Regal vs SIERRA

1. Best-in-class voice AI
2. Data-driven personalization and easy A/B Testing
3. Low variable pricing

Sierra offers conversational agents that primarily operate through webchat, with voice as a secondary option. Sierra expanded its capabilities to include voice interactions, allowing AI agents to manage phone calls with lifelike quality.
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Regal was built for voice interactions, delivering AI agents with low latency and human-like qualities to create natural, engaging conversations that drive customer satisfaction. With Regal, companies can easily build voice agents personalized to their brand voice, customers, and use cases. The Regal Agent Builder offers a variety of best in class voice options, supports 20+ languages, and provides powerful customization tools all in an easy to use interface, enabling teams to quickly design, test, and optimize every voice interaction at scale.

Sierra provides businesses with the  tools to build AI agents that can access information and perform tasks, contributing to efficient customer experiences. Sierra allows customer experience teams to monitor performance using analytics to track trends and identify opportunities for improvement. However, Sierra does not include native A/B testing capabilities, conversation intelligence, campaign orchestration, or an agent desktop — which can make it difficult for teams to rapidly test ideas, optimize customer journeys, or manage complex workflows at scale.

Regal makes it easy for CX teams to personalize every interaction and continuously improve performance. With 40+ native integrations, Regal AI Agents connect to your customer data, automate repetitive tasks, update systems in real time. They can seamlessly transfer calls to human agents with full context operating in a true omnichannel capacity. 

Built-in A/B testing tools let business users test and optimize performance in real time — fostering a culture of rapid iteration and continuous improvement. Regal also includes advanced capabilities like conversation intelligence, campaign orchestration, and an agent desktop to help CX teams operate smarter at scale.

Sierra offers outcome-based pricing, which can be appealing in industries like retail, where success is often measured by completed transactions or resolved inquiries. This model aligns costs with performance, meaning businesses only pay when a specific result is achieved. This pricing model requires predefining success metrics and agreeing on pricing structures for every interaction. As AI costs decline over time, brands may find themselves locked into pricing that doesn’t reflect ongoing efficiency gains.

Regal offers consumption-based pricing—charging per minute of AI agent usage. This approach provides complete transparency and flexibility, allowing businesses to scale AI interactions without lengthy pricing negotiations. Unlike outcome-based pricing, which often benefits the vendor more than the customer, Regal’s per-minute model ensures companies can take advantage of AI’s rapidly declining costs. As AI technology becomes more efficient, businesses using Regal automatically see cost savings without renegotiating contracts. Plus, this structure enables teams to continuously test and optimize AI workflows without worrying about unpredictable pricing changes, making it easier to drive ROI.