In this exclusive interview, Phyllis Scholl, Chairwoman of the Board at Unique, sits down with René Schmidli to discuss what it means to build an AI-ready board and how agentic AI is already transforming the financial industry.
René Schmidli: Phyllis, Unique, where you serve as Chairwoman of the Board, has a name that is as distinctive as it is confident. At first glance, one notices terms like “platform” and “AI factory,” along with references to “agents.” What exactly does Unique offer?
Phyllis Scholl: Hello René, happy to explain. Unique is a specialized platform for agent-based AI solutions that optimize business processes in the financial industry, in other words, a vertical AI provider.
We serve banks, insurance companies, and private-equity firms with a fully finance-specific, secure, compliant, and easily integrable solution.
Our focus is on innovative, responsible, and safe AI development, following international and industry-specific governance and ethics standards.
Unique supports processes such as investment analysis, KYC, onboarding, and due diligence, always under strict data protection and compliance requirements.
More than 40 well-known financial institutions in Switzerland, the EU, and the U.S. are already using Unique’s solutions. The platform is built around a clear governance framework that defines responsibilities between Unique and its clients to manage both risk and benefit effectively.
René Schmidli: Let’s stay with Unique’s strategic approach, which also defines how clients in the financial sector can capture value from AI. Of course, there are other paths, such as in-house development with a hyperscaler or using AI features through existing enterprise platforms like Salesforce (now with Agentforce), IBM Watson, or SAP AI. Why does Unique see its own approach as the best one, and when might these alternatives make sense?
Phyllis Scholl: Unique’s AI solutions are designed specifically for the financial industry. They already include features for regulation, data protection, compliance, and KYC, and come with ready-to-use use cases like onboarding and anti-money-laundering.
Developing internally with a hyperscaler offers maximum flexibility, but it ties up massive internal resources and drives costs that usually only very large institutions can justify. Even then, it often does not pay off.
On the other hand, using AI through broad enterprise platforms like Salesforce or SAP AI can make sense when AI needs to be closely tied to CRM or ERP processes. But these platforms are not designed around the financial sector’s regulatory environment, so extensive customization is still required.
Unique fills exactly that gap. We deliver industry-specific solutions with built-in governance that can be deployed immediately, achieving a very short time-to-value. For banks and wealth managers looking for measurable results and regulatory assurance, it is the most efficient option.
René Schmidli: Unique’s platform runs on Microsoft Azure. Why did you choose this environment over another hyperscaler, and how do clients think about balancing on-premise and cloud solutions?
Phyllis Scholl: Microsoft’s focus on OpenAI models (GPT-4/4o, DALL·E, Codex) and its deep integration within the Microsoft ecosystem (Copilot, Office, Dynamics) fit perfectly with Unique’s integrated approach for financial services.
Microsoft also provides a more cohesive business suite with Office 365, Teams, Outlook, and Dynamics than Amazon or Google. Many clients prefer Microsoft because its enterprise-grade compliance and governance frameworks are more mature, which matters greatly in highly regulated sectors like finance.
Another key advantage is that Microsoft is one of the few AI providers hosting models locally in Switzerland, ensuring that data storage and processing remain within the country. That is essential for use cases involving sensitive client data.
Typically, clients keep critical or sensitive data and core processes on-premise, while running scalable AI models and collaboration tools in the cloud.
René Schmidli: Why did Unique choose to focus on the financial industry from the very beginning?
Phyllis Scholl: The financial industry is under pressure, margins are tight, and labor-intensive processes need to be streamlined. Our AI solutions directly address that need, and the industry has been very receptive.
Banking and insurance were natural starting points. These sectors are highly data- and document-intensive, from KYC processes to regulatory reporting to complex client interactions. They also face strict requirements around compliance, data protection, and transparency, which makes AI solutions with integrated governance immediately relevant.
Financial institutions are also willing to invest when technology demonstrably boosts efficiency, ensures regulatory compliance, and enhances customer experience, all of which our solutions do.
Because challenges such as onboarding, anti-money-laundering, and investment research are similar worldwide, our solutions can scale easily across markets. All that made finance the ideal place to start.
René Schmidli: How important are industry partnerships, for instance with core-banking providers, to your growth strategy?
Phyllis Scholl: Partnerships are crucial. But rather than with core-banking vendors, where integration moves slowly, our focus is on agile integration partners who can move fast.
A great example is our partnership with Capgemini. Unique brings its specialized AI solutions, while Capgemini contributes expertise in consulting, systems integration, and implementation in complex banking and insurance environments.
The partnership strengthens Unique’s market position and gives clients a trusted partner to help them manage AI’s complexity in financial services.
René Schmidli: Unique’s product portfolio is clearly structured by sector, such as banking, insurance, and private equity, and by sub-sectors such as retail or private banking. Then there is a set of specialized agents with clear use cases. How standardized are these agents, and how much customization do clients have? How do you balance standardization and flexibility, given costs and implementation time?
Phyllis Scholl: The agents are designed to be customized, and clients are encouraged to do so. They should plan resources for that. Our clients value the ability to start from our proven standards and then tailor solutions to their own institutions.
Thanks to Unique’s modular setup, combined with customization options such as specific data connectors like SharePoint or CRM systems, banks can launch AI use cases quickly.
René Schmidli: How fast is the “time to market”? Are clients already seeing measurable results, or are they still in an R&D or learning phase?
