A ministry needed an integrated governance approach for the responsible development, acquisition, and deployment of algorithms and AI systems. It required ethical, legal, and technical frameworks to manage frontline risk in times of significant technological change. We developed the Algorithm Process Model (APM), a comprehensive framework covering the entire algorithm lifecycle from initiation to decommissioning, including assessment frameworks, templates, and guidance for ten distinct phases spanning idea generation through implementation and monitoring. The structured model was tested across five diverse algorithmic applications—from decision support to predictive maintenance—and includes EU AI Act implementation advice, ethical principles based on international guidelines, and procurement policy recommendations. It provided the organisation with a robust, integrated approach to responsible algorithm governance across all operational domains.
A national land registry agency sought to develop a comprehensive AI vision aligned with its public mission and core values to guide effective and responsible AI implementation across its operations. We supported the organisation through contextual analysis, co-creation workshops, and stakeholder interviews to identify strategic opportunities, risks, and organisational priorities. We developed an AI vision that identified opportunities within the organisation, aligned AI initiatives with the business and organisational strategy and goals, and established a roadmap of actions needed to enhance the organisation's AI maturity level. The resulting strategy positioned the agency for AI-driven transformation while maintaining its commitment to public values and provided clear guidance for broader AI maturity development across governance, organisational structure, and AI literacy initiatives.
A national youth helpline sought strategic guidance to navigate digital transformation and identify opportunities for Responsible AI adoption while maintaining its human-centric mission and ethical standards. Acting as strategic advisors to the executive team, we facilitated in-depth discussions on AI implementation and future direction, focusing on organisational needs and opportunities with strong emphasis on human impact and ethical considerations. We developed tailored AI use cases and translated them into a strategic roadmap aligned with the helpline's operational and long-term goals and broader business and organisational strategy. This roadmap now serves as a foundation for Responsible AI integration, enabling the organisation to harness AI's potential while safeguarding its human-centric mission.
A global insurance company faced uneven maturity across data & AI capabilities, insufficient alignment between local units and central leadership, and a variety of operating models that prevented them from unlocking value from their data at scale. We supported their data & AI strategy development across nine business units and the central organisation, assessing current capabilities, designing future-state blueprints, and delivering a comprehensive roadmap with clear milestones. The transformation delivered a harmonised operating model, prioritised AI use cases, and a scalable structure including a dedicated data & AI hub, laying the foundation for agentic AI implementation and stronger cross-functional collaboration across the global organisation.
An international financial institution sought to improve operational efficiency by increasing straight-through-processing rates across key business processes. With a mature data environment already in place, the organisation was well-positioned to scale AI adoption. We designed an agentic solution architecture that enables rapid development and integration of AI agents into existing systems, facilitates sharing of AI capabilities and agents across business units, and ensures control over reliability and deployment costs. The result was a standardised architecture that reuses core data and AI components already active within the client’s ecosystem, while leveraging cutting-edge agentic technologies. The engagement also delivered a clear roadmap for platform development to accelerate implementation.
A large financial institution wished to accelerate the pace of its AI implementation by strengthening its in-house AI risk expertise. We provided hands-on subject matter expertise to the second-line risk management team to clear backlogs, establish lasting governance practices in relation to (generative) AI use cases, and co-develop an AI risk control framework aligned with ISO/IEC 42001. We advised on AI policy updates and upskilled the internal risk team, delivering faster approvals, stronger controls, and a repeatable assessment process for responsible AI implementation.
A technology-driven financial institution was looking to systematically manage AI risks and prepare for compliance with the newly introduced EU AI Act across their AI-powered operations. Our cross-line-of-service team helped navigate EU AI Act requirements by analysing several scalable AI use cases in customer service and internal operations, while assessing regulatory and governance needs. We established an organisation-wide AI inventory, delivered AI literacy sessions, and developed a comprehensive AI risk management blueprint with defined roles, responsibilities, and AI principles. This resulted in a tailored framework that enhanced risk management capabilities, streamlined processes, improved operational efficiency, and guided the organisation toward full compliance readiness.
A ministry aimed to promote the responsible use of data, AI, and algorithms in anticipation of future legal obligations, including the EU AI Act. We conducted a needs assessment across ten operational agencies to understand current practices and future requirements. The approach included document analysis, informative sessions on upcoming legislation, discussions on Responsible AI, and a joint validation workshop. The outcome was a detailed report that comprehensively mapped the ministry's needs in policy, communication, and training, enabling informed decision-making for Responsible AI implementation across all operational agencies.
