Why I’m Building HQLogic.tech

For a long time, I was interested in both machine learning and software engineering.

But I noticed a gap.

Building a machine learning model in a notebook is one problem.

Turning that model into a reliable product that people can actually use is a completely different one.

That's the problem space I want to work in.

What is HQLogic?

HQLogic.tech is my independent software brand.

I'm building it as a place where I can experiment with ideas, build products, and explore practical applications of AI.

The focus isn't on adding AI to everything.

The focus is on asking:

Can AI actually make this product better?

If the answer is yes, I'll use it.

If a simpler piece of software solves the problem better, I'll use that instead.

What I'm Building

My interests sit at the intersection of:

• Artificial Intelligence
• Machine Learning
• Data & Analytics
• Backend Systems
• High-performance applications
• Automation
• SaaS products

I'm particularly interested in the journey from:

Problem → Data → Model → API → Product → Production

A model that works perfectly in a notebook isn't enough.

It needs to become a system.

It needs an API.

It needs a usable interface.

It needs monitoring, error handling, deployment, and eventually real users.

That's where I want to spend my time.

The Engineering Philosophy

I'm not interested in using complicated architecture just because it looks impressive.

For an early-stage product, a well-structured modular monolith can often be a better choice than immediately introducing microservices, queues, and distributed infrastructure.

Complexity should be earned.

The same principle applies to AI.

Not every problem needs an LLM.

Not every application needs an AI agent.

Not every dataset needs a deep learning model.

Sometimes a simple algorithm, a good database schema, or a carefully designed workflow is the better engineering decision.

Building in Public

I'll also be sharing the process of building HQLogic.

That includes:

• Architecture decisions
• Database design
• AI/ML experiments
• Performance optimization
• Infrastructure
• Product development
• Things that break
• Lessons learned
• And, hopefully, things that actually work

I don't want this website to be a collection of polished success stories.

I want it to document the engineering process behind the products.

What's Next?

I'm starting with small, focused products and gradually building toward something bigger.

There will be experiments that fail.

There will be architectures that need to be rewritten.

There will be models that don't perform as expected.

That's part of building software.

The goal is simple:

Build useful things. Learn from the process. Ship again.

Welcome to HQLogic.tech.

— Shivam