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Belgium 10-09-2026 Squad Only Physical english

Building the Infrastructure AI Needs: From computer and data access to scalability, cost control, and operational readiness.

AI is moving from pilots into operational use, and the infrastructure question is becoming more concrete. The challenge is deciding what needs to be built, expanded, controlled, or delayed as usage grows. Three pressure points usually appear first. - Compute capacity requires careful planning: teams need enough GPU, cloud, or specialised processing power, while keeping utilisation and cost under control. - Data movement becomes more demanding: AI needs access to data across systems, with latency, security, integration, and quality managed from the start. - Operational control becomes essential: monitoring, access rights, resilience, cost visibility, and ownership need to scale with usage. The working question is simple: how do we support AI at scale while keeping infrastructure efficient, governed, and financially sustainable? If you are working through these choices, let’s compare approaches with others facing similar constraints.

Belgium 15-09-2026 Squad Only Virtual english

Turning AI Pilots into Daily Workflows: How to move from experimentation to adoption by redesigning work, ownership, controls, and habits.

AI pilots are easier to launch than to embed into daily operations. The challenge is changing how work happens once AI becomes part of decisions, tasks, handovers, and controls. Three pressure points tend to decide whether adoption holds. - Workflow fit matters: AI has to enter the flow of work as part of the process. - Ownership needs to be clear: someone must own the process, the controls, the exceptions, and the outcome. - User trust has to be built: people need to know when to rely on AI, when to challenge it, and when to escalate. The working question is simple: how do we move AI from promising pilots into daily work while keeping clarity, accountability, and risk control? If this is part of your current reality, let’s compare choices, constraints, and lessons learned.

Belgium 17-09-2026 Country Members Physical french

Les Rencontres: CTO: Le Saint Graal?

Pendant longtemps, le TCO donnait une impression de contrôle. On investissait, on amortissait, on optimisait. Les coûts étaient visibles, relativement prévisibles, et structurés autour d’une logique claire entre CAPEX et OPEX. Ce modèle ne suffit plus à expliquer où va réellement l’argent. Aujourd’hui, une part croissante des dépenses IT ne repose plus sur ce que l’on possède, mais sur ce que l’on consomme: des tokens générés par l’IA des agents qui exécutent des actions en continu des outils SaaS qui se multiplient dans les équipes du cloud qui s’adapte en permanence à l’usage Le coût ne disparaît pas, mais il devient plus diffus, plus dynamique, et souvent plus difficile à attribuer, à expliquer, et à maîtriser. C’est là que des approches comme le Technology Business Management, ou TBM, redeviennent particulièrement utiles: non pas comme un exercice de reporting supplémentaire, mais comme un moyen de relier concrètement les dépenses aux services, aux usages, et aux décisions. Et c’est là aussi que la question du “Saint Graal” revient, mais sous une autre forme. Vous vous demandez peut-être: Comment garder de la maîtrise quand la dépense dépend du comportement, des usages, et parfois même de systèmes autonomes ? Comment piloter l’équilibre CAPEX/OPEX quand le cloud, le SaaS et l’IA déplacent progressivement les coûts vers des modèles variables ? Quels coûts restent encore trop souvent hors radar: ressources métier, formation, support, intégration, sécurité, gouvernance ? Et surtout, qu’est-ce qu’un “bon TCO” veut encore dire quand il faut le mettre en regard d’objectifs parfois plus stratégiques, plus longs à mesurer, ou plus difficiles à quantifier: qualité de service, résilience, agilité, expérience utilisateur, capacité d’innovation ? Ce sont précisément ces questions qui seront au cœur de notre rencontre: une discussion ouverte entre pairs, ancrée dans la réalité du terrain, pas pour débattre de modèles idéaux, mais pour comprendre comment chacun tente, concrètement, de mesurer, d’attribuer et de reprendre le contrôle, sans réduire la valeur d’un choix technologique à son seul coût.

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How Hello Sugar reached a 66% automation rate with our hybrid solution

Hello Sugar wanted to scale their waxing franchise without growing their reception staff – all while offering higher quality CX. With Ultimate’s hybrid automation solution, this process couldn’t have gone more smoothly.

