If your focus is elsewhere, it’s easy to overlook just how many support tickets follow familiar patterns. Yet someone still has to read each of them, investigate the customer’s environment, and prepare a response before moving on to the next one. Repeat that dozens or hundreds of times every day and it becomes clear that the biggest challenge isn’t solving difficult problems, but finding enough time for the people who actually should be solving them.
When our CEO sat down with Alexis Garcia, Director of Operations and Technology at Gigacore, the conversation quickly moved past the usual AI narrative that begins and ends with faster replies. What emerged instead was a story about reorganizing an entire support operation around the idea that technical specialists should spend their day solving technical problems, not repeatedly handling work that software can now do remarkably well.
The Cost of Repetition
Every support department has its own version of déjà vu. The same password questions, the same DNS confusion, and countless other routine requests that are rarely difficult on their own, but together consume an astonishing amount of time.
At Gigacore, the international hosting provider that grew out of Ecuador’s Nodored, first-line requests often followed those familiar patterns. Even when the issue itself was straightforward, a support agent still had to open the ticket, review the customer’s account, inspect the relevant environment, and prepare a response. In more technical cases, the investigation naturally took even longer.
Alexis described just how much of the team’s attention this absorbed:
That time slipping away in small portions, scattered across dozens of routine tickets that each appear harmless on their own, is one of the less visible costs of support work.
Konrado.AI changed that starting point. Because it operates within Gigacore’s server infrastructure and has access to the relevant technical data, it can do more than recognize a familiar question. It can investigate many customer issues, understand what is happening in the account, and provide an appropriate response before a human agent needs to become involved.
Today, it effectively serves as Gigacore’s first-line support agent, handling both routine and technical inquiries while passing cases to the human team when additional expertise is genuinely required.
Trust Is Built Long Before Deployment
Support software doesn’t get a second chance to make a first impression. The moment it starts talking to customers, every response becomes part of the company’s reputation. That’s why choosing an AI assistant starts with trusting the people building the software that’s about to speak on your behalf.
Gigacore didn’t have to build that trust from scratch.
That familiarity gave Konrado.AI something most new products spend months trying to earn: trust before the first deployment.
It also made the alternative much clearer. Instead of continuously expanding the first-line support team to keep pace with repetitive inquiries, Gigacore could build a support model that was easier to scale without adding another person every time the queue became busier.
Where the Biggest Gains Actually Came From
Hosting providers usually measure the impact of automation through familiar metrics: response times, ticket volume, staffing needs, and running costs. Gigacore saw improvements in each of those areas, but Alexis described something more interesting than a collection of isolated numbers.
The individual benefits began reinforcing one another.
As routine first-line requests stopped occupying engineers, the number of tickets requiring human escalation dropped dramatically. Customers no longer had to wait for an available agent to inspect common issues, because Konrado.AI could respond and begin investigating almost immediately. Faster initial support reduced pressure on the queue, while fewer repetitive requests gave the technical team more room to focus on cases that genuinely required analysis or intervention.
The Impact in Numbers
70%
Reduction in first-line tickets requiring human escalation
16h→30 min
Reduction in average first-response time
Konrado.AI delivers automated support insights that Gigacore uses to demonstrate the quality of its service with transparent, measurable results. Those reports have become another way to transform everyday support performance into a genuine competitive advantage.
The change also produced direct cost savings.
This was not simply a matter of replacing one cost with another. It gave Gigacore a much more manageable way to deal with a type of work that had previously grown alongside ticket volume.
The impact reached beyond the support queue itself. Gigacore discontinued direct human technical support through WhatsApp and redirected customers to its ticket system, where Konrado.AI now serves as the first point of contact. Besides delivering exceptionally fast initial responses, the change brought every support conversation into one place, improved traceability, and made every issue easier to review later.
What began as a way to handle repetitive inquiries more efficiently ended up improving the structure of the entire support process.
More Than a Better Reply
Many AI support tools are still judged primarily by the quality of the text they generate. That matters, of course, but for Gigacore the most valuable part of Konrado.AI happens before the response is written.
Instead of relying on plain documentation or predefined response libraries, it starts by investigating the issue itself. By collecting the technical context behind each request, it builds responses on what is actually happening rather than on what usually happens. That distinction is easy to miss from the outside, but it changes the role AI can realistically play in customer support.
That’s how Konrado.AI moves beyond educated guesses. It can inspect the data available within Gigacore’s infrastructure, identify many common issues, and prepare a relevant response based on what it finds.
While this gives the team confidence that customer requests are being handled consistently, Alexis never suggested automation should take over every conversation:
Knowing when not to answer is just as important as knowing how to answer. The smartest decision AI can sometimes make is recognizing where its role ends and human expertise begins.
For Gigacore, success is not defined by eliminating every human interaction. It comes from ensuring that every ticket ends up in the right hands at the right moment.
Where Human Expertise Matters Most
Previously, a large part of the team’s day was spent answering questions they had already answered many times before. Today, that same capacity can be directed toward developing new solutions, managing infrastructure, improving server performance, strengthening security, and resolving complex technical cases.
Automation has changed where human expertise is needed, not whether it is needed. It is now focused on the work where it creates the greatest value.
Konrado.AI handles repetitive first-line support and performs much of the initial investigation, while Gigacore’s specialists become involved when the situation requires deeper analysis or direct intervention. That creates a clearer division of responsibility without forcing customers to choose between speed and access to real technical knowledge.
Alexis summed up the broader impact in one sentence:
That is the difference between automating a task and redesigning a whole process. While the former may save a few minutes here and there, the latter changes what the team is able to do with the rest of the day.
Looking Beyond the Ticket Queue
There is an old assumption in hosting that growth eventually means hiring more people to answer more tickets. Gigacore’s experience suggests otherwise. The real breakthrough is not answering tickets faster, but making sure your best engineers are no longer occupied by the questions they know by heart.
Konrado.AI gives hosting companies a practical way to separate repetitive work from work that truly benefits from human expertise. Customers receive help sooner, routine issues move through the system without unnecessary delays, and technical teams regain the time and focus that first-line support consumes.
We would like to sincerely thank Alexis Garcia for taking the time to walk us through Gigacore’s support operation with such openness and attention to detail. Being invited into that process step by step gave us a much clearer view of how Konrado.AI works in practice, not as an abstract AI feature, but as a working part of the support team’s daily operations.
It is a genuine pleasure to share Alexis’ perspective with our community, and knowing that Konrado.AI has become such a natural part of Gigacore’s support model gives us every reason to feel sincerely proud of this collaboration and excited about where it may lead next.
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