Phyllis Scholl: That is an excellent question. A great example is our collaboration with BNP Paribas Wealth Management on the Genix project. Unique AI enables the creation of investment content and advisor text in half the time, allowing BNP to respond faster to market changes and update clients quickly.
The KPIs are clear, a 50 percent time saving, and the ROI is already realized because advisors can spend more time with clients. Service quality rises, business opportunities grow, it is a win-win.
This is no longer R&D sandboxing, it is genuine business-driven value creation.
René Schmidli: How does Unique ensure that its AI becomes an integral part of clients’ strategies rather than just another tool?
Phyllis Scholl: We put a strong emphasis on co-creation. We work closely with clients to embed our solutions directly into their core processes, for example within CRM or compliance systems.
We do not just help automate existing workflows; we help rethink them. It starts with identifying relevant use cases and then implementing them in a way that fits naturally into business operations.
The goal is for the tools to become part of the process, not something that sits alongside it.
René Schmidli: Often when companies talk publicly about AI, for example LGT Bank, it is the CTO who speaks. But isn’t AI increasingly becoming a Board-level issue, given its strategic importance? Where does Unique see its role, as a transformation partner rather than just a technology provider?
Phyllis Scholl: Absolutely, Boards of Directors must address AI, but at the strategic level. The Board sets the boundaries within which AI initiatives are carried out safely, responsibly, and in alignment with corporate strategy.
That includes understanding both the opportunities and risks of AI, having at least a basic grasp of the technology, and defining investment priorities.
Execution, however, sits with management. They initiate projects, secure budgets, allocate resources, and make the business impact visible.
Only through this interplay, clear governance from the Board and consistent execution by management, can AI deliver its full potential.
René Schmidli: Gartner recently predicted that more than 40 percent of agentic AI projects will be abandoned by 2027 because of rising costs, unclear business value, and weak risk controls. Many companies are still in the pilot phase, often driven more by hype than by strategy. Gartner also warned about “agent washing,” meaning vendors rebranding traditional automation as agentic AI. What is your view?
Phyllis Scholl: The warning is valid, but it should not be overstated. Most technologies go through a phase of disillusionment, as we saw with cloud, RPA, and blockchain.
Agent washing is real, but it also indicates a fast-moving market where the genuine players will soon stand out.
Companies that take governance, cost control, and value creation seriously from the start will be the ones that successfully industrialize agentic AI, precisely because many others will not.
René Schmidli: Looking ahead, how do you see agentic AI developing over the next three to five years? Will it become a foundational technology or remain a niche?
Phyllis Scholl: Agentic AI will absolutely become foundational, but its complexity lies in vertical specialization. Each industry will need its own AI employees with domain-specific knowledge.
We see ourselves as pioneers in financial services, building expertise that is not easily replicated. In five years, every financial institution will use agentic AI; the only question is who will have the best agents.
René Schmidli: It makes sense to build or adapt governance structures in parallel with, or even before, implementing AI. From a governance perspective, how does Unique’s “Shared Responsibility Model” differ from others, and how has it been received?
Phyllis Scholl: Here is how it works. Unique develops the governance frameworks, tools, and policies, while clients bring their own processes, controls, and risk management practices.
Core principles, such as transparency, accountability, and robustness, are jointly embedded into both the product and the partnership. Both sides continuously monitor and refine them.
Depending on the element, such as access control, data management, or monitoring, the balance of responsibility shifts between Unique and the client.
While most models define a static, contractual split, Unique’s approach is dynamic and evolves with each use case.
In regulated markets like those governed by FINMA or the EU AI Act, this shared accountability is crucial. Unique takes a deliberately active, advisory role, more so than most pure technology vendors, and clients value that highly.
René Schmidli: Regulatory compliance is critical in financial services. How does Unique ensure that AI decisions remain auditable and transparent?
Phyllis Scholl: Every AI decision is documented with a full audit trail. Our agents show not only the outcome but also the reasoning path, data sources, and applied rules.
We integrate FINMA guidelines, the EU AI Act, and other regulations directly into our governance engine.
We also strictly apply the human-in-the-loop principle. There are, so far, no fully automated decisions. A human, such as an advisor, always reviews the output.
René Schmidli: Unique recently raised USD 30 million in Series A funding. The funds will be used to advance the platform and expand globally, especially into the U.S. What is driving this move?
Phyllis Scholl: We want to benchmark ourselves against the best and grow in the process. Most of our competitors are in the U.S., so winning U.S. clients is a clear priority.
The U.S. market’s scale is key to global growth and scalability. We have already onboarded our first hedge-fund clients there; they chose us because of our high security and data-protection standards.
René Schmidli: Finally, what lessons or advice would you share with board members from other service industries who are still at an early stage in their AI journey?
Phyllis Scholl: Beyond experimenting themselves, Boards must foster a learning culture for AI inside the company. That means allowing pilot projects but setting clear governance boundaries: where experimentation is allowed, how risks are managed, and how knowledge is shared.
Boards can drive real impact by asking the right questions and ensuring that AI learnings spread across the organization, turning them into a competitive advantage.
Another key takeaway is that AI is not just about efficiency. It is also about new business models. Boards in other sectors should start exploring how AI might reshape their value propositions, through personalized services, data-driven products, or intelligent customer interactions.
Anyone who sees AI only as a cost-reduction tool will miss its real strategic potential. My advice is this: in workshops, do not just test the technology; also explore its implications for strategy, organization, and talent.