about us
about us
about us
The team that integrates AI into your company's operations
We are a team of data engineers, data scientists, and business consultants passionate about bringing AI to the operational complexity of businesses.
VOLIS
VOLIS
VOLIS
Our mission
Taking AI from theory to practice, integrating it into the real processes of organizations.
We integrate AI directly into business operations, connecting data, processes, and teams to support critical decisions at the right time.
We do this through robust, secure, and scalable solutions designed for complex operating environments.
Bringing order to chaos.
Bringing order to chaos.
Bringing order to chaos.
Bringing order to chaos.
TEAM
TEAM
TEAM
Where do our talents come from
Our specialists comes from large global companies, bringing solid experience and a strategic vision that elevates the quality of our deliverables.
LEADERS
LEADERS
LEADERS
Leadership team
Corporate
Corporate
Corporate
Corporate
Investors and Advisors
Letter
CARTA
CARTA
How we see the world
At Volis, we work at the intersection of data architecture, operational ontology, artificial intelligence, and real business transformation. Our perspective is not theoretical, it is shaped by the direct experience of working with executive teams in the field, solving real business problems, and building systems that work under operational pressure.
Along this path, we've learned that the real challenge lies not in the lack of data or the absence of technology, but in how the reality of the business is (or isn't) represented in the systems. That's where ontology becomes central: how the organization defines, structures, and relates its assets, processes, people, and decisions.
We saw firsthand where AI creates value, and where it doesn't.
AI is an accelerator, not a strategist
Artificial intelligence is extremely effective at making decisions within a well-defined framework. It scales processes, compresses complexity, replicates patterns, and identifies efficiencies. But it doesn't create strategy, define priorities, or exercise judgment. These remain human responsibilities.
Without a clear model of reality, without an ontology that represents how the business actually works, AI becomes just another layer of abstraction. The risk is not AI replacing people, but disconnecting them from operational reality. Once implemented, it generates noise, automates wrong decisions, and creates artificial trust in systems that don't understand the context.
Our goal is the opposite: to use AI as a capacity multiplier, always anchored in a rigorous understanding of the business.
Executive capacity is the real bottleneck
Most organizations don't fail because of a lack of data, but because of a lack of actionable clarity. They have dashboards, reports, and indicators galore, but little real visibility into what's happening on the ground, right now.
Critical business knowledge is fragmented, delayed, or translated into metrics that serve reporting purposes, not decision-making. The result is a silent erosion of executive capacity.
Our work begins by rebuilding that capability. We structure data around real operations, decision flows, and causal relationships that drive the business, not around abstract KPIs. We create models that enable leaders to see, understand, and act continuously, promoting daily operational improvement instead of slow review cycles.
Software should follow the business, not the other way around
Traditional enterprise software prioritizes standardization over nuance. It's designed for administrative scale, not operational adaptability. But the organizations we work with don't need generic systems, they need platforms that reflect their specific logic, constraints, and way of operating.
At Volis, we design systems based on business realities. Ontology is the starting point: it defines what exists, how it relates, and how it evolves. Data becomes infrastructure, structured from the ground up, integrated across functions, and accessible in near real-time, allowing the software to adapt to the business, not the other way around.
Our approach
We work with organizations ready to move beyond incremental automation and embrace systemic change. This path begins with clarity: clean, well-defined, and semantically coherent data. From there, we build tools, workflows, and decision models that enable continuous improvement and responsible use of AI.
We take responsibility for the impact. We structure our projects in clear phases, POC, Pilot, and Scale, where each stage is validated by concrete results before moving on to the next.
We don't just sell software or data products. We build organizational capacity. The transformation we seek is not measured in presentations or proofs of concept, but in strategic leverage, decisional clarity, and sustainable operational results.
G.
Gonçalo Fernandes
CEO & Founder
CARTA
How we see the world
At Volis, we work at the intersection of data architecture, operational ontology, artificial intelligence, and real business transformation. Our perspective is not theoretical, it is shaped by the direct experience of working with executive teams in the field, solving real business problems, and building systems that work under operational pressure.
Along this path, we've learned that the real challenge lies not in the lack of data or the absence of technology, but in how the reality of the business is (or isn't) represented in the systems. That's where ontology becomes central: how the organization defines, structures, and relates its assets, processes, people, and decisions.
We saw firsthand where AI creates value, and where it doesn't.
AI is an accelerator, not a strategist
Artificial intelligence is extremely effective at making decisions within a well-defined framework. It scales processes, compresses complexity, replicates patterns, and identifies efficiencies. But it doesn't create strategy, define priorities, or exercise judgment. These remain human responsibilities.
Without a clear model of reality, without an ontology that represents how the business actually works, AI becomes just another layer of abstraction. The risk is not AI replacing people, but disconnecting them from operational reality. Once implemented, it generates noise, automates wrong decisions, and creates artificial trust in systems that don't understand the context.
Our goal is the opposite: to use AI as a capacity multiplier, always anchored in a rigorous understanding of the business.
Executive capacity is the real bottleneck
Most organizations don't fail because of a lack of data, but because of a lack of actionable clarity. They have dashboards, reports, and indicators galore, but little real visibility into what's happening on the ground, right now.
Critical business knowledge is fragmented, delayed, or translated into metrics that serve reporting purposes, not decision-making. The result is a silent erosion of executive capacity.
Our work begins by rebuilding that capability. We structure data around real operations, decision flows, and causal relationships that drive the business, not around abstract KPIs. We create models that enable leaders to see, understand, and act continuously, promoting daily operational improvement instead of slow review cycles.
Software should follow the business, not the other way around
Traditional enterprise software prioritizes standardization over nuance. It's designed for administrative scale, not operational adaptability. But the organizations we work with don't need generic systems, they need platforms that reflect their specific logic, constraints, and way of operating.
At Volis, we design systems based on business realities. Ontology is the starting point: it defines what exists, how it relates, and how it evolves. Data becomes infrastructure, structured from the ground up, integrated across functions, and accessible in near real-time, allowing the software to adapt to the business, not the other way around.
Our approach
We work with organizations ready to move beyond incremental automation and embrace systemic change. This path begins with clarity: clean, well-defined, and semantically coherent data. From there, we build tools, workflows, and decision models that enable continuous improvement and responsible use of AI.
We take responsibility for the impact. We structure our projects in clear phases, POC, Pilot, and Scale, where each stage is validated by concrete results before moving on to the next.
We don't just sell software or data products. We build organizational capacity. The transformation we seek is not measured in presentations or proofs of concept, but in strategic leverage, decisional clarity, and sustainable operational results.
G.
Gonçalo Fernandes
CEO & Founder
Join us
We are always looking for exceptional talent who want to be part of our mission. If you are passionate about technology, data, and transforming operations through artificial intelligence, join our talent pool.