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WhatsApp is no longer just another channel. With more than 3 billion active users in 2025 and a volume of more than 100 billion daily messages, this application has grown exponentially to become the communication standard. For many companies, WhatsApp is directly “the place” where their customers ask, claim, buy, or cancel, and where they also expect an immediate response, as if you were on the other side of the mobile phone.
The challenge arrives when the volume grows, unpredictable peaks appear, and the human team cannot and should not live putting out fires. In that scenario, WhatsApp ai agents help to absorb the load because they automate from end to end, perform specific tasks, and transfer the conversation to a human agent without losing information.
Below, we tell you what they contribute, how they are implemented with Inconcert, and why Inconnect and Inagent is the ideal combination to manage WhatsApp integrally.
What are WhatsApp AI agents exactly?
We should not confuse an ai agent with chatbots of previous generations or basic virtual assistants, which are limited to following a predefined script:
- A bot usually moves by rules and flows: if A happens, respond B.
- An AI agent is designed to operate in real cx scenarios: it interprets the intention, maintains the context, makes decisions within limits, and can execute actions by connecting to systems.
Therefore, it is important to distinguish them from similar concepts such as basic virtual agents, or solutions marketed as “agents” that are actually just re-labeled workflows (yes, the classic AI agent washing that eventually impacts operational efficiency).
In this regard, the cx industry is increasingly discussing the agentic AI approach: agents with a certain degree of autonomy, reasoning capabilities, and access to tools (such as crm, erp, ticketing, or knowledge bases).
To understand why these agents can maintain more natural conversations, it is essential to distinguish between three components:
- NLP: the umbrella term for language processing.
- NLU: the component that interprets intent and context.
- NLG: the part that generates coherent responses.
Thanks to this combination, the agent does not simply match keywords: it understands what the customer means and responds in a more human way.
How to implement ai agents on WhatsApp with Inconcert
An AI agent is implemented well when operation and customer experience are worked on simultaneously. This is the step-by-step process to deploy it without friction.
1. WhatsApp Business Platform registration and management (with Inconcert as a BSP)
Before discussing automation, the channel must be secured. It is standard to operate on the WhatsApp Business Platform and, in this initial stage, having Inconcert as a BSP (Business Service Provider) not only accelerates the process and reduces common frictions (validations, templates, numbering, and compliance) but also saves time and provides a more guided approach, with a team that understands the complexities of the channel and helps avoid them from the beginning.
This initial phase typically includes the following steps:
- Creation and validation of the WhatsApp Business account and its initial configuration.
- Certification and activation of the number and the setup of the business profile.
- Template management and best practices to reduce rejections and ensure operational stability.
- Compliance support to ensure the channel grows without issues (especially during campaigns or peak periods).
2. The knowledge base: the brain of the WhatsApp AI agent
On WhatsApp, inquiries often arrive with little context and cover multiple topics, which may lead the agent to provide generic responses or escalate too early. A robust knowledge base is what enables the AI to respond with confidence, remain consistent, and know exactly when to request data or when to transfer the conversation.
During this phase, manuals, company policies, and FAQs are uploaded, providing the system with the necessary information to respond accurately and maintain a consistent experience at all times.
3. Integration with the ecosystem
An isolated agent is merely an informant. To be truly effective, it must connect to the company systems. Through integration with your CRM, ERP, or ticketing software, the agent can check balances, schedule appointments, or modify orders in real-time, becoming an active member of the team.
WhatsApp is now a key channel in CX: this guide explains how to manage it efficiently and scalably.
Access here
4. Natural language training
Instead of building rigid trees of “if A happens, then B,” training focuses on the agent understanding intent and context while acting under clear rules. To achieve this, guardrails are defined (what it can do, what it cannot, when to request data, and when to escalate) and tests are performed with real WhatsApp examples: incomplete messages, subject changes, complaints, or urgent matters.
Thus, instead of forcing the customer to follow a closed path, the agent adapts to the conversation and resolves issues more naturally, without losing control or consistency.
5. Activation and supervision: measure, review, and improve
Launching the WhatsApp AI Agent is not the end, but the beginning of controlled learning. During this phase, it is verified that the tone remains aligned with the brand, that it responds consistently, and that it transfers conversations when appropriate.
The supervision functions of Inagent and the conversation history are tools used to monitor the activity of each AI agent. You can intervene in real-time, but also analyze the development of each conversation. In the case of AI agents for WhatsApp, this also allows for the modification of WhatsApp HSM messages.
With these insights, you can update the knowledge base and optimize responses, ensuring the agent resolves more cases with greater precision week by week.
