The Foundations

Exploitation within ACES has been conceived as a progressive path from knowledge creation to market positioning. It aims to transform technical outcomes into tangible assets capable of sustaining value beyond the project’s lifetime. This process requires clarity on what can be exploited, who is best positioned to take it forward, and under which conditions. The first phase of this journey therefore concentrated on defining the exploitable elements with precision, assessing their potential through analytical tools, and aligning them with the expertise and roles of each partner. The ACES exploitation journey began with the identification of its Key Exploitable Results (KERs), a structured SWOT/PESTLE analysis, and a detailed mapping of each result to the consortium partners — establishing a foundation for market readiness.

Key Exploitable Results: the three main KERs

The first Key Exploitable Result is an open-source modular architecture that supports virtualisation and multiple patterns for ad-hoc edge-cloud deployments across single or multiple sites. It is event-driven, data-centric, and designed for autonomy, orchestration, and high throughput without a single point of failure. Its exploitable outcomes include: intelligent automated orchestration of edge services; visualisation and recommendation frameworks for operators and developers; asset monitoring and management; and a distributed knowledge base to sustain awareness and autonomy.

The second KER is the cognitive autopoietic framework embedding awareness, inference, and actionability. It establishes a system of distributed agents acting on shared knowledge to sustain system fitness and resilience, operationalised through the General Collective Intelligence schema and User Interface and Experience (UIX)components for operators and developers.

The third KER concerns intelligent energy grid frameworks, supporting local flexibility markets and local energy management systems while providing analytical visibility to developers and end-users. This result directly links the ACES technological capacity to the energy sector’s decentralised needs.

To understand ACES’s potential and strategic positioning, an integrated market and contextual analysis was conducted. It examined both internal dynamics and external conditions influencing exploitation pathways, highlighting how technological strengths align with regulatory, economic, and societal factors. This dual assessment provided a clear foundation for ACES’s strategic direction and market alignment.

The SWOT Analysis

The SWOT analysis positioned ACES within the evolving Edge-as-a-Service (EaaS) market.

Strengths include flexibility, scalability, improved performance, and reduced latency. The model’s compatibility with outsourcing further supports EaaS uptake by enterprises seeking local autonomy without ownership burdens.

Weaknesses centre on the relative immaturity of distributed mesh EaaS, uncertainties in demand scale, and the need for local infrastructure investment.

Opportunities arise from Europe’s push for data sovereignty, compliance with privacy frameworks, and secure micro-server operations.

Threats include the slow rollout of 5G and uncertainties around infrastructure scale and cost recovery.

Together, these findings guided ACES toward a realistic market positioning bridging internal technological development and external regulatory and industrial trends.

The PESTLE Analysis

The PESTLE analysis assessed macro conditions shaping exploitation: Political factors highlight the EU’s supportive environment (AI Act, Data Act, Gaia-X), though lacking disincentives for less sustainable technologies. Economic conditions remain dominated by non-European hyperscalers; ACES aims to reduce operational expenditures via AI-driven automation. Social barriers include limited trust and skill gaps, which ACES addresses through transparency-by-design and awareness tools. Technological aspects reveal fragmentation and weak cross-domain security—precisely where ACES introduces cognitive orchestration. Legal fragmentation across Member States hinders a unified digital market, while environmental concerns emphasise ACES’s potential for energy efficiency and lower CO₂ emissions through optimised resource use.

Mapping KERs to Partners

Each Key Exploitable Result was mapped to the consortium partners, aligning technical ownership, expertise, and exploitation potential to ensure coherent advancement from research to market. The mapping exercise clarified ownership and defined exploitation pathways.

• HIRO MicroDataCenters leads on microdata-centre hardware and integration.
• Lakeside Labs exploits swarm-intelligence coordination algorithms for workload orchestration and resource management.
• UPM focuses on decentralised system optimisation and educational integration of ACES advances.
• Martel Innovate aligns the ACES cloud stack with its IoT and Smart City portfolio, ensuring technology transfer and standardisation alignment.
• DataPower contributes to exploitation management, stakeholder engagement, and market modelling.
• This mapping ensures that each KER is linked to partners’ competencies and exploitation capacities, guaranteeing both horizontal and vertical integration across ACES’s technical and market domains.

Conclusions – Foundations

The Acceleration

The foundational phase structured ACES’s transition from research to exploitation. It identified its technological nucleus — autopoietic intelligence and cognitive orchestration — while anchoring its market entry strategy in European regulatory, social, and environmental frameworks.

Two extensive surveys defined the supply-side and demand-side perspectives on the Edge-as-a-Service model. The supply side rated the highest-relevance components as autopoietic functions for service management (self-adjustment, orchestration, self-healing), edge security, EaaS management software, and standardised gateways for interoperability. The demand side emphasised reliability, energy efficiency, and cost-effectiveness as purchasing drivers.

Analysis showed alignment on the complementarity between edge and cloud — both recognising that edge computing enhances real-time responsiveness, while the cloud retains long-term storage and heavy computation. Divergences were noted in perceptions of cost, with suppliers viewing capital expenditure as an acceptable barrier and users expressing caution toward upfront investment.

Energy Use Cases

The ACES framework demonstrates its functionality through energy-focused use cases:

1. Local flexibility markets — enabling distributed trading of energy at micro-grid level, enhancing efficiency and resilience.
2. Local energy management systems — dynamically optimising consumption and production via AI-driven orchestration.
3. These use cases test the real-world viability of autopoietic cognition for balancing load and supply, validating the environmental and economic potential of edge intelligence.

Business Model Canvas and Roadmap

ACES employs a three-step roadmap to market:

1. Consensus baseline through surveys and partner workshops to define service characteristics and investor typologies.
2. Refinement phase integrating market feedback, stakeholder interviews, and pilot validation to align supply and demand expectations.
3. Acceleration phase establishing business model variants (open-source platform, commercial service layers, and hybrid licensing) and preparing for post-project sustainability.

The emerging business models range from open federated EaaS (community and SME adoption) to commercial hybrid deployments integrating private and public edge infrastructure. These models embody European digital sovereignty principles, focusing on local autonomy, transparency, and energy-aware operations.

Luca Alessandro Remotti – DataPower – ACES Dissemination Coordinator