PH Deck

The current situation involves creating voice agents manually, which is time-consuming and requires expertise in voice technology. The drawbacks include high costs associated with development and deployment, lack of natural-sounding speech, and slow integration processes.

Users are currently facing challenges in building efficient voice AI agents due to the need for complex coding skills. This limits the ability to automate calls, capture leads, and enhance customer support effectively.

Users face high operational costs and inefficiency in traditional contact centers using human agents. Drawbacks include high costs and inefficiency.

Businesses relying on human agents for customer support face high operational costs, limited availability (not 24/7), and language barriers, leading to delayed resolutions and reduced customer satisfaction.

Users struggle to find suitable and authentic AI agents for their specific needs, leading to inefficiencies in operations, task automation, and delivery of complex solutions.

Developers looking to create voice agents face long development times and complexity, which can lead to slow and less human-like interaction experiences.

Users rely on traditional customer service teams limited by human availability, language barriers, and scalability issues, leading to delays and inefficiencies in handling sales, support, and multilingual interactions.

Users face time-consuming and inflexible development processes when creating AI agents, struggling with challenges in integrating various LLMs and workflows using traditional coding methods.

Users manually control machinery without AI integration, leading to inefficient processes and higher error rates due to lack of real-time automation.

Users manually calculate costs and latency for voice AI agents across multiple providers (STT, LLM, TTS), leading to time-consuming, error-prone comparisons and lack of integrated cost-latency optimization.