows us down instead are things like tax, legal compliance, hiring, support, payments — sometimes even geopolitics. The moment users show up from a new country, a “product” problem turns into an operating one.
That also makes me wonder: Is “US-first” still the right default for AI products?
Or do some products actually benefit from starting in smaller, simpler markets?
No strong conclusion yet — just a tension I keep running into. Curious how others are thinking about this.
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I don’t think “US-first” is a default anymore -it’s a tradeoff.
The US gives fast feedback and revenue, but it also turns product problems into ops problems very early (compliance, support, security, expectations). I can say this because I have personally set up companies in both USA and India, and have lived through the pros and cons of it.
Sometimes you end up scaling operations before you’ve truly learned the product.
For some AI products, starting in smaller or less noisy markets lets you stay in product-learning mode longer. But to be honest shared workflows and pain points often matter more than geography now.
Feels less about biggest TAM, more about where you can learn fastest without ops overwhelming you.
Vozo AI — Video localization
@dushyant_khinchi By the way, is the Indian market more operationally intensive compared to other markets?
Vozo AI — Video localization
@dushyant_khinchi @josie_oy Curious how others are thinking about this in practice.
If not US-first (or not only US), what other markets are people starting with — or prioritizing right after — and how are those decisions being made?
Is it driven more by customer density, regulatory simplicity, distribution channels, or something else?
@josie_oy @lightfield
From what I’ve seen (both first-hand and by watching other founders closely), the answer really starts with the type of business, not the geography.
For purely online / AI / software products, location matters far less for demand and far more for:
compliance & tax simplicity
where you incorporate vs. where you operate
payment rails and data rules
Your actual TAM is global from day one. Users don’t care where you’re based as long as the product works and trust signals are there. In those cases, founders often start where it’s cheapest and fastest to learn, then expand compliance later as usage shows up in specific regions.
For other business types, geography matters a lot more:
Marketplaces (rides, rentals, services)
These live and die by local density. For example, food delivery or mobility marketplaces often find early traction in India or Southeast Asia because dense cities create faster liquidity, while the same model can struggle in spread-out US suburbs.
Fintech & Payments
Regulation dominates everything. Many founders prototype in the US for credibility but launch real products in India, Brazil, or Indonesia, where digital payments adoption is massive and consumer behavior evolves faster -though compliance still varies country by country.
Healthtech / Medtech
The US and EU offer large budgets but slow approvals. Some startups validate products in India or Latin America, where hospital partnerships and trials can move faster, before expanding into heavily regulated Western markets.
Manufacturing & Hardware
Geography is critical. China, Vietnam, and Taiwan dominate electronics due to supplier ecosystems. India works well for textiles and certain electronics thanks to labor scale and government incentives. Trying to do this from a high-cost country early can kill margins instantly.
Climate, Energy, and Resource-heavy startups
These depend on natural advantages. Nordics for clean energy pilots, Middle East for large-scale solar, Australia for mining-tech. The product literally can’t exist without the right local resources.
What I’ve seen work best in practice is:
Start where learning is fastest and operational drag is lowest, then follow usage and pull. Let real customers dictate which markets deserve deeper compliance and investment.
So it’s less “US-first vs non-US” and more:
Where does this specific business model have the highest chance to compound before ops complexity slows it down?
That question tends to produce much better decisions than defaulting to any single geography.
@josie_oy Good question -short answer: it depends on the business model.
Yes, India can be more operationally intensive than the US, especially for businesses that involve physical infrastructure, manufacturing, logistics, or heavy regulatory touchpoints. If I were setting up a factory or managing a complex supply chain, I’d think very carefully before starting in India.
But for AI / online / service-based businesses, the equation flips.
For my AI work, India has actually been simpler operationally:
No complex state-level compliance maze like in the US
Lower baseline costs for experimentation
Easier early hiring and iteration
Much less pressure to look “enterprise-ready” on day one
In the US, you often hit operational overhead early - legal structure, security expectations, contracts, tax complexity, customer compliance - even before true product-market clarity. That can slow learning.