Hello Sugar at a glance

The customer

Hello Sugar is the fastest growing Brazilian wax and sugar salon in the U.S.

The market

Hello Sugar serves beauty-conscious customers across the U.S.

The support team

Their support team consists of 20 receptionists who handle requests via Zendesk.

The channels

Hello Sugar offers customer support via SMS.

The situation

Hello Sugar was looking to double the number of stores – without doubling their receptionists' workload.

The solution

Ultimate's hybrid combination of gen AI and conversation design helped Hello Sugar hit a sweet spot between empathetic, personalized, and scalable support.

Getting started with Ultimate

Trying to double the number of stores in their franchise within the year – without growing their support team – may sound like the makings of a sticky situation. But what sets Hello Sugar apart in the beauty and wellness space is their tendency to be tech savvy. They knew that the best way to scale was to automate. And while a lot of other AI providers sugar coat their automation capabilities, Ultimate’s automation solution proved to be the real deal.

Hello Sugar’s CTO, Austin Towns, was instantly impressed by the generative AI technology behind UltimateGPT and quickly began automating common intents about salon services and pricing. With the help of Ultimate’s hands-on customer success team and a seamless integration with Zendesk - who recently acquired Ultimate to scale the partnership - they enhanced the quality of their support by combining ultra-personalized service with near-instant response times.

With the freedom and flexibility of generative AI, their bot also delivers precise info about the location of salons to lost customers as well as empathetic responses for first time waxers – all in perfect brand tone of voice. Meanwhile, the precision and control of manual conversation design enabled them to automate their entire appointment booking process. Now, Hello Sugar boasts a 66% automation rate thanks to our hybrid automation solution.

"We currently have 81 salons and are going to grow to 160 this year – without growing our reception staff. And with automation, we’re able to do that while offering way better CX and getting higher reviews."

Austin Towns
CTO, Hello Sugar

Automation rate: 66%

Monthly savings$: 14K

Agent hours saved: 200

AI use case spotlight #1: Hello Sugar’s journey to +66% automation

Hello Sugar wanted an AI provider that could go beyond the traditional dialogue builder. Ultimate’s hybrid approach that integrates the precision of conversation design with the freedom and flexibility of generative AI delivered on this promise.
UltimateGPT has enabled them to quickly automate FAQ style questions about services provided and how to prep for an upcoming appointment. And conversation design helped them automate intents like booking appointments, as they can use API integrations to confirm location and generate a booking link for their customers.
Taken together, they have reached a 66% automation rate – with rave reviews about their CX from customers.

AI use case spotlight #2: Knowledge base optimization for better CX

Hello Sugar also succeeded in honing the powers of a well-designed knowledge base to enhance the capabilities of UltimateGPT.
By compiling a knowledge base replete with information on the details of location of each salon around the country, their generative AI-powered bot can provide extremely precise directions. Customers are also left with the feeling that they’re speaking to a human receptionist, thanks to the bot's natural-sounding tone of voice (TOV).
As a result, Hello Sugar harnessed the power of generative AI to deliver ultra-personalized and empathetic support to customers within seconds and at scale.

The success story

Instant Zendesk integration

Ultimate’s hybrid automation solution seamlessly integrated with their existing CRM so they were able to start automating common queries straight away.

Industry beating results

As a tech savvy business within the beauty and wellness space, Hello Sugar has been able to offer improved CX even as they double their number of salons – all while saving $14K in agent costs per month.

Hybrid automation solution

With our hybrid solution, Hello Sugar was able to combine generative AI and conversation design to reach an automation rate of +66%.

Improved customer experience

With the help of AI, Hello Sugar is able to attend to customer queries in a matter of seconds. Thanks to UltimateGPT, they’re able to do so in a way that integrates empathy and on-brand TOV into each interaction.

Next on their automation journey

Hello Sugar plans on continuing to find more use cases for AI to improve CX, such as by expanding their APIs to reduce manual work for receptionists.

For example, they want to harness the capabilities of API integrations for booking and rescheduling appointments to expand the capabilities of what their bot can do when responding to these requests.

They plan to audit all existing intents to find more opportunities to leverage UltimateGPT.

Technologies

Ultimate: Chat automation Zendesk: A CRM Platform

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