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What happens when you bring together four of the most innovative companies in contact center AI—and ask them to show, not tell?

Contact Center AI Demo Day delivered just that: an interactive, expert-led event showcasing real-world ways to combine AI agents, speech technologies, training simulators, Auto QA, and performance intelligence. But beyond the demos, this session offered something deeper—an honest conversation about how AI elevates human agents, connects data to coaching, and turns operations into outcomes.

Moderated by Scott Logan, CMO at AmplifAI, the panel featured leaders from:

• Sanas – Tiffany O’Malley, Head of Partnerships
• SymTrain – Dan McCann, Founder & CEO
• Quiq – Michael Hartsog, VP of Global Alliances‍
• AmplifAI – Adrian Valenzuela, VP of Sales

Who This Session Was For

If you’re navigating a crowded AI marketplace and need to make real decisions for your contact center, this session was built for you. Specifically:

• Operations and support leaders trying to reduce churn and improve productivity
• CX owners and execs looking to automate without compromising the customer experience
• Training and QA teams eager to level up coaching, feedback, and new hire readiness
• Tech buyers wondering how to tie multiple AI tools together into a coherent strategy

1. AI Elevates the Agent, Not Just the Experience

The panel opened with a powerful throughline: AI isn’t just for customer-facing automation—it’s for making your agents better. From real-time coaching prompts to confidence-boosting voice modulation, every demo reinforced how AI helps people perform better, feel more supported, and stay longer.

Adrian Valenzuela from AmplifAI emphasized that today’s agents handle increasingly complex issues—and AI’s job is to reduce their manual load while surfacing simple, tailored performance insights that improve every interaction.

Meanwhile, Tiffany O’Malley from Sanas showed how AI voice transformation isn’t about changing who agents are—it’s about helping them communicate clearly and be heard, leading to more confident conversations and higher CSAT.

2. Auto QA and Coaching: Two Halves of a Smart Performance Strategy

It’s not enough to evaluate calls—you need to act on them.

Adrian walked through how AmplifAI pairs automated QA with role-specific coaching to create a continuous improvement loop. Auto QA gives full visibility into every interaction across every channel—not just a 2% sample. That data is then connected directly to coaching workflows, which are tailored by metric, behavior, and agent need.

The innovation? Supervisors don’t need to dig through dashboards. The AI highlights who needs help, why, and what action to take—whether that’s a coaching moment or a recognition opportunity. Even more, managers can track how effective each supervisor is at improving specific KPIs through coaching—coaching the coach, not just the rep.

3. Understanding the Four Main Categories of AI for Your Customer Experience

Scott Logan outlined the four essential categories of contact center AI that leaders should understand:

1. Customer-Facing AI Agents: Tools like Quiq’s agentic AI agents handle repetitive tier-1 issues, guide users through decisions, and escalate intelligently. They’re built to reduce effort and create personalized service at scale.‍
2. Performance Management & Coaching AI: AmplifAI helps unify fragmented data across CCaaS, CRM, QA, and surveys—then transforms it into action plans for agents, supervisors, and managers. Think real-time visibility and AI-curated coaching actions.‍
3. Speech & Communication AI: Sanas removes language friction, improving agent confidence and customer understanding. The result? Lower AHT, fewer escalations, and stronger human connection.‍
4. Training Simulation AI: SymTrain converts real call data into repeatable, role-specific simulations. It’s like batting practice for agents—targeted, trackable, and tied to performance KPIs.

Together, these categories build a complete ecosystem: anticipate needs, resolve with AI, evaluate automatically, and improve continuously.

4. Start with Your Business Challenge, Not the Tool

Each panelist returned to the same principle: define the outcome, then match the tech.

Michael Hartsog of Quiq emphasized the importance of aligning AI use cases with customer journey touchpoints and business objectives—whether that’s removing friction, increasing conversion, or improving efficiency.

Dan McCann from SymTrain added that you don’t need a “perfect” data set to start—just the right data tied to the right KPI. And whatever you’ve got—call recordings, QA data, supervisor notes—they’ll use it to generate targeted training simulations.

The takeaway: You don’t need to boil the ocean. Start with the pain. Pick the metric. Choose the tool.

5. AI That Works Together Works Better

The future isn’t about buying a single platform—it’s about making your platforms work together.

SymTrain, Sanas, Quiq, and AmplifAI each emphasized interoperability as a success factor. When your QA system talks to your coaching platform, when your voice AI feeds better data into training, when your agent assistant learns from real conversations—you unlock exponential value.

It’s not about “checking the AI box.” It’s about using the right tool for the right job—and connecting them all to your business reality.

🧠 Expert Quote to Remember

“You don’t just coach the agent anymore—you coach the coach, using QA data that’s always on. That’s how AI helps everyone level up.”

— Adrian Valenzuela, VP of Sales, AmplifAI

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