Founder. Operator. Technology & Product Advisor.

The capability arc

This is not a job history. It is the sequence that produced the way I look at a system.

• QALearned failure modes — not in theory, but by watching which things actually break in production and which never do.
• QA architectureLearned how systems create or prevent defects. Coverage is a lagging indicator; structure is the cause.
• Product leadershipLearned how product decisions create engineering consequences. Most “engineering quality problems” were authored months earlier in a prioritisation meeting.
• Founder / operatorLearned the economics and execution constraints directly, with my own capital and my own runway at stake.
• AdvisorCombines the above — which is the actual differentiator. Not that I know QA and product, but that I can see the failure modes between product strategy, engineering execution, quality architecture and release outcomes.

Why the ventures matter to the advisory work

I run Aarohii AI Solution, an AI product house behind four products: PixellPeep (visual regression testing), Captverse (business OS), ViraQueue (AI social media with human approval) and Auvora (enterprise vendor management, launching soon). That is not a credibility ornament — it is the reason the advice stays honest.

Building an AI product forced me to solve evaluation for non-deterministic output rather than talk about it. Folding an earlier venture into Aarohii taught me the cost of spreading a small team across too many bets, which is the same discipline I now ask clients to apply to roadmaps. And paying for a flaky pipeline out of my own runway settled any remaining doubt about whether quality architecture is a cost or an investment.

Advising and building are complementary. The moment I stop building, my advice starts aging.

Operating philosophy

• Fix systems before adding headcount. Hiring into a broken system scales the symptom.
• Measure the constraint before prescribing the solution. I read CI history and incident logs before I read documentation.
• Make risk explicit before building. Name the assumption that, if wrong, kills the initiative — then go test it cheaply.
• Prefer capability transfer over consultant dependency. If an engagement ends with your team needing me more than when we started, I did it wrong.
• Use AI where it improves leverage, not where it merely sounds modern.

How I work with clients

Three clients at a time, maximum. That constraint is commercial and deliberate: the value of a weekly advisory session collapses if I am running twelve of them.

Engagements are fixed-fee and fixed-scope, agreed before we start. I do not bill hourly, and I keep advice and delivery in separate commercial envelopes — so a recommendation from me is never a quote in disguise. Where hands-on build capacity is needed, it is scoped separately or handled by Aarohii, and you are free to take the plan elsewhere.

If there is no fit, I will say so on the first call and point you somewhere better. That happens often enough to be worth stating.

Background

14+ years across QA engineering, quality architecture and technical product leadership, in SaaS, regulated fintech, healthcare and enterprise environments. Engineering education at Dr. A.P.J. Abdul Kalam Technical University. Based in Noida, India, working with teams across India, Southeast Asia, North America and Europe — remote by default, travelling for intensive work.