Fractional Tech & Product Advisor for SaaS & AI · Founder, Aarohii
I help founders and CTOs of SaaS and AI companies decide what to build, how to ship AI features people can trust, and where engineering and quality will break before growth finds out. Fourteen years from QA to product leadership, and today I build my own SaaS products at Aarohii — so every piece of advice gets tested in something I run.
14 years · QA → Product → Founder · Product leadership · AI product building · Software quality
Results from in-house product leadership roles, not advisory engagements. Full context and attribution on Outcomes.
Product decisions: roadmaps you can defend to a board, what to kill, and how to move upmarket.
AI features: readiness, evaluation, failure states and guardrails before customers find the gaps.
Technology risk: architecture reviews, technical-debt priorities, and due diligence for investors.
Release confidence: quality architecture that lets you ship weekly without heroics.
For founders and technology leaders who need ongoing judgment across architecture, product, quality, AI and engineering decisions.
A monthly retainer covering the decisions that are too expensive to get wrong: architecture reviews, roadmap calls, quality and release risk, AI readiness, technical hiring, debt prioritisation and board preparation.
For teams with release risk, flaky automation, weak CI gates or unclear quality ownership.
Read the engagementFor founder-led SaaS teams before a major product investment, enterprise push or AI initiative.
See how it runsFixed-scope independent assessment for investors, acquirers or founders preparing for funding.
See the scopeFor companies adding AI features that need evaluation, observability and quality guardrails before launch.
See the assessmentEntry offers exist so we can start where the risk is. The advisory retainer is where most engagements settle. Hands-on implementation is scoped separately, or built with Aarohii.
Two outcomes from in-house product roles, where I worked with client programmes as an employee, and one from building my own companies. Client identities are withheld; the intervention and measurable outcomes are described.
Automation architecture, CI quality gates, performance engineering and release controls for a regulated insurance platform facing scaling risk.
Enterprise deals die on trust gaps — audit logging, SSO/SCIM, permissions, data residency — not on missing features. Resequencing the roadmap around deal blockers, and killing what is loud but irrelevant.
Read the full caseQuickVikalp (2023–2026) folded into Aarohii, now an AI product house with three live products and a fourth launching — real users, real constraints, real runway.
My current ventures keep me close to the realities I advise on: AI integration, SaaS product development, quality engineering, automation and operating constraints. Consulting and building are complementary — not separate worlds.
The arc runs QA → quality architecture → product leadership → founder → advisor. Each step added a failure mode I can now see from the other side of the table.
Parent company · AI products & integration
LLM SaaS, AI integration and quality engineering. Where hands-on build capacity is scoped when an advisory engagement needs execution — and the house behind the four products below.
aarohii.com
Visual regression testing
AI-powered visual regression testing — catch visual and flow breaks before your users do.
pixellpeep.com Read the build log
Business OS
CRM, sales, inventory, payments and AI agents in one operating system.
captverse.com Read the build log
AI social media
AI that cannot post without you. It drafts in your brand voice, and nothing publishes until you approve it, from Telegram in seconds.
viraqueue.com Read the build log
Vendor management
Enterprise vendor management and procurement — requisitions, RFx, suppliers, work orders and invoicing, source to settlement.
auvora.co.inWhy adding engineers can make a scaling problem worse.
The roadmap is not the strategy — the assumptions underneath it are.
AI features need evaluation architecture, not just more E2E tests.
What I would inspect before investing in a SaaS company.
Which shape of help the decision in front of you actually needs.
Spikes and named assumptions before roadmap fiction.
Ongoing senior judgment across architecture, quality, product and AI decisions — without hiring another full-time executive. It is not staff augmentation, not outsourced QA, not an unlimited engineering help desk, and not a replacement for a CTO or VP Engineering you already have. Full scope and boundaries.
Founder-led B2B SaaS and AI companies, typically Series A–C or growth stage, around 20–200 engineers. The quality architecture engagement also fits smaller teams of 10–60. Investors and acquirers engage me for technical due diligence.
Most advisory work begins within a week of signing. Diligence can start in two business days.
Yes — India, Southeast Asia, North America and Europe. Remote by default; I travel for intensive work.
A project has a defined scope and end. A retainer is ongoing judgment — see how to tell which one you actually need. For a full build, that’s Aarohii.
Tell me what is happening, what it is costing the company, and what decision you need to make. If there is no fit, I will say so.
I read every submission personally and reply within two business days — including the ones I decline.
Ten questions. The more precise your answers, the more useful my reply.