Tu WhatsApp puede hacerlo todo. Tu proveedor actual no

Un primer caso de uso en producción suele tardar entre 4 y 6 semanas desde la firma del contrato.

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Durante este tiempo, lo que pedimos a tu equipo es concreto: una sesión semanal de trabajo conjunto, acceso a las personas que conocen los sistemas con los que se integra el agente (CRM, ERP, base de conocimiento) y un interlocutor que decida sobre el alcance funcional.

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Después del go-live, el ritmo baja a una reunión cada dos semanas para revisar métricas y priorizar la siguiente iteración.

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Acotamos el planteamiento es deliberadamente para que el proyecto avance rápido. El objetivo es salir a producción en ese plazo de 4 a 6 semanas con un primer caso de uso que aporte valor, y luego seguir añadiendo complejidad y avanzando en fases posteriores.

An AI agent is not a rule-based chatbot or a simple system of predefined responses limited by a static "decision tree" that breaks down as soon as the user deviates from the script.

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Unlike a passive system that simply "reads answers from a manual," the AI agent is capable of recalibrating itself to maintain the process's resolution. That is, if it encounters an obstacle, it adjusts its strategy and continues working until the case is solved.

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Nor should it be understood as a generic AI "black box" operating uncontrolled over the internet; on the contrary, it is a system shielded by strict guardrails that anchors exclusively to your knowledge base to guarantee reliability and eliminate any risk of invention or hallucination.

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The difference between a rule-based chatbot and an AI agent represents a complete paradigm shift: it goes from following a pre-written script to having the ability to reason and execute.

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Generally speaking, a rule-based chatbot is like an operator who can only read phrases from a pre-printed manual, while an AI agent is like a smart employee who is given a goal, access to company tools, and rules of conduct, and it manages the task autonomously.

LLMs alone are probability engines that can "hallucinate" (invent answers based on what is most likely linguistically, not on reality). At Hubtype, we use 4 key mechanisms to prevent fabrications and inappropriate behaviour:

1. We connect the agent to reality (with tools and knowledge bases). To prevent the agent from inventing data, we eliminate the need to "guess" and give it the ability to "see" the real data.
2. We add security barriers (guardrails), which act as an AI-powered "moderation filter" that reviews messages before processing or responding to them.
3. We define instructions and roles. We establish the agent's personality and objective through System Prompts.
4. We advocate for a hybrid model combining rules and AI, where the creative or conversational aspects are handled by AI, but the strict processes (such as payment confirmation or legal terms) are managed through rule-based workflows or decision trees. This ensures that "if the user says A, the system responds B" without any margin of error.

In short: AI is not left "unleashed." It is confined to an environment where, to obtain data, it must use official tools; to communicate, it must respect security guardrails; and to behave, it must follow strict instructions.

The short answer is NO. You don't need to change your current CRM or software to implement AI agents with Hubtype. In fact, Hubtype's architecture is specifically designed to integrate with and enhance the tools you already use, not to replace them.

To avoid chaos, Hubtype uses a centralised architecture called the "AI Super Agent Orchestrator."

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This system acts as an "orchestra conductor," ensuring that each agent intervenes only when necessary, keeping the conversation smooth and coherent. The orchestrator decides who speaks next based on intent, while the helper agents silently process data.