About Sharoze Iftikhar

I design HubSpot revenue systems and build AI automation for B2B revenue teams. My work sits where two things meet: the operational plumbing that makes a CRM actually drive revenue, and the AI tooling that takes the repetitive, judgement-heavy work off a team's plate. The throughline is the same in both cases - make the system do the work reliably, so the people don't have to.

On the HubSpot side, I'm a HubSpot Certified Trainer with deep platform expertise. I've spent years inside the parts of HubSpot most consultants never touch: workflow actions and their real-world guardrails, CRM architecture and association schema, calculated properties, and custom coded actions that extend the platform beyond what the native toolset allows. I know not just what the UI exposes, but what the public API actually supports - and where the gaps are that quietly break revenue processes.

The proof is in what I've shipped. I built NetworkDays, a HubSpot app that brings real business-day logic - holidays, working calendars, SLA timers - into HubSpot workflows, and you can install it at networkdays.io. Alongside client work, I run revopsdev.com, my RevOps consulting practice. Building and operating my own products keeps me honest: I live with the same tradeoffs I recommend to clients.

Read the NetworkDays build journey for the engineering and operating decisions behind the app.

My approach is minimal and deliberate. I'd rather ship one thing that works than five things that demo well and break in production. Every tool, integration, and dependency has to earn its place. When the answer is to do less, I do less. That discipline carries into how I build AI systems too - for knowledge retrieval I favour hybrid CAG over naive RAG, because grounding an agent in structured, queryable truth beats stuffing it with fuzzy chunks and hoping the embeddings line up. Correct beats clever, every time.

I work with clients worldwide - across time zones, mostly async, always with a bias toward systems that keep running whether or not I'm in the room. If you're a revenue team trying to make HubSpot do more, or you want AI automation that's actually wired into how your business operates rather than bolted on, that's the work I do.

HubSpot Consultant Background

As a HubSpot consultant, my work sits at the intersection of CRM architecture and automation engineering. I design HubSpot implementations for revenue teams that have outgrown template setups: complex pipeline logic, custom-coded workflow actions, Operations Hub data syncs, and AI agents wired into the CRM rather than bolted on. The HubSpot Trainer credential and 26+ HubSpot certifications reflect depth across the platform, not breadth across agencies or industries. I'm also a solo practitioner, which means the person scoping your build is the person shipping it.

How I got to RevOps

I did not start in revenue operations, and I did not jump there from a desk. The earliest work was research: around 2019 I published policy and security analysis as a Research Fellow at the South Asian Strategic Stability Institute (SASSI) and on Strafasia, writing on nuclear deterrence and strategic stability. Those pieces ran under the bylines M. Sharoze Iftikhar and Muhammad Sharoze Iftikhar, the same chsharoze handle I still use on GitHub, X, and email. You can read that work on my Strafasia author archive, including pieces like Emerging Dynamics in South Asia and Implications for Strategic Stability.

From there I worked across the commercial side of the business before any of it was called RevOps. Three years in marketing, PR, and compliance, then a move into business development, then into sales operations, where the HubSpot and systems work started to take over. RevOps is where all of that converged. I had done the marketing, carried a sales number, and run the operations, so building the engine that ties those functions together was the natural next step, not a left turn. Today that means enterprise CRM architecture, post-merger consolidation, attribution, and AI automation for revenue teams.

The throughline is a way of thinking. My training is in Public Administration, and research, marketing, sales, and operations all reward the same habits: model how the system actually works, reason under incomplete information, design for the real constraints, and refuse to claim more than the data shows. The subjects changed. The discipline did not.