Kevin William David

nRev - Your AI GTM Engineer

The future of GTM is here. nRev is a GTM wizard, trained on 10,000+ deployed marketing and sales engines. It consults based on what's working, builds and deploys automations, simply by having a conversation with it.

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Chaitali Naik

Excited for this launch!

The problem around GTM being too tool-heavy and manual is very real. @nRev feels like a strong step towards simplifying that.

Would love to know, what is the most painful part of your current GTM setup?

Athsara Fernando

Can I set this up to watch executive job changes in my target accounts and trigger a warm outreach the day they update LinkedIn?

Sayanta Ghosh

@athsara absolutely, and this can be completely outbound - the entire sequence of steps and a notification to let you know about it in the way you want.

Aradhya Shandilya

@athsara Indeed. We have live linkedin monitoring that you can run on a cadence of your choice.
We further have Rocketreach as a partner that can help you directly search people who've recently switched jobs or used to work with your past customers.

You can even monitor and warm up prospects by automatically engaging with their linkedin.

Bhavesh Navandar

Hi everyone, Bhavesh here!

I'm a Founding Engineer at nRev.
My focus has been building the underlying engine that powers everything the team have shared.
While Nikhil and Daksh were perfecting the AI "brains," I spent my last year building the "body"—the platform that ensures those agents have a solid place to work.

In GTM, "cool" doesn't matter if it isn't reliable. You can't run a $50M company on a system that "mostly" works. I've spent the last year obsessing over the platform's plumbing: ensuring that when an agent triggers a workflow, the data flows perfectly from the CLI or workflow to your CRM without a hitch.

We built nRev so you could stop being a "tool integrator" and start being a "GTM Architect."

We've taken the entire burden of managing vendors, fallbacks, and execution logic and baked it into the platform core.

If you've ever had a workflow break in the middle of a massive campaign, you know my pain. I'd love to know what's the most "fragile" part of your current GTM setup?

Hiya Udwani
Massive congrats on the launch! ⚡️ I’ve been interning at nRev since February and seeing the team build this from the ground up has been incredible. It’s not just another tool. It actually replaces the mess of duct taped apps most GTM teams deal with. So proud to see the "AI GTM Engineer" finally out in the world! 🚀
Kumar Amit

Hey everyone, Amit here, Founding Engineer at nRev.

Huge day for us. This has been a deep, hands-on build - taking GTM from a pile of stitched tools to something you can actually reason about, modify, and scale without friction.

My focus has been on making the system behave predictably under real-world complexity. GTM workflows aren’t static APIs fail, data is messy, and edge cases show up at scale.

We designed the platform to handle this natively: retries, fallbacks, state management, and observability are not add-ons, they’re core.

The goal was simple: you describe intent, the system figures out execution - reliably.

If you’ve ever had a campaign break because one integration failed or spent hours debugging a workflow across tools, I’d love to hear where things usually fall apart for you.

Dipanjan Dey

What happens if something breaks midway? Can users' see what broke? this has been a major problem with some of the AI integration-type tools I've tried till date

Sayanta Ghosh

@dipanjan_dey I love this question, this is probably one of the things that make workflows stand far apart from agents. Workflows are defined by the exact steps that they need to do. In fact, even the AI steps have guardrails which ensure 100% times that they structure their output in the way that is desired.

This ensures that the sacrosanct GTM systems of record are not messed up even over millions of executions and every time the output or actions are exactly same.

Agents in nRev however are used to experiment on data sets, build the workflows but not execute workflows because of this exact same problem

Aradhya Shandilya

@dipanjan_dey Absolutely. Every execution stays logged. Every credit attributed. You can even set up notifications directly on slack, gmail and more if anything goes off.

Shivang Kamboj

“Tried this today pretty interesting so far. Planning to use it for LinkedIn GTM for our product to drive B2B clients. Curious to see how well it handles platform-specific nuances though LinkedIn outbound and content strategy can get very context-heavy (ICP, tone, sequencing, etc.). If it can go beyond generic playbooks and actually adapt to that level, this could be a strong tool.

Aradhya Shandilya

@shivang_kamboj2 the fact that you're leading with this thought itself is a step in the right direction.

And of course, every message you send out can have every possible nuance like

  1. ICP: A simple gatekeeper to ensure you don't waste your precious limits.

  2. Tonality: Can be curated to the last detail or can be simply sourced from your past conversations ;)

  3. Sequencing: Complete flexibility, you can space your messages based on your schedule and we ensure you stay adherent to the limits.

  4. Personalisation: Anything from a generic signal to a person's interests driven from emerging patterns from their historical reactions can drive a message.

    Happy to brainstorm and showcase how we approach it: https://cal.com/aradhya-shandilya-oaznsv/15min


Jan Martínek

Are u only listening to LinkedIn and Reddit, or can it pick up signals from other public sources like X, Instagram, SEC filings, government data, news?

Aradhya Shandilya

@honzamartinek indeed. We have a suite of AI models that can access almost any of the sources you've mentioned to get you precise information on demand.

Abhijit Bhole

Fantastic stuff!

Jay Purohit

@anbhole Thank you

Lotanna Nwose

Great launch, Once I set this up, can I trust it to run the exact same way every single time?

Aradhya Shandilya

@_viclotana That's the game !

Your GTM systems are sacred. One wrong CRM write is a week long cleanup.
Hence the approach. Use AI agents to build a deterministic workflow that runs a 1000 times rather than running an AI agent over and over again.