DISCOVER PROJECT
3 min read
nRev - AI Sales Worflow
For RevOps team to design custom revenue workflows powered with AI agents
MY ROLE
Lead designer
DURATION
1 MONTH
TEAM
1
TL;DR
nRev is a no-code platform built for RevOps leaders to create and deploy AI-driven workflows — automating lead generation, enrichment, outreach, and follow-ups.
Being a very early stage startup, the product evolved through multiple pivots before landing on a flexible, modular workflow builder that now powers revenue automation with AI agents across the GTM stack.
This included working without the safety net of proper users on platform.
The Initial Challenge
Sales and RevOps teams still rely on spreadsheets, scattered CRMs, and manual grunt work to build their pipeline.
Daily tasks like:
Finding target accounts
Enriching with news, updates, intent signals
Pulling in LinkedIn or CRM data
Sending outreach
Logging follow-ups
...were being done manually or through messy point tools which costed them a lot of wasted time slowing down pipeline momentum
🔁 Multiple Pivots: How We Got to Today
*1
Slack-Based AI Assistant
A tool that connected to Slack and internal knowledge bases to:
Answer queries
Report health scores
Auto-generate to-dos
❌ Why it failed?
Company wikis were outdated → inaccurate results
The outputs were not that accurate overall without various third party data
Complex setup → low scalability
*2
Intelligence Layer for Lead Discovery
This version offered:
Whitespace mapping
Key Decision-makers
Lead recommendations
❌ Why it failed:
"Qualified leads" was too ambiguous — varied across teams
Hard to generalize industry-specific heuristics
Results felt opinionated, lacked trust
✅ Final Direction: Workflow Builder for Revenue Automation
Instead of promising magic insights, we switched to enabling teams to build their own AI automations.
Think n8n meets RevOps, tailored for sales playbooks and GTM use cases.
The user now owns the output, and we provide the Lego blocks — AI agents, integrations, conditions, filters, and triggers.
Design Goals:
Intuitive drag-and-drop interface
Clear logic flow between triggers, conditions, and actions
Scalable architecture that could support future modules like Slack, Salesforce, HubSpot, etc.
Reduce the time to create a workflow from days to minutes
DESIGN
Stakeholder Conversations
Since we had no live user base yet, I collaborated closely with RevOps and GTM advisors to define top workflows:
Inbound lead enrichment
Account research
Trigger-based outreach
ICP scoring + assignment
Benchmarking
I closely studied 6+ workflow tools including N8N, Make.com, Clay, Gumloop to inform component structure, visual patterns, and usability heuristics.
Design Systems + Figma Prototypes
Created reusable components. This allowed for fast iteration across pivots and multiple directions.
Nodes (AI, CRM, Slack, Enrichers)
Connections (Logic gates, Data flow)
Sidebar asset manager
Execution preview
🚀 FROm DESIGN to DEV
Wearing multiple hats at a startup, I also contributed directly to development:
Built and shipped the nRev marketing site using Figma-Make
Implemented visual changes directly into the workflow UI
Used V0, Figma-Make, etc Ato bridge design-dev gap
This hands-on execution kept iteration cycles tight… often going from Figma to live within a day.
🚫 What I’d Do Differently
Even though the current workflow is live and usable, we made critical missteps early on:
Test faster
We waited to build full MVP flows before validating ideas — which led to multiple scrapped builds. I’d now test concepts via:
Clickable demos
Workflow mockups
Test broader
We repeatedly tested with the same small group of RevOps folks, which limited perspective. Broader outreach could’ve revealed edge cases and needs earlier.
