The Challenge

This Austin-based financial services company operates in a high-stakes world. With roughly $200 million in annual revenue, every conversation matters for them. Their customers are everyday Americans making serious decisions about their retirement savings.

Their business model is straightforward but intense. Heavy marketing spend generating thousands of inbound leads, and an in-house team making a large volume of outbound calls every month.

“We were doing about 50,000 outbound phone calls per month,” their COO told us.

Everything was handled internally by their in-house call center agents. Since their demographic skewed older and trust was everything, it was functionally a requirment to hire and manage a team of U.S.-based sales reps, causing them to deal with attrition, training, and the constant balancing act between talk time and dial volume.

The bigger bottleneck, though, was speed and distribution.

“Salesforce is great at a lot of things,” he said. “But it’s not built for what we do. It’s not good at distributing leads in a timely fashion.”

Speed-to-lead is critical in their business. The faster a prospect receives a call after submitting information, the higher the likelihood of engagement. But relying on humans meant inevitable delays. Leads piled up. Capacity fluctuated. And scaling meant hiring more people, which came with cost, risk, and operational complexity.

At the same time, the team knew AI was coming for their industry.

“It would be stupid of us not to look at this technology,” he said candidly. “AI is everywhere. Why wouldn’t we try to leverage it in our business?”

They experimented with another provider first. It could dial. It could connect calls. But according to their COO, the voice quality and qualification process fell short.

“You can hire anybody to make a phone call,” he said. “But can you serve up a more qualified prospect to my closers? That’s the vision.”

They needed more than a robo-dialer. They needed an intelligent front end to their sales engine.

The Solution

After continued research, this company decided to partner with Bland to build an AI dialing agent designed specifically for their outbound sales process.

The goal was not just to automate calls. It was to rethink the structure of their team.

“My vision is that I’m no longer going to have openers,” he explained. “There will be no more openers. I want to have 10 closers who are well paid and experts in this field, being fed by a better qualified lead via Bland.”

Instead of replacing humans outright, Bland became a capacity multiplier. The AI agent could:

• Call instantly when leads arrived
• Dramatically increase total dial volume
• Transfer qualified prospects directly to closers
• Operate continuously without fatigue or inconsistency

The implementation was not rushed. The team took a measured approach, launching with lower-cost leads while they refined scripts, workflows, and handoffs.

Within two months, the system was live and fully integrated into their outbound workflow. Call patterns were connected to their CRM. Zapier flows were adjusted. Qualification logic was refined. The AI began feeding live prospects directly to their sales team.

Importantly, the rollout was done thoughtfully. Their customer base skews older, and trust is critical. They had real discussions about whether prospects would accept an AI as the first point of contact.

“Is that psychological barrier too great?” he asked. “That was something we really thought about.”

By starting with controlled traffic and iterating carefully, they were able to validate performance without risking core revenue streams.

The Outcome

The story here is not just about revenue. It’s about speed and capacity.

Within just two months of going live, the AI-driven outbound engine generated $154,000 in additional revenue.

And this was done while primarily working lower-cost, lower-volume lead sources as the system was being refined.

More importantly, the company effectively doubled its dialing capacity without doubling headcount.

The AI agent never waits for lunch. Never calls in sick. Never slows down at the end of the day. It calls instantly. It transfers instantly. It creates surface area for revenue that did not exist before.

Even more compelling, the team sees the long-term trajectory.

“You’re just going to be adding capacity in a way that functionally gets people faster,” he said. “The sky’s the limit there.”

And because they launched in just 60 days, they were able to test, learn, and start compounding improvements almost immediately.

The Future

The outbound dialing use case is only the beginning.

The company is now exploring expanding Bland into inbound after-hours coverage, operational workflows, and even SMS.

“This is going to be a three to five year cycle for me,” he said. “Partnering early and getting this right now means we’ll pick fruit from the tree later on.”

Their long-term vision is clear:

• AI handles initial qualification
• Elite closers focus only on high-value conversations
• Capacity scales without linear increases in payroll
• AI becomes the unified front door across channels

In just two months, they proved that AI dialing can go live fast and produce real revenue. Now they are building toward something much bigger: a scalable, AI-powered inbound and outbound engine designed to grow with them for years to come.

And they did it without betting the business. They did it deliberately, strategically, and quickly.