3 min read

May 27, 2025

How Qualified Scaled with an AI Workforce of 35+ Agents

250%

increase in output

$10m

pipeline in 6 months

50+

agents across the org

Qualified, an agentic marketing platform, has reimagined their revenue operations by building a sophisticated AI workforce. The company partnered with Relevance AI to build 35+ specialized AI agents that generated a further $7 million in pipeline and $500,000 in closed revenue over just six months.

The Challenge: Manual Processes Holding Back Growth

Qualified was stuck in the typical scaling trap:

  • Revenue targets growing faster than team capacity
  • Manual tasks consuming valuable time across all levels
  • Expensive, hard-to-scale human-intensive processes and repetitive work like data cleanup, research, and outreach

Even their AI Go-to-Market Operations Manager was skeptical about automating complex BDR work, having been one himself for two years. But when Relevance took 40-50 BDR tasks and returned an AI agent performing at human-level quality in just one week, the skepticism vanished.

We were just overloaded by manual processes across our business. There was just a lot of manual tasks, data cleanup and repeatable processes that I knew there was an opportunity to automate - Kieran Snaith, SVP of Revenue Operations

The Solution: Deep Integration with Relevance AI

After evaluating 60 different vendors, Qualified chose Relevance AI for three key reasons:

  1. Deep integration - Works with existing tech stack and custom processes (not just generic automation)
  2. No technical barriers - Subject matter experts can train agents directly, no engineering required
  3. True partnership - Hands-on support and training throughout implementation

Unlike other solutions that force you to change how you work, Relevance adapts to your unique business processes.

What stood out the most about Relevance is its ability to integrate not only into our tech stack but into our customized processes - Kieran Snaith

The Results: $7M Pipeline in Six Months

Quantified Impact:

  • $7 million in S1 pipeline generated
  • $3.5 million in S2 pipeline created
  • $500,000 in closed revenue achieved
  • 35 AI agents now handling diverse business functions

Quality & Efficiency:

  • AI-generated content often outperformed human-created versions
  • 24/7 operation with consistent high-quality output
  • Breakthrough moment: 3 meetings booked automatically while manager was traveling

The system proved itself when their Manager received three meeting bookings in one afternoon - all handled completely by AI agents.

I was honestly impressed a lot of the emails sometimes were better emails than even I could put together - Rich Campbell

Training the AI Workforce

Simple Training Process:

  • Share your existing processes and frameworks
  • Define job requirements and goals
  • Agents immediately operate within your structure
  • No need to change how your business works

Current Scale:

  • 35 specialized AI agents handling different functions
  • 25 agents managed as part of regular workflow
  • 150+ AI tools supporting various business needs
  • Ongoing partnership ensures continuous improvement

The key difference: instead of generic automation, these agents learn your specific way of doing business.

Here's our processes, here's how to think about your job, here are your goals, and immediately that agent is operating on that framework - Kieran Snaith

What's Next: Enterprise-Wide AI Adoption

Qualified's success has opened their eyes to AI possibilities across the entire organization. They're expanding beyond sales and marketing into recruiting, finance, and other departments.

The company is now looking at their entire customer lifecycle to identify where AI can add value at every step. With agents becoming top of mind across all departments, Qualified is building toward a comprehensive AI workforce that amplifies human capabilities throughout the business.

Sky's the limit here. We're looking at our entire customer lifecycle and every business department within Qualified, asking ourselves, where can we deploy AI? - Kieran Snaith

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