The challenge
Scaling logistics support without losing accessibility or control
At BSL, growth did not arrive as orderly progress. Instead, it arrived as things usually do in logistics: with peaks, emergencies, and constant changes in pace. For a time, the operation held up thanks to pure human traction, using memory, coordination, and a lot of manual work to ensure each client received a response on time.
The problem is that this model has a ceiling. With rising volume, the service began to fall behind exactly during critical moments. The team suffered from longer queues, more abandonments, less traceability, and a dangerous feeling of always being one step behind. In parallel, outbound efforts made it difficult to contact people, and when contact was achieved, it did not always translate into results.
Everything pointed to the need to automate recurring inquiries, establish operational governance, and ensure journey continuity. This was necessary so the service could withstand peaks with the same solidity with which BSL wanted to continue growing.
What exactly did they need?
- To improve inbound accessibility even during moments of high demand and to make outbound more effective by improving contactability through segmentation, time windows, and dialing rules.
- To reduce operational friction by decreasing manual searches, after-call work, and rework.
- To consolidate traceability and context in every interaction, regardless of the channel.
- To automate frequent inquiries on voice and WhatsApp without it becoming a robotic experience.
- To ensure a smooth handover to a human agent with the history available to continue without repeating information.
- To take decisions based on real-time data using panels and alerts that allow action before the service suffers.
- To scale with a sustainable model where the workforce is no longer the only lever for growth.
The Solution
More agile, traceable, and scalable support with Inconcert technology
The solution was built on a very practical idea: centralizing voice and digital attention, automating the most repeated inquiries, and reserving the time of the human team for cases that truly require judgment.
To achieve this, Ayesa accompanied the project from the beginning with operational alignment and execution discipline. Inconcert provided the technological layer and a phased deployment so that the implementation fit the daily reality.
The implementation relied on a hybrid model with two solutions from the Inconcert ecosystem:
- Inagent, the voice and text AI agent, oriented to resolve frequent inquiries autonomously, such as shipment status, tracking, common incidents, delivery or pickup information, confirmations, and FAQs. It provides immediate transfer to a human agent when the case requires it and always includes the full context.
- Inconnect, the omnichannel contact center software that centralizes attention on WhatsApp and calls. It allows the application of routing rules and provides access to indicators and analytics.
Furthermore, it includes integrations with the internal systems of BSL, such as the CRM and shipment management system. This unifies information, avoids duplication, and accelerates resolution. The objective was to evolve toward a more coherent and scalable service model where quality is maintained even when volume increases.
In logistics, the customer does not forgive uncertainty. What we value most about this project is traceability and context: now each interaction arrives with the necessary information to truly resolve the issue.
Gloria Cardona
General Manager at BSL
1. Intelligent automation of logistics inquiries
With Inagent, BSL can automate the most repetitive inquiries and absorb peaks without saturating the human team. When a case is sensitive or complex, the interaction is scaled to an agent with the full history, preventing the customer from having to repeat everything.
Where is the improvement noticed?
- There is more autonomous resolution for repetitive inquiries, which reduces delays and waiting times.
- The attention is expandable by channel and hours without depending on increasing the team to cover every peak.
- Scaling to a human happens with context to accelerate management and improve the experience.
The most important change was to stop depending on reinforcements to sustain peaks. With omnichannel capabilities and AI, the operation gained control and stability without the workforce being the only lever.
Paula Andrea López Castaño
Director of Ayesa Colombia
2. A connected and traceable operation with Inconnect
With Inconnect, the control room based on Excel documents, hand-written notes, and whiteboards became connected and centralized. The voice and WhatsApp operation is managed from a single platform with defined rules, queues, and routing. It provides end-to-end traceability for each interaction. This allows the company to organize the attention, prioritize better, and maintain consistency even during moments of high demand.
Additionally, Ayesa and BSL use Inconcert technology to follow the operation in real time and convert that visibility into a routine of continuous improvement. Through dashboards and alerts, they supervise key indicators of accessibility and performance with breakdowns by time slot, channel, or skills and typology. This data allows them to detect deviations in time, find the root cause, and quickly adjust rules and campaigns to sustain the service without improvisation.
Where is this improvement appreciated?
- Total traceability of each interaction: what was requested, what was done, and where it stands.
- Fewer duplications and more speed thanks to integration with the CRM and the shipment management system.
- Supervision and continuous improvement with panels and operational analysis used by Ayesa and BSL to optimize sustainably.
We went from managing with intuition to managing with data. Having a record of indicators and visibility by typology and time slot allows us to act before the service suffers.
Paula Andrea López Castaño
Director of Ayesa Colombia
The conclusion
from improvisation to data-based control
With the incorporation of Inconnect and Inagent, and the coordinated work between the final client, the BPO, and Inconcert, BSL moved from manual management to a much more controlled model. The combination of omnichannel reach and conversational automation allowed for ordering queues and rules, reducing daily friction, and reserving the time of the human team for tasks that require judgment.
However, the jump was not only technological. The difference was marked by the three-way collaboration and constant iteration between Inconcert as the provider, Ayesa as the specialized BPO, and BSL as the final client. This cycle allowed the model to be refined quickly and sustained over time.
Ultimately, the important thing is that BSL now has a model that adapts. It automates recurring tasks, maintains context when derived to a human agent, and allows for adjusting rules and capacity with speed. It is a customer experience prepared for the real pace of the last mile.