Discover all Inagent features and technical specifications in this datasheet. Access here
What happens if the AI agent cannot resolve the issue on WhatsApp?
In a real operation, there will always be conversations that need to be passed to a person: due to complexity, sensitivity, or because the customer simply wants to speak with someone. The important thing is that this change of hands is natural and does not involve any loss of information, so that the service continues to flow. Therefore, two key aspects are usually managed:
- Derivation to the contact center at the right time: the agent identifies when it is no longer advisable to continue automating and activates the transfer to avoid blocks, unhelpful responses, or unnecessary back-and-forth.
- Handover with full context: the conversation reaches the human agent with the history, the detected intent, and what has already been attempted, so that the person can continue from where it left off (without asking the customer to repeat everything).
Analytics and control for high-volume WhatsApp operations
When volume is high, automating is only the first step. What truly keeps the operation stable is having visibility into what is happening to improve with data: which contact reasons are repeated, at what points the agent hesitates, what triggers transfers, and how the experience changes after each adjustment. In Inagent, this control is supported by two very practical levers:
- Analytics panels in Inagent: these allow for a quick check of the agent performance (which queries it resolves, at what points it transfers to a human, which contact reasons are growing, and how results evolve over time) and provide performance statistics by channel, including WhatsApp. This makes it easier to detect clear optimization opportunities and prioritize where to act first.
- Recording and analysis of conversations for continuous improvement: reviewing real interactions helps to identify knowledge gaps, adjust rules, refine the tone, and reduce avoidable transfers. In practice, every conversation leaves useful signals so that the agent responds better in future interactions.
Inconnect and Inagent: comprehensive management of the WhatsApp channel
When Inagent (to automate and resolve) and Inconnect (to orchestrate the omnichannel operation) are combined, WhatsApp stops being a separate chat and starts functioning as a channel with control, traceability, and continuity when it is necessary to transfer to a person.
Key WhatsApp functionalities in Inconnect
If the goal is to operate WhatsApp with volume (and without continuously switching tools), Inconnect provides especially useful advantages:
- Native connection and secure startup: Inconnect integrates WhatsApp as a contact center channel and, furthermore, Inconcert acts as an authorized WhatsApp Business Service Provider, which helps to implement the channel with guarantees.
- Use of advanced functions without leaving the platform: daily operations can be managed from Inconnect taking advantage of templates, flows, and automations, without having to jump between solutions.
- Messaging prepared to sell and serve better: the possibility of creating conversational templates and configuring personalized automated messages (with variable texts) facilitates both customer service and commercial follow-up.
- Routing and contact center control: to avoid ending up with an unmanageable WhatsApp channel, automatic distribution assigns interactions based on skills, business data, or segmentation, and relies on real-time monitoring and reporting to maintain service levels.
The Mentius case: when theory turns into results
When a commercial operation grows and does so in a sector as competitive as Telco, the challenge is usually not to serve more, but to sell faster and with more control, without saturating the team or leaving opportunities behind.
That is exactly what Mentius, a BPO specialized in Telco sales, addressed by integrating Inagent (AI agents on WhatsApp and the voice channel) with Inconnect to automate interactions and coordinate work between AI and human agents.
In figures, the impact has been noted on three very clear fronts: efficiency, speed, and conversion:
- Speed: the average handling time was reduced from 18 to 10 minutes, which accelerates the commercial rhythm and improves productivity.
- Efficiency: the team gained capacity, as the number of interactions per agent increased by 55%. This was possible thanks to the fact that AI agents absorb volume and filter interactions better.
- Conversion: the conversion to sale on inbound WhatsApp reached 90%, with conversations guided by AI agents and handover to human agents when the closing requires it.
Discover how Mentius accelerated its commercial operation in telco with Inagent and Inconnect from Inconcert. Read more
When is it advisable to incorporate AI agents on WhatsApp into your operation?
Ultimately, for AI agents to work well on WhatsApp, it is advisable to answer three questions before launching them:
- What minimum volume justifies AI agents? More than a magic number, the clue is usually found in repetition: when the same tasks are repeated daily and consume resources, automation begins to have an evident return.
- How are quality and brand tone managed? By defining a voice, rules, limits, and supervision. The AI agent on WhatsApp should not improvise your identity: it should execute it with consistency, conversation by conversation.
- What happens if the AI agent fails? It should not leave the customer in a dead end. The ideal scenario is that it knows how to ask for help, transfer with context, and leave traceability so that the system improves.
If you want to see it applied to your operation, it is as simple as taking the step: speak with a specialist and launch your AI agents on WhatsApp.