On funding: it’s a misconception that serious AI funding only exists in the US. India now has strong seed and pre-seed options, active angels, global funds investing locally, and government-backed programs actively pushing AI. The ecosystem is maturing fast, and the support is very real.
So it’s not about one market being “easier.”
It’s about choosing the market whose friction matches your stage and product.
Every geography has trade-offs — the key is deciding which ones you want early and which ones you’re okay taking on later.
Vozo AI — Video localization
@dushyant_khinchi Thanks for sharing this — it was genuinely helpful.
I’ve mostly associated India with challenges I’d seen in physical or highly regulated industries, so I’ve probably carried that bias over more broadly. Your perspective on AI and software was new to me, and it definitely reshaped how I think about India as a starting point for certain products.
From building browser-based tools used by people in different countries, I’ve seen that “US-first” works for MVP speed, but breaks quickly at scale.
Language isn’t the hard part anymore — it’s things like performance on slower networks, local expectations around signup, privacy, and even payment friction.
Tools that feel simple and accessible globally tend to win more trust than feature-heavy products optimized for one market. Designing global-first from day one saves a lot of rework later.
Vozo AI — Video localization
@allinonetools_net That makes a lot of sense. I’ve run into some of this myself — things like app size, assumptions about stable networks, or default signup/payment flows feel invisible early on.
For those who’ve designed global-first from day one, what were the most practical early decisions that actually paid off?
@lightfield Thanks, glad it resonated 🙌
We’ve seen the same thing—shipping “US-first” is fast early on, but it creates friction later when real users come from everywhere. Even small steps like neutral copy and flexible onboarding make a big difference. Curious how others here are approaching this.
I'm living this right now! I'm UK-based but built HIPAA-compliant voice AI targeting US healthcare because that's where the budget and willingness to pay is. But the compliance overhead (BAAs, US-based servers, etc.) is real. Smaller markets are easier operationally but harder to build a business on.
Launching on PH in 2 days actually & would be curious for your take on the product!
Vozo AI — Video localization
@philk1 That’s a very real tradeoff — and good luck on the launch in 2 days!
Totally agree that for B2B, compliance isn’t optional, it’s foundational. We’ve just gone through SOC 2 Type II and GDPR ourselves, and the overhead is real but unavoidable if you want to earn trust.
Happy to share what we learned if it’s useful for anyone here.
To me, it’s still US-first.
The US market has strong willingness to pay, high adoption of new tools, and the best “generality”.
There’s also a very practical reason: localization cost.
I once wanted to focus on Japan, but quickly realized how expensive and hard it is if you’re not a native speaker — from expressing value clearly, to making videos and marketing assets.
Vozo AI — Video localization
@jojo_li Totally fair point — localization used to be genuinely hard.
From our side, tools are getting much better though. We launched Vozo’s video translator on PH last year, and over the past year most of our work hasn’t been “big launches”, just weekly improvements on real edge cases: subtitles timing, dubbing quality, lip sync, weird languages, long videos, etc.
That said, I agree language isn’t the whole story. Even when translation works, there’s still context, culture, pricing expectations, and ops friction that tools don’t magically solve.
If you ever try it and something feels off, I’d honestly love to hear where it breaks — that’s how most of our improvements happened.
@lightfield Ha, nice product! Tried it out and left a review.
Lancepilot
I think the default is shifting. Translation and localization aren’t the bottleneck anymore, operations are.
For some AI products, starting in smaller, simpler markets makes sense: faster buying decisions, clearer pricing, less compliance drag. You can reach PMF operationally before taking on the complexity of the US.
US-first still works if your ICP is US-centric or enterprise, but it’s no longer the obvious default. Ops, not language, now determines where you start.
Spot on. As someone building a finance-focused Notion system, I see this daily. Translation is just the surface.
The real challenge is context. For example, a US-first finance tool often fails in Europe because of different banking cultures, tax regulations, and even mindset towards saving.
I actually believe starting in a 'smaller, simpler' (or just specific) market is a massive advantage. It allows you to solve the operational pain for a specific group of people so well that a 'US-first' giant can't compete with you. Deep localization is the new moat!
Many companies are now staying in Europe aka the spotify model, and realizing that it doesnt have to be in SF to actually take the leap.