A rapidly expanding technical service provider needed to leverage AI and Microsoft 365 Copilot to enhance operational scalability while reducing costs. We conducted a six-week program with employees from four key functions, combining hands-on training with strategic use case development. We also provided practical implementation guidance and identified opportunities for AI agent applications. The program delivered significant results: participants saved an average of seventy minutes per week while reporting improved job satisfaction. We co-developed 25 high-value use cases and identified nine AI agent-based solutions for additional business value. The company received a structured phased rollout strategy with targeted recommendations for scaling AI capabilities across the entire organisation.
A leading healthcare information provider faced challenges with manual, inconsistent processes for capturing and exchanging critical data across their network, creating bottlenecks that slowed information flow when speed and accuracy were essential. We implemented ChatGPT Enterprise and built a custom AI lab, launching three pilot AI assistants that were iteratively improved and scaled to over thirty solutions through hands-on training, hackathons, and governance frameworks. The program achieved 75 per cent staff adoption within six months and delivered six core use cases that transformed daily operations, positioning generative AI as a strategic enabler for faster, more consistent healthcare information standardisation and exchange across their entire ecosystem.
A major bank faced challenges navigating thousands of project documents across work instructions, audits, regulatory compliance, and process execution, creating inefficiencies in knowledge management. To address this, we developed the Digital Project SME, a GenAI-powered Power BI dashboard that serves as an intelligent subject matter expert. Leveraging Llama models and Power BI, the solution allows users to get answers to questions across organisational documentation and access GenAI-generated summaries and insights through a user-friendly interface. The solution enables fast and accurate document retrieval and delivers significant time and cost savings while transforming document management into a smart, efficient experience.
A leading pension provider faced challenges with inconsistent quarterly IT health reporting across seven value streams, relying heavily on manual processes that impeded effective decision-making. In response, we developed the Digital Health Cockpit, an automated dashboard that replaces manual reporting with a unified view of the digital landscape. Additionally, a policy monitor has been designed to track real-time compliance with IT, data, and AI policies. This integrated solution is set to provide instant insights, support improved governance decisions, and centralise all health monitoring in one place, transforming how the organisation manages IT oversight and policy compliance.
One of the leading energy companies in the Netherlands needed to adjust their financial reporting models for commodities (Gas and Power) to handle the highly volatile energy market, as traditional gross margin calculations were no longer providing accurate output in unstable market conditions. We developed a sophisticated financial model that provides highly detailed and accurate actual insights by integrating usage-, pricing- and sourcing data through a state-of-the-art data platform across the B2C domain. As this effort led to reconciliation of information across the business unit, various other initiatives were spinning off to improve data maturity. Through multiple MVP phases, the model now has a proven (>1 year) track record of highly accurate volume and revenue reporting of Gas and Power. Next to the much needed improved reliability of external reporting, this enables the company to more actively drive performance through improved management reporting (customer value and insights across the full value chain) compared to legacy systems.
A leading property & casualty insurer operated a highly manual claims process resulting in significant inefficiencies throughout the process and low NPS scores amongst colleagues and clients. We helped the insurer redefine the future state of their claims organisation identifying the claims workforce of the future. Subsequently, we detailed the key shifts infusing agentic AI to redefine high volume process steps and launched pilots to drive real results. The result: reduced turnaround time, lower average handling time, reduced costs per claim, and decreased inbound query calls.
A leading consumer goods company faced significant market challenges and process bottlenecks that hindered their ability to leverage available data effectively for financial planning and reporting across the organisation. We developed an AI-powered assistant using AzureAI and PowerBI that enables users across finance and non-finance functions to interact with financial data through natural language, streamlining processes foro financial planning and analysis, and removing data accessibility barriers. Delivered in two phases, use case identification and MVP implementation, the solution improved data accessibility, enhanced reporting accuracy, and strengthened decision-making capabilities across the business.
A ministry needed an integrated governance approach for the responsible development, acquisition, and deployment of algorithms and AI systems. It required ethical, legal, and technical frameworks to manage frontline risk in times of significant technological change. We developed the Algorithm Process Model (APM), a comprehensive framework covering the entire algorithm lifecycle from initiation to decommissioning, including assessment frameworks, templates, and guidance for ten distinct phases spanning idea generation through implementation and monitoring. The structured model was tested across five diverse algorithmic applications—from decision support to predictive maintenance—and includes EU AI Act implementation advice, ethical principles based on international guidelines, and procurement policy recommendations. It provided the organisation with a robust, integrated approach to responsible algorithm governance across all operational domains.
