ESG Policy
Environmental, Social & Governance
Environmental, social, and governance considerations form part of how Synapse Capital evaluates assets, technologies, operating environments, and long-term risk.
Our approach focuses on factors that are financially material, operationally relevant, and appropriate to the characteristics of each strategy and underlying asset.
Our Approach
ESG Within the Decision-Making Process
Relevant ESG factors are considered alongside financial, operational, technology, and market analysis throughout the asset lifecycle.
Materiality varies by asset. For AI infrastructure, power, water, land, equipment lifecycle, and local operating conditions may be significant. For technology businesses, data governance, cybersecurity, workforce practices, and responsible AI may carry greater relevance.
Assess
Identify material ESG factors associated with each asset, technology, and operating environment.
Integrate
Incorporate relevant findings into financial, operational, and risk analysis.
Monitor
Track material indicators and developments throughout the holding period.
Review
Reassess factors as operations, regulation, technology, and markets evolve.
ENVIRONMENTAL
Managing the Resource Requirements of AI
Artificial intelligence requires substantial computing infrastructure. That infrastructure depends on power, cooling, land, equipment, connectivity, and supporting resources.
Environmental considerations are assessed where they may influence operating resilience, long-term economics, regulatory exposure, or asset value.
Energy
Power availability, reliability, pricing, source, and long-term requirements.
Efficiency
Compute efficiency, cooling architecture, power usage, and infrastructure performance.
Water
Water requirements and availability where relevant to cooling and local operating conditions.
Emissions
Operational emissions and the carbon intensity of electricity where material.
Land & Development
Environmental considerations associated with site selection, construction, permitting, and infrastructure development.
Equipment Lifecycle
Hardware replacement, reuse, recycling, and responsible management of electronic equipment.
AI INFRASTRUCTURE
Power as a Strategic Consideration
Energy is one of the defining requirements for large-scale AI infrastructure.
Our assessment considers access to sufficient power alongside reliability, economics, grid capacity, infrastructure requirements, and the long-term characteristics of the energy environment supporting each location. For development-stage assets, these considerations form part of site assessment, technical planning, operating economics, and long-term resilience.
Operating With Greater Efficiency
Infrastructure efficiency is considered across both physical facilities and computing assets. Areas of focus may include:
Power Usage Effectiveness
Cooling Efficiency
GPU Utilization
Compute Density
Water Efficiency
Equipment Lifecycle
Hardware Reuse & Recycling
Waste Heat Opportunities
Where reliable data is available, relevant indicators may be incorporated into asset monitoring and operating reviews.
People, Skills & Communities
The expansion of artificial intelligence affects workforces, communities, education, access to technology, and the way digital services are delivered.
Social factors are considered where they may influence operating quality, resilience, stakeholder relationships, or long-term asset performance.
Workforce
Health, safety, working conditions, technical development, and access to skilled talent.
Communities
Local effects of infrastructure development, including employment, construction activity, land use, and community relationships.
Education & Skills
Development of capabilities required to participate in an increasingly AI-driven economy.
Digital Access
The role of infrastructure and technology in expanding access to computing and intelligent services.
Data & Privacy
Responsible handling of personal, commercial, and sensitive information.
Building Capability Alongside Infrastructure
The expansion of AI requires both computing capacity and people with the skills to understand, build, operate, and responsibly use intelligent systems.
Within the broader Synapse Power AI ecosystem, education and workforce-development initiatives support AI literacy, practical technical training, certification, and professional development. These capabilities contribute to the human infrastructure required for long-term AI adoption.
Explore Synapse EducationAI Literacy
Technical Training
Certification
Professional Development
Governance for Intelligent Systems
As artificial intelligence becomes more capable and more widely deployed, governance around its development and use becomes increasingly relevant.
Data Governance
Quality, provenance, security, and appropriate use of data.
Privacy
Protection of personal and sensitive information.
Bias & Fairness
Potential for automated systems to produce unintended or discriminatory outcomes.
Human Oversight
Appropriate human involvement in consequential processes and decisions.
Transparency
Understanding where and how automated systems influence outcomes.
Safety & Reliability
Testing, monitoring, and controls appropriate to the intended use.
Misuse Risk
Consideration of foreseeable misuse and appropriate safeguards.
Accountability Across the Asset Lifecycle
Governance provides the structure through which financial, operational, technology, and ESG considerations are managed. Our approach emphasizes clear responsibilities, documented controls, appropriate oversight, accurate reporting, ethical conduct, and accountability throughout the lifecycle of an asset.
From Assessment to Asset Management
ESG considerations are incorporated where relevant throughout the portfolio process.
Initial Assessment
Identify material environmental, social, and governance factors associated with the asset, business, technology, or location.
Due Diligence
Evaluate relevant operating practices, risks, regulatory considerations, and potential improvement areas.
Portfolio Decision
Consider material ESG findings alongside financial, operational, market, technology, and risk analysis.
Asset Management
Monitor relevant indicators and material developments during the holding period.
Review
Reassess material factors as operations, regulation, technology, and market conditions change.
ESG From the Development Stage
Large infrastructure projects introduