Observe launches VoiceAI agents to automate customer call centers with realistic, humanlike voices that don’t interrupt

Observer.ai Officially, VoiceAi agents presented a solution designed to automate daily client interactions in contact centers.

The company’s latest addition to the company’s AI-Driver’s Talk Exploration Platform, VoiceIi agents aim to improve their customer experience while reducing operating costs.

Observe, with this release

The company’s solutions set now includes enterprise-class VoiceIi agents, real-time agent help tools, quality monitoring, agent training and autoqa for business concepts.

To automate daily

VoiceIi agents of the observation.AI are set to manage a wide range of customer service requests to more complex conversations than often asked questions.

They are built with a combination of AI models and partnerships with large AI providers such as AI models and large language models (LLM) at home.

“This is the ensemble of a very small model,” Jain said. “For example, we have a special model for disclosure, a model for detection, a model for turn detection, a model, etc.”

The goal is to lighten the burden on human agents that allow them to focus on higher valuable interactions.

As with Swapnil Jain, the CEO and observer co-founder, the last video call interview in Venturebeat said: “Do we really need human agents for such use?” ”

Jain said that companies often call the account balance or call the EU as the main tasks such as a password-interactive connection, which can now manage effectively.

For customers, it means to overcome long retention time and prevent messages that are disappointed to press multiple buttons or require a human agent.

Voice AI space, Openai’s newly released GPT-4o-transcription Family and unlikely soluors are increasingly crowded with protection models such as family and eleventabs. Why does anyone observe agents on them?

In short: ease of specialization and use. Providers are set to “chips and play” with a job or special sound apps, instead of using APIS raw sound AI models, or special voice applications, Obseis.Ai platform with existing workflows and operations.

Thus, GPT-4O and other LLMS are the proposal of raw AI opportunities, Jain and observer, customer service for work flows.

In addition, unlike the traditional sound AI assistants, the observer VoiceIi agents have specially designed for contact centers. The system combines various AI technologies, including:

• Automatic speech recognition (ASR): Transforms the spoken language in real time into the text.
• Talk from the text (TTS): Responds to a person similar to a similar voice.
• Special AI models: Customer service settings specialize in numbers, turns and intervals.

Jain has known that one of the main problems of facing AI agents know that a client is actually speaking. “When do you know that the AI ​​agent can start processing and ceases to speak customer?” asked. “Sometimes my sentence is over and I started a new one. Sometimes I just stop talking. How do you know the difference?”

Providing smooth conversations between the observation.ai, AI and customers, developed special home models that solve these nuances.

Place fast while integrating product support and tracking systems

The main advantages of observers are the ability to connect without problems with existing enterprise systems.

With the time of time, the company has developed pre-built integrations in more than 250 platforms in the leading telephone, CRM and Sale, CRM and Sale, Zendesk and Servicenow.

This approach allows enterprises to quickly apply voice adventures to enterprises. Although the EU placement sometimes takes months, observe.

“It’s not a model of professional services that we take six months to make something for you,” Jain said. “We are coming, we take two weeks and works to configure the product.”

Safety and matching on the front

Considering the sensitivity of customer interaction, the observer.ai established his solution with enterprise-class security. The company provides certificates including GDPR, HIPAA, Hitrust, SOC2 and ISO27001.

When the use of voice biometrics in the past, Jain noted that he did not trust them for security concerns for the observer. Instead, the system follows traditional identification methods such as checking social security numbers or account information.

In addition, observe.

“You cannot trust individual speech samples for authentication in today’s world,” Jain said. “We work with enterprises to configure the same security rules they use for human agents.”

To save $$$ via Automation

The price model of the observation.AI is based on working more than a clear use.

Expenditure depends on the complexity of interaction (such as calling) more than business tasks (such as insurance requirements).

According to Jain, enterprises can save between 70-80% of 70-80% on customer service expenditures compared to human agents.

Early enterprise success stories

Companies using VoiceAi agents have already seen significant developments. Emmanual Noyola, the director of favorable patient services, stressed the impact of his team: “Our VoiceAi agent, 95% intends to more than one intention, so our customer maintenance group can focus on more complex cases.”

Analyze each conversation and observe.AI’s platform, ensuring accuracy and compatibility, continuously cleans the performance of AI agent. Enterprises can also use the outs of both AI and Human Agents and Improvements.

One of the main problems of AI-based customer service, protects accuracy when preventing unexpected answers.

Jain acknowledged these concerns by referring to the former AI Missteps in automating customer service. “The main thesis of the main thesis behind the grade announcement of this enterprise has a very high rod in the confidence of the answer.” “If our response trust is less than a certain threshold, the AI ​​agent is better not to engage.”

To confuse AI automation with human experience

Launch of VoiceAi agents is a great step towards what the future is observed as the center of the autonomous contact.

As AI continues to grow, the company focuses on creating a seamless customer experience and creating solutions that confuse automation with human experience.

“Since our worship was established seven years ago, we have created a platform that is unparalleled by the contact center talks,” Jain said. “It is a logical step to support the noise to present a consistent, secure, high-quality customer experience between both noisy and AI agents and every touch point to automate our noises.