Aliee and Onepoint: The Convergence of Cognitive AI and Contact Center That Redefines Customer Experience

The contact center industry in Latin America is at an inflection point. For two decades, the model was relatively stable: hire agents, train them on scripts, measure them by handle time and first-contact resolution, and replace those who leave with new hires in a turnover cycle that in Mexico averages between 60% and 80% annually depending on the sector. Costs rise, quality is inconsistent, and customers, in 2025, expect something entirely different.

Gartner projects that by 2026, 75% of organizations will have adopted some form of AI in their customer service operations. But there is an important difference between "adopting AI" —adding a chatbot in front of the IVR— and transforming the contact center operating model with cognitive intelligence. That difference is exactly what separates Aliee Onepoint CACP from any other solution on the market (Gartner, "Future of Customer Service Technology," 2024).

The problem with the traditional contact center augmented with basic AI

The first generation of AI in contact centers was additive, not transformative. Companies added chatbots at the front of the digital channel, added voice synthesis to their IVRs, and added real-time sentiment analysis to supervisor dashboards. The result was a more complex system with the same underlying problems:

• Customers still had to repeat their information every time they switched channel or agent.
• Transfers between bot and human agent remained disruptive and frustrating.
• Human agents still lacked the full customer context at the moment they took the call.
• Personalization remained superficial: "Hi, [customer name]" is not cognitive personalization.

Forrester reports that 67% of Latin American customers experience at least one frustrating interaction with a company's contact center per month, and 43% have switched providers in the past year, citing poor service quality as the main factor (Forrester, "Customer Experience Index LATAM," 2024). The problem is not a lack of technology: it is the wrong technology.

The architecture of Aliee Onepoint CACP

Aliee Onepoint is SLM Sistemas' Contact Center Cognitive Autonomous Platform. Unlike conventional contact center platforms —which are essentially call-routing systems with analytics bolted on— Onepoint was designed from its foundational architecture around three cognitive engines:

Engine 1: Empathic Voice

Onepoint's Empathic Voice Engine goes beyond word recognition. It analyzes in real time the semantic content, tone, pace, and emotional state of the customer to build a picture of the interaction's context. A customer who speaks quickly, uses emotionally charged words, and interrupts frequently is in a very different state from one who speaks calmly and asks specific questions. The engine automatically adjusts the response —in tone, speed, level of detail, and priority— for each state.

Engine 2: Intent and Reasoning

Once the Empathic Voice Engine has processed the signal, the Intent and Reasoning Engine determines what the customer wants to accomplish (their explicit intent) and what they actually need (their implicit need). The difference is crucial: a customer who calls to report an unrecognized charge doesn't just want the charge explained. They want resolution. The reasoning engine identifies that distinction and orients the response toward resolution, not explanation.

Engine 3: Real Execution

The third engine is where Onepoint definitively distinguishes itself from the competition: it has real execution capability. It can not only answer questions; it can act. It can check the status of an order, process a return request, update customer data, escalate a ticket with all the contextual information pre-filled, or generate a summary of the interaction for the CRM system —all autonomously, without human intervention in the cases that fall within the defined scope.

The Aliee-Onepoint integration: where the magic happens

The platform's real competitive advantage lies not in each product separately, but in their integration. Aliee acts as the long-term cognitive brain that knows the customer, and Onepoint acts as the real-time interaction system. When a customer makes contact through any channel —voice, chat, WhatsApp, email— Aliee has already built their full context before the conversation begins:

• Interaction history across all channels (not just the most recent).
• The status of their active products, contracts, or services.
• Previous unresolved interactions and pending commitments.
• AML risk profile (if applicable, for financial institutions).
• Value segment and churn probability calculated in real time.
• Channel, timing, and communication-style preferences learned from previous interactions.

That context is presented automatically to the agent —human or cognitive— who takes the interaction. The human agent no longer has to ask "How can I help you?" after verifying identity: they already know, with high probability, why the customer is calling, and can begin the conversation at that point.

The human-AI collaboration model

A frequent concern among contact center operations directors is that AI will displace their agents. The reality is more nuanced —and more interesting. The Aliee-Onepoint model does not eliminate human agents: it reclassifies them.

High-complexity, high-emotional-load, or high-value customer cases are handled by human agents who have, thanks to Aliee, all the information needed to resolve on first contact. Low-complexity, high-frequency cases —balance inquiries, status checks, basic data changes— are handled autonomously by Aliee, freeing agents to focus on the cases where human judgment and genuine empathy are irreplaceable.

The result: more satisfied agents because they work on cases that require their real skill, more satisfied customers because they receive more consistent quality service, and operations directors with metrics that improve on every front.

IDC estimates that organizations implementing cognitive human-AI collaboration models in their contact centers report:

• A 34% increase in customer satisfaction (CSAT) in the first 12 months.
• A 28% reduction in average handle time (AHT).
• A 41% reduction in agent turnover (agents work on more interesting and less repetitive cases).
• A 22% increase in first-contact resolution (FCR) (IDC, "Human-AI Collaboration in Contact Centers," 2024).

Metrics that matter to executives

For the Operations Director, the indicators that Aliee Onepoint directly impacts are:

Cost per contact: With cognitive automation of 60-70% of low-value cases, total cost per contact is reduced by between 35% and 50% in the first 18 months of full operation.

NPS and CSAT: Cognitive personalization and first-contact resolution have a direct, measurable impact on customer satisfaction. Organizations with NPS below 30 that implement Aliee Onepoint have seen increases of 15 to 25 points in 12 months.

Revenue generation: Aliee can identify cross-sell and up-sell opportunities during service interactions, presenting them to the agent at the precise moment and with the estimated conversion probability. This turns the contact center from a cost center into a revenue lever.

The contact center of the future is already available. It does not require replacing all of your current infrastructure: Aliee Onepoint integrates with existing telephony platforms, CRMs in operation, and any system of record the customer has. The transformation begins from day one of operation.

— Andrés Lozada, Executive Director | Sumato

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