A national land registry agency sought to develop a comprehensive AI vision aligned with its public mission and core values to guide effective and responsible AI implementation across its operations. We supported the organisation through contextual analysis, co-creation workshops, and stakeholder interviews to identify strategic opportunities, risks, and organisational priorities. We developed an AI vision that identified opportunities within the organisation, aligned AI initiatives with the business and organisational strategy and goals, and established a roadmap of actions needed to enhance the organisation's AI maturity level. The resulting strategy positioned the agency for AI-driven transformation while maintaining its commitment to public values and provided clear guidance for broader AI maturity development across governance, organisational structure, and AI literacy initiatives.
A national youth helpline sought strategic guidance to navigate digital transformation and identify opportunities for Responsible AI adoption while maintaining its human-centric mission and ethical standards. Acting as strategic advisors to the executive team, we facilitated in-depth discussions on AI implementation and future direction, focusing on organisational needs and opportunities with strong emphasis on human impact and ethical considerations. We developed tailored AI use cases and translated them into a strategic roadmap aligned with the helpline's operational and long-term goals and broader business and organisational strategy. This roadmap now serves as a foundation for Responsible AI integration, enabling the organisation to harness AI's potential while safeguarding its human-centric mission.
A global insurance company faced uneven maturity across data & AI capabilities, insufficient alignment between local units and central leadership, and a variety of operating models that prevented them from unlocking value from their data at scale. We supported their data & AI strategy development across nine business units and the central organisation, assessing current capabilities, designing future-state blueprints, and delivering a comprehensive roadmap with clear milestones. The transformation delivered a harmonised operating model, prioritised AI use cases, and a scalable structure including a dedicated data & AI hub, laying the foundation for agentic AI implementation and stronger cross-functional collaboration across the global organisation.
An international financial institution sought to improve operational efficiency by increasing straight-through-processing rates across key business processes. With a mature data environment already in place, the organisation was well-positioned to scale AI adoption. We designed an agentic solution architecture that enables rapid development and integration of AI agents into existing systems, facilitates sharing of AI capabilities and agents across business units, and ensures control over reliability and deployment costs. The result was a standardised architecture that reuses core data and AI components already active within the client’s ecosystem, while leveraging cutting-edge agentic technologies. The engagement also delivered a clear roadmap for platform development to accelerate implementation.
A ministry needed an integrated governance approach for the responsible development, acquisition, and deployment of algorithms and AI systems. It required ethical, legal, and technical frameworks to manage frontline risk in times of significant technological change. We developed the Algorithm Process Model (APM), a comprehensive framework covering the entire algorithm lifecycle from initiation to decommissioning, including assessment frameworks, templates, and guidance for ten distinct phases spanning idea generation through implementation and monitoring. The structured model was tested across five diverse algorithmic applications—from decision support to predictive maintenance—and includes EU AI Act implementation advice, ethical principles based on international guidelines, and procurement policy recommendations. It provided the organisation with a robust, integrated approach to responsible algorithm governance across all operational domains.
A large financial institution wished to accelerate the pace of its AI implementation by strengthening its in-house AI risk expertise. We provided hands-on subject matter expertise to the second-line risk management team to clear backlogs, establish lasting governance practices in relation to (generative) AI use cases, and co-develop an AI risk control framework aligned with ISO/IEC 42001. We advised on AI policy updates and upskilled the internal risk team, delivering faster approvals, stronger controls, and a repeatable assessment process for responsible AI implementation.
A technology-driven financial institution was looking to systematically manage AI risks and prepare for compliance with the newly introduced EU AI Act across their AI-powered operations. Our cross-line-of-service team helped navigate EU AI Act requirements by analysing several scalable AI use cases in customer service and internal operations, while assessing regulatory and governance needs. We established an organisation-wide AI inventory, delivered AI literacy sessions, and developed a comprehensive AI risk management blueprint with defined roles, responsibilities, and AI principles. This resulted in a tailored framework that enhanced risk management capabilities, streamlined processes, improved operational efficiency, and guided the organisation toward full compliance readiness.
A ministry aimed to promote the responsible use of data, AI, and algorithms in anticipation of future legal obligations, including the EU AI Act. We conducted a needs assessment across ten operational agencies to understand current practices and future requirements. The approach included document analysis, informative sessions on upcoming legislation, discussions on Responsible AI, and a joint validation workshop. The outcome was a detailed report that comprehensively mapped the ministry's needs in policy, communication, and training, enabling informed decision-making for Responsible AI implementation across all operational agencies.
A rapidly expanding technical service provider needed to leverage AI and Microsoft 365 Copilot to enhance operational scalability while reducing costs. We conducted a six-week program with employees from four key functions, combining hands-on training with strategic use case development. We also provided practical implementation guidance and identified opportunities for AI agent applications. The program delivered significant results: participants saved an average of seventy minutes per week while reporting improved job satisfaction. We co-developed 25 high-value use cases and identified nine AI agent-based solutions for additional business value. The company received a structured phased rollout strategy with targeted recommendations for scaling AI capabilities across the entire organisation.
A leading healthcare information provider faced challenges with manual, inconsistent processes for capturing and exchanging critical data across their network, creating bottlenecks that slowed information flow when speed and accuracy were essential. We implemented ChatGPT Enterprise and built a custom AI lab, launching three pilot AI assistants that were iteratively improved and scaled to over thirty solutions through hands-on training, hackathons, and governance frameworks. The program achieved 75 per cent staff adoption within six months and delivered six core use cases that transformed daily operations, positioning generative AI as a strategic enabler for faster, more consistent healthcare information standardisation and exchange across their entire ecosystem.
A major bank faced challenges navigating thousands of project documents across work instructions, audits, regulatory compliance, and process execution, creating inefficiencies in knowledge management. To address this, we developed the Digital Project SME, a GenAI-powered Power BI dashboard that serves as an intelligent subject matter expert. Leveraging Llama models and Power BI, the solution allows users to get answers to questions across organisational documentation and access GenAI-generated summaries and insights through a user-friendly interface. The solution enables fast and accurate document retrieval and delivers significant time and cost savings while transforming document management into a smart, efficient experience.
A leading consumer goods company faced significant market challenges and process bottlenecks that hindered their ability to leverage available data effectively for financial planning and reporting across the organisation. We developed an AI-powered assistant using AzureAI and PowerBI that enables users across finance and non-finance functions to interact with financial data through natural language, streamlining processes foro financial planning and analysis, and removing data accessibility barriers. Delivered in two phases, use case identification and MVP implementation, the solution improved data accessibility, enhanced reporting accuracy, and strengthened decision-making capabilities across the business.
A leading property & casualty insurer operated a highly manual claims process resulting in significant inefficiencies throughout the process and low NPS scores amongst colleagues and clients. We helped the insurer redefine the future state of their claims organisation identifying the claims workforce of the future. Subsequently, we detailed the key shifts infusing agentic AI to redefine high volume process steps and launched pilots to drive real results. The result: reduced turnaround time, lower average handling time, reduced costs per claim, and decreased inbound query calls.
One of the leading energy companies in the Netherlands needed to adjust their financial reporting models for commodities (Gas and Power) to handle the highly volatile energy market, as traditional gross margin calculations were no longer providing accurate output in unstable market conditions. We developed a sophisticated financial model that provides highly detailed and accurate actual insights by integrating usage-, pricing- and sourcing data through a state-of-the-art data platform across the B2C domain. As this effort led to reconciliation of information across the business unit, various other initiatives were spinning off to improve data maturity. Through multiple MVP phases, the model now has a proven (>1 year) track record of highly accurate volume and revenue reporting of Gas and Power. Next to the much needed improved reliability of external reporting, this enables the company to more actively drive performance through improved management reporting (customer value and insights across the full value chain) compared to legacy systems.
A leading pension provider faced challenges with inconsistent quarterly IT health reporting across seven value streams, relying heavily on manual processes that impeded effective decision-making. In response, we developed the Digital Health Cockpit, an automated dashboard that replaces manual reporting with a unified view of the digital landscape. Additionally, a policy monitor has been designed to track real-time compliance with IT, data, and AI policies. This integrated solution is set to provide instant insights, support improved governance decisions, and centralise all health monitoring in one place, transforming how the organisation manages IT oversight and policy compliance.
A leading consumer goods company faced significant market challenges and process bottlenecks that hindered their ability to leverage available data effectively for financial planning and reporting across the organisation. We developed an AI-powered assistant using AzureAI and PowerBI that enables users across finance and non-finance functions to interact with financial data through natural language, streamlining processes foro financial planning and analysis, and removing data accessibility barriers. Delivered in two phases, use case identification and MVP implementation, the solution improved data accessibility, enhanced reporting accuracy, and strengthened decision-making capabilities across the business.