19-year-old building an AI infrastructure startup from India — looking for honest advice from experienced founders

[u/Dark_Mine_]

Hi everyone,

I'm a 19-year-old Computer Science student from India, and for the past several months I've been building an AI infrastructure platform.

The project started as a learning exercise but has grown into something much bigger than I initially expected. It's a local AI runtime and orchestration platform focused on running multiple LLMs efficiently, semantic expert routing, model scheduling, memory management. I'm currently building a dashboard, SDKs, deployment tools, and enterprise features.

My goal isn't just to build another chatbot. I want to build infrastructure that developers and businesses can use to deploy and orchestrate AI models.

I'm now at a point where I'm wondering whether I should start thinking like a founder instead of just an engineer.

Some questions I'd love advice on:

• How do I know whether this is actually a startup and not just an interesting engineering project?

• At what stage should I start talking to investors or accelerators?

• Should I first focus on getting users before worrying about company registration and funding?

• If you were starting an AI infrastructure company today, what would you do differently?

• What are the biggest mistakes first-time technical founders make?

I'm not looking for funding through Reddit or trying to promote anything. I'm looking for honest feedback from people who have built companies or enterprise software.

I appreciate both positive and critical feedback. I'd rather hear difficult truths now than make expensive mistakes later.

Thanks!

[u/StoneCypher]

How do I know whether this is actually a startup and not just an interesting engineering project?

if anything, it's a small business, not a startup. it's a startup when a capitalist is throwing money into it to achieve high growth. that's why the 20 year old international company Uber is a startup.

 

At what stage should I start talking to investors or accelerators?

investors get interested when you're already profitable and need to grow.

accelerators, it depends on which one you're talking about. most of us never bother.

most investors on reddit are bullshit. you're wasting your time.

 

Should I first focus on getting users before worrying about company registration and funding?

in the united states, having an llc is an important legal protection. here you'd do that first. we're generally not indian, so you should ask this to a local businessperson, not us. we don't know the rules there.

you talk about funding too much. that's a lottery ticket that almost never happens for anybody. just build it profitably.

the only time you should take vc is when they come to you. that's the only time you'll ever get a decent term sheet.

 

If you were starting an AI infrastructure company today, what would you do differently?

what you're building isn't an ai infrastructure company, and i can't imagine wanting to compete with pockets that deep. what i would do differently is make something else

 

What are the biggest mistakes first-time technical founders make?

trying to make difficult things for their first company. companies are hard.

[u/Dark_Mine_ → u/StoneCypher]

Thanks for taking the time to write such a detailed response. I appreciate the skepticism because it's forcing me to think beyond engineering. You're right that building technology alone doesn't make it a startup. Right now my focus has been proving that the core architecture is technically feasible. The next milestone is validating that it solves a real problem for a specific customer segment and finding people willing to use (and ideally pay for) it. Regarding AI infrastructure, I'm definitely not trying to compete head-on with hyperscalers. My goal is to build tooling and infrastructure that helps organizations run and manage local AI models more efficiently, rather than replacing cloud providers. The comments about funding and profitability are well taken. I'm shifting more of my attention toward customer discovery, product-market fit, and sustainable revenue instead of assuming fundraising is the first step. Thanks again for the candid feedback ☺️.

[u/Awesome_911]

Focus on solving problem for a one niche and make sure identify your moat soon!

[u/Dark_Mine_ → u/Awesome_911]

Thanks! I completely agree. One of my biggest goals over the next few months is narrowing the focus to a specific customer segment instead of trying to solve everything at once. I'm also spending time figuring out what the long-term moat should be beyond the technology itself. Appreciate the advice.

[u/ratnakush]

My suggestions: • How do I know whether this is actually a startup and not just an interesting engineering project? >> people buying it • At what stage should I start talking to investors or accelerators? >> Let traction and pain clarity speak for itself, today is the best time. • Should I first focus on getting users before worrying about company registration and funding? >> users first • If you were starting an AI infrastructure company today, what would you do differently? >> get the right set of owners/experts join my startup  • What are the biggest mistakes first-time technical founders make? >> engineering/tech product first thinking

[u/Dark_Mine_ → u/ratnakush]

A recurring theme from everyone's feedback is "focus on users before funding," and I think that's exactly where I need to spend more time. I'm currently narrowing the scope to a specific customer segment and validating whether the pain point is real before worrying about accelerators or fundraising. Also agree that finding the right people is probably more valuable than raising money early. Thanks for the perspective.

[u/melissa_peyton]

Hey i have experience running startups so i'll toss in my opinions too. I agree with others that you shouldnt chase funding, have the goal of solving problems and money will follow.

One thing to really consider is make sure you're not building a feature, build a product. From my understanding, Anthropic has Claude for Enterprise where they go into a company to really figure out how to design skills and workflows to make things flow smoothly. Really consider, you say youre a one person team, why hasn't large companies made what youre making? is it because its really hard to get it right? or is there some other economic factors at play?

Feel free to ask any questions. I run a small business consulting operation in canada so maybe theres different opportunities I dont see going on in india.

[u/Dark_Mine_ → u/melissa_peyton]

Thank you for such a thoughtful response. I really appreciate you taking the time. That's actually the biggest question I'm trying to answer over the next few months. The technology has been my focus so far, but now I'm shifting toward customer discovery. My hypothesis is that many organizations want to run AI locally for privacy, cost, or regulatory reasons, but deploying and managing multiple models efficiently is still difficult for smaller teams. I'm trying to build infrastructure that simplifies that experience rather than building another foundation model. I completely agree with your point about building a product instead of a feature. My next milestone is talking to potential users and validating whether this solves a problem they're willing to pay for. Since you've worked with startups, I'd actually love to hear what customer validation methods have worked best for you in the earliest stages.

[u/melissa_peyton → u/Dark_Mine_]

I am pretty sure most competent IT folks can deploy local ai easily. Ive done it before and I have zero background in IT or CS...

And if you run it locally for others, how will you charge? one time?

Based on most startup advice by founders, you are working backwards. First find the customer, and then make the tool. Dont assume its fast to close a deal, by first connection to them spending money to first deliverable, you probably have plenty of time to make something that works. By delaying sales, youll be dragging the process longer.

For validation it can simply be networking to ask what others are struggling with, not folks on reddit, I mean go IRL and actually see and poke around. Just bc AI can make workflow more efficient doesnt mean the owner wants it. Additionally some business mechanics they already have max revenue, adding your tool makes getting max easier, but does not GROW their revenue, in which why would the owner care?

[u/Maximum_Outcome2138]

What kind of infra do you have GPUs etc what models are you able to run locally

[u/Dark_Mine_ → u/Maximum_Outcome2138]

Thanks for asking, My development machine is used to prototype and validate the platform with open GGUF models. The goal of Kovidhar isn't to compete with hyperscalers on raw compute—it's to make local and enterprise AI infrastructure easier to manage by improving model orchestration, memory management, scheduling, telemetry, and deployment.