Most prospecting workflows don’t fail because of bad data — they fail because humans are still doing the orchestration.
In this Builder Series post, we break down how one RevOps builder used Lusha’s API, automation, and AI to turn prospecting into a background system instead of a daily task.
Most prospecting setups don’t fail because the data is bad.
They fail because the workflow is fragmented.
Open LinkedIn.
Copy a name.
Paste it into a data tool.
Check company context somewhere else.
Switch tabs. Lose focus. Repeat.
That loop isn’t inefficient — it’s cognitively expensive. And RevOps teams feel it every day.
So when Manthan Patel decided to stop prospecting from his laptop entirely, it wasn’t a stunt. It was a systems decision.
He built a Telegram bot that connects directly to Lusha’s API, routes requests through an AI agent, and returns fully enriched person and company data — in one conversation, from his phone.
No tabs. No dashboards. No context switching.
The problem wasn’t speed — it was mental load
Before the build, Manthan’s flow looked familiar:
- Search a person on LinkedIn
- Copy into a data tool
- Pull contact details
- Check company size, industry, funding
- Repeat 20–30 times per session
Each lead took 5–10 minutes. Not because the tools were slow — but because the human was doing the orchestration.
RevOps teams see this pattern everywhere:
- Humans stitching systems together
- Tools waiting to be told what to do next
- Data arriving too late to be useful
The insight wasn’t “we need faster enrichment.”
It was: why is a human still coordinating this at all?
The build: intent → routing → data, automatically
Manthan’s setup is simple by design.
He connected:
- Telegram as the interface
- n8n as the orchestration layer
- Claude as the intent parser
- Lusha’s APIs as the data engine
How it works
He sends a message in Telegram:
- “Find info on Satya Nadella at Microsoft”
- “Tell me about Tesla”
- “Find marketing directors at Salesforce”
An AI agent interprets the request and routes it automatically:
- Person API
- Company API
- Prospecting API
Lusha returns verified contact data and company context.
The bot responds — in the same thread — with enriched results.
Because the agent remembers conversation context, follow-ups don’t require re-prompting. The system behaves like a knowledgeable ops assistant, not a form.
What changed (and why it matters for RevOps)
This isn’t about prospecting from your phone.
It’s about collapsing intent, data, and action into one surface.
A few important shifts happen here:
1. Prospecting becomes event-driven
The question triggers the data pull — not the other way around.
2. Data becomes ambient
Enrichment runs when needed, not as a scheduled task or CSV job.
3. Humans exit the glue layer
RevOps logic lives in the workflow, not in someone’s browser history.
This is exactly how Revenue Builders think:
- Fewer tools to “use”
- More systems that quietly run
- Less time spent coordinating, more time acting
As one commenter on the post put it:“Speed isn’t the win here. Cognitive load is.”
Why Lusha fits naturally into builds like this
Lusha isn’t the interface in this setup — and that’s the point.
It acts as:
- A verified data layer
- Accessible via API, automation tools, and AI workflows
- Reliable enough to be embedded into live systems
When builders trust the data, they stop checking it manually.
When they stop checking it manually, automation actually sticks.
This is how Lusha shows up in modern RevOps stacks:
- Not as another tab
- But as infrastructure other tools depend on
The bigger takeaway
The most interesting part of this story isn’t Telegram or AI agents.
It’s the mindset behind the build.
Revenue Builders don’t ask: “How do I prospect faster?”
They ask: “Why is prospecting still a manual activity at all?”
They design systems where:
- Intent triggers data
- Data triggers action
- Humans supervise, not execute
That’s the shift the Builder Series is about.
Quiet systems.
Verified data.
Less toil.
Keep reading:
How one builder used n8n + Lusha’s API to enrich enterprise CTOs in mins
How Lusha uses job-change signals to re-activate high-intent prospects
How one builder turned buying signals into instant outbound
Waterfall data enrichment: why streaming data beats static stacking
FAQs
RevOps automation is the practice of turning manual revenue operations tasks—like data enrichment, lead qualification, and routing—into system-driven workflows that run continuously without human intervention.
Revenue Builders don’t focus on doing prospecting faster. They design systems where intent triggers data enrichment automatically, removing manual steps like list building, copying data, or switching tools.
nstead of searching manually, an API-based setup routes a request (for a person, company, or ICP) directly to the relevant data endpoint. The system returns enriched results instantly and can trigger downstream actions automatically.
No. Many Revenue Builders come from sales or RevOps backgrounds. The key requirement isn’t coding expertise—it’s understanding which parts of the workflow create friction and should be automated.
Context switching between tools increases errors, slows execution, and leads to inconsistent follow-through. Automation removes the need for humans to coordinate systems, allowing teams to focus on decisions and conversations.
