Strategy, process design and implementation for AI adoption. upmkt.one helps organisations turn AI opportunities into working solutions, with people, governance and measurable business value at the centre.
AI adoption for your business.From strategy to implementation.
“You cannot adopt AI while keeping processes designed 30 years ago”
Paula Suárez · Director of Technical Solutions, Microsoft Latin America
Let’s talkStart with the way work is designed
This is a starting point for examining how work gets done: what creates value, what causes delays and what should change. Experience is an asset; the aim is to put it to better use.
Services
Support across the adoption process
The right starting point depends on the business problem, the data available and the people involved. Each engagement defines a practical scope and a way to measure progress.
Strategy and process redesign
Understand the operation, identify constraints and prioritise opportunities by expected value, feasibility and exposure to risk. The outcome is a roadmap with a clear first step.
Design, development and implementation
Design and test the workflow, build the required components and connect them with the systems that support the operation. Acceptance is based on agreed criteria.
Adoption and organisational change
Prepare the people who will operate, supervise and lead the change. Roles, training and everyday practices are part of the work.
Governance, quality and cost control
Define responsibilities, evaluate output quality and monitor costs and exceptions. Controls should match the consequences of each decision.
Method
Build in stages and learn from use
A diagnosis establishes the baseline. A prototype tests the proposed workflow with the team. Implementation advances through agreed milestones, with acceptance criteria and follow-up after delivery.
Understand and establish a baseline
The starting point is the operation: the task, the people, the information and the constraints. Baseline measures are agreed before claims about improvement are made.
Test the proposed workflow
Users examine a working representation before wider construction. Feedback changes the design while adjustments are still practical.
Implement and accept by milestones
Each stage defines responsibilities, acceptance criteria and evidence of completion. The engagement sets the schedule rather than assuming a universal delivery interval.
Chile
Data protection in Chile
Preparation for Law 21.719 connects policies with everyday operations. The work can include data mapping, responsibilities, supplier review and technical controls, coordinated with the appropriate legal specialists.
Status checked on 18 October 2026.
Own technology supporting delivery
Command Center brings a technology foundation to selected engagements. Its role is to support project context, document work and control workflows. The solution is designed around the client’s operation and existing systems.
Perspectives
A place for professional judgement
Perspectives brings together signed reflections on AI, business, work and current affairs. Each contribution makes its author and sources visible and leaves room for informed disagreement.
Alex Karp y el futuro del trabajo: el valor de pensar diferente
La visión de Alex Karp abre una reflexión sobre el valor de los oficios y la neurodivergencia en la era de la IA. Amplificar, Automatizar y Reimaginar permiten explorar cómo reconocer ese talento y crear las condiciones para convertir sus capacidades en resultados.
Diego Pérez F.22 October 2026 · 11 min◌ Society and educationESLa educación como motor de integración y movilidad social
Una propuesta para conectar aprendizaje, trabajo remunerado y movilidad durante toda la vida, ampliar las oportunidades y fortalecer la confianza social sin debilitar la protección.
Diego Pérez F.19 October 2026 · 26 min◉ AI governance and dataESHuman in the loop no basta: medidas concretas para mitigar riesgos
Dónde detener la automatización, qué pedir al controlador y cómo cruzar aprobaciones, bloquear inconsistencias y escalar alertas al supervisor.
Diego Pérez F.11 October 2026 · 7 min◎ AI architectureThe Twitter Paradox: Connecting People While Rewarding Polarisation
When we design policies and architectures to mitigate bias in LLMs and AI tools, we need to translate principles into system behaviour.
Diego Pérez F.25 September 2026 · 2 minWhat would you like to improve?
Bring a process, a recurring problem or an initiative that needs a clearer path to implementation. The first conversation establishes the context and whether a useful next step exists.
Let’s talk