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Neha Prasad
Neha Prasad

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I Built a GTM Research Workflow with One Vaaya API Key

I wanted to see how far I could take a simple idea:

Give an agent one API key and let it handle the different pieces of company research.

So I built GTM Radar.

You paste a company URL, and it turns that into a structured GTM brief instead of making you jump between different research and data tools.

What GTM Radar does

The workflow currently generates five main sections:

  • Overview — company description, industry, size, location and website
  • Structure — departments and key people
  • Market — signals, competitors and positioning
  • People — who might be relevant to reach and why
  • Outreach — why now and a possible angle

The goal is simple: go from company URL → useful GTM context as quickly as possible.

Why Vaaya?

The interesting part for me was being able to connect several providers through Vaaya rather than integrating each one separately.

The workflow currently uses:

Firecrawl · Exa · Akta · OpenFunnel · OneFind

through a single Vaaya key.

Vaaya's API provides a common interface for its catalog, so the workflow can call different services using the same API authentication and request pattern. It also supports cost limits and only charges successful calls.

That made experimenting with different providers much easier.

The workflow

At a high level:

Company URL
     ↓
Company discovery / extraction
     ↓
Company + market research
     ↓
People & GTM signals
     ↓
Structured GTM brief
     ↓
Share / copy / reuse
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The interesting part isn't any individual API call.

It's combining several data sources into something that is actually useful to a person doing GTM research.

Handling failures

Real-world data workflows don't always return clean results.

For extraction, I added a fallback path so that if the first provider doesn't work, the workflow can try another route instead of immediately failing.

The current flow is roughly:

CRW
 ↓
Firecrawl scrape
 ↓
CRW fallback
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I also added cost-capped runs and a 12-hour cache to avoid unnecessary repeated work.

Sharing the research

The latest thing I added was Share Insights.

After generating a brief, you can now:

  • Copy a link and let someone else open the same brief without running the workflow again
  • Copy the summary and paste it into a chat or document
  • Share the generated insights directly with someone else

This felt like an important addition because research is rarely useful if it stays inside the person who generated it.

A practical use case

One use case I had in mind is interview preparation.

Before interviewing with a startup, instead of only reading the company's homepage, you could run the company through GTM Radar and quickly get context around:

  • what the company does
  • how it positions itself
  • who its competitors are
  • what's happening in the market
  • who the important people are
  • what questions or talking points might be worth bringing up

The same workflow could also be useful for sales research, competitive research or preparing for a customer conversation.

What I learned

The biggest thing I learned from building this wasn't about any individual provider.

It's that having access to many tools is only useful when you can turn them into a workflow.

You don't want to give someone five different dashboards and tell them to figure it out.

You want:

Input → research → useful output.

That's the part I'm most interested in exploring with AI agents.

What's next?

There are still plenty of things I'd like to improve:

  • Better company-level signals
  • More reliable extraction fallbacks
  • More GTM-specific workflows
  • Better sharing and collaboration
  • More ways to turn the research into an actual action

The project is also available with the setup and deployment instructions in the README.

If you're building with AI agents, I'm curious:

What company research workflow would you automate first?

and you can check out here also: https://x.com/nehaaaa_6/status/2092170249919746306

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