Servicios al cliente omnicanal
Plataforma de conversación cognitiva multilingüe y multiempresa
Cobertura de servicios al cliente omnicanal
Our LLM-based platform Beth has been designed to facilitate the creation and implementation of next-generation intelligent virtual assistants to serve corporations and their stakeholders in various industries (including heavily regulated ones such as Banking, Insurance and Telecoms).
Based on the revolutionary ChatGPT Large Language Model, Beth transforms the way clients and employees interact with the company, access its services and execute operations. Built on unique, proprietary architecture, Beth effectively utilizes a set of deep-learning LLMs developed by OpenAI to bring unparalleled coprehension of human language pushing their application boundaries further. These models have numerous advantages over traditional NLP models, such as understanding long and complex sentences, capability to generate natural, structured and coherent text and understanding instructions in the form of prompts.
The enormous potential and the advantages of LLMs over tradition NLP, make their application in customer service immensely appealing. However, the nature of deep neural networks used, raise concerns over the degree of control and predictability of the so called 'black box' output. These concerns can be summarized as:
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Vulnerability to bias: LLMs can produce discriminatory outputs due to biased data, leading to potential losses in revenue or customer dissatisfaction.
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Lack of transparency: LLMs operate as a "black box," making it difficult to determine why a specific output was generated, raising concerns in high-stakes decision-making scenarios.
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Hallucination: Over-trained LLMs may generate nonsensical or inaccurate information, leading to misinformed decisions, compliance risks, difficulty in customization, inefficient use of resources, and potential harm to brand reputation.
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Limited programming interface: The current API only allows communication via natural language, making it challenging to collect data or impose constraints on text completion.
These challenges must be addressed to fully harness the potential of LLMs in a corporate context and regulated fields, such as financial services, telecoms and even health care.
Cobertura de servicios al cliente omnicanal
Ablera's LLM-based platform for Intelligent Virtual Assistants (IVA) addresses the challenges posed by taming LLMs and effectively bring them under control. The platform, designed for corporate business, focuses on three main strategies:
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Intercepting LLM thoughts by using specifically designed prompts and labeling user intent,
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Eliminating hallucinations by using GPT labels to detect user intent and overwrite GPT messages with predefined messages
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Token optimization, which involves separating logically isolated tasks to reduce tokens and improve efficiency. These approaches help avoid hallucinations, stabilize conversations, and maintain the conversational skills of the Assistant.
Canal transaccional multilingüe para conversación humana
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Mejora la disponibilidad de agentes en vivo para ayudar a los consumidores con consultas más complejas
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Brinda asistencia de navegación a los consumidores con tareas generales y específicas que incluyen, entre otras, Cotización, FNOL, Centro de asistencia / reemplazo de llamadas, Corredores, Agentes.
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Servir como un comprador activo, incluida la creación de procesos competitivos que aumentan la experiencia del Cliente
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La Plataforma Beth proporciona un sólido soporte basado en ML para la gestión del diálogo y amplios flujos de conversación.
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