Use Case 1: After-Hours Coverage

Before Voice AI, Matic relied on third-party call center vendors to handle after-hours calls. Performance was poor — missed calls, inconsistent messaging, and lost opportunities.

With Voice AI, Matic launched an after-hours AI phone agent to handle all incoming after-hours traffic.
Available 24/7 all year round, the AI phone agent collects basic contact and insurance info and schedules follow-up calls.

This ensured:

• High-intent customers were never lost overnight.
• Representatives had all necessary context before following up.
• Every caller received a consistent, branded first touch — no matter the time or call volume.

Use Case 2: Appointment Confirmation & Rescheduling

Scheduling delays and missed calls were costing Matic valuable opportunities. Agents couldn’t always dial out exactly at the scheduled time, and answer rates dropped when calls came late.

Voice AI solved this by handling scheduled call follow-ups automatically. The AI voice agent calls the customer exactly on time, confirms they’re still available, reschedules if needed, and transfers the call to a licensed human agent.

Results:

• 3,000–4,500 scheduled calls handled every month.
• 85–90% success rate in transferring calls to licensed agents.
• Consistently higher answer rates than human-led calls, due to precise call timing.

“In Q1, we handled just about 8,000 calls with the AI operator bot. What we found, and we ran this as an A/B test, was that we actually saw a higher rate of answer rate using the bot. We attribute that a lot to the fact that the bot can make the call at the exact minute of that appointment being scheduled.”

Use Case 3: Data Collection & Lead Qualification

Quote intake was one of the most repetitive and time-consuming parts of Matic’s call operations. Agents were spending 7–9 minutes per call gathering details before even getting to the consultative part of the conversation.

With Voice AI, that entire process is now automated. The AI phone agent collects all 20–30 required data points, flags any disqualifying factors, and hands off only eligible leads to licensed agents.

Impact:

• Average data collection time dropped from 9 minutes to ~6 minutes.
• Agents save time by avoiding calls with ineligible or unqualified leads.
• The system can be easily updated as product or eligibility rules evolve.

Implementation & QA

Matic’s telephony team led the integration of Voice AI. The initial build took just 1–2 months, including foundational integration work with Twilio, API endpoints, and internal prompt handling systems. Once the groundwork was in place, new AI use cases were rolled out rapidly in 1–2 sprint cycles.

By early 2025, more than 60% of the team’s call operations development was focused on AI.

Quality Assurance Included:

• Weekly QA sampling: A dedicated team member reviews 150+ calls per week.
• Automated call reviews: An internal prompt checks transcripts for flow adherence.
• Continuous iteration: Engineering, QA, and ops meet regularly to refine flows based on live feedback.

“There were five or six improvements we made just last week based on QA insights. This work is ongoing and essential.”

Voice AI's Impact

Matic’s use of Voice AI phone agents has produced meaningful, measurable results across the board:

• 8,000+ calls handled by AI in Q1 2025 across all use cases
• 85–90% transfer success rate for scheduled appointment calls
• Higher answer rates for AI calls vs. human calls (from A/B testing)
• Call handling time reduced by ~3 minutes in data intake flows
• ~50% of low-value tasks automated and reassigned
• 90 NPS maintained throughout automation rollout
• 80% of customers complete AI-handled calls without asking for a human
• Cost per policy and cost per transfer significantly reduced (exact metrics pending)

Takeaways

1. Start Small, But Smart

Matic began with a low-complexity, high-impact use case: after-hours call handling.
The workflow was simple and the benefits were immediate — collect basic info, schedule a callback.
This gave the team early wins, measurable ROI, and internal confidence to build momentum.

2. Never Compromise on Customer Experience

Because Matic operates through co-branded partnerships with mortgage lenders, every interaction is a reflection of another company’s brand. That meant AI couldn’t just be functional — it had to feel human. From voice quality to response accuracy, customer trust remained non-negotiable.

3. Validate with Data, Not Gut

Before scaling automation across the board, Matic ran controlled A/B tests to compare AI performance against human agents. In the case of appointment confirmations, the AI phone agent actually outperformed humans on answer rate.

4. Invest Upfront to Move Faster Later

The team spent the first 1–2 months laying a strong technical foundation: integrating with Twilio, building a flexible prompt infrastructure, and aligning internal QA processes.
This early investment enabled rapid iteration later, with new use cases launching in just 1–2 sprint cycles.

5. Repurpose, Don’t Replace

Matic didn’t approach AI as a headcount reduction strategy. Instead, they focused on repurposing human agents to handle higher-value interactions.
Higher value tasks like cross-sell opportunities and deeper consultative conversations ramped up, allowing Matic to provide deeper value for customers while maximizing ROI.

“We’re not replacing people — we’re giving them better things to do.”

Conclusion

Through their phased implementation of Voice AI's voice automation platform, Matic has successfully transformed their customer operations, reducing costs while maintaining excellent customer experience metrics.

By automating repetitive tasks, they've freed their human agents to focus on higher-value activities like consultative selling and relationship building.

For B2B leaders considering similar automation initiatives, Matic's experience demonstrates that thoughtful implementation of AI voice agents can deliver measurable operational benefits without sacrificing customer satisfaction.
As AI voice technology continues to advance, companies that embrace these tools strategically can gain significant competitive advantages in efficiency, scalability, and customer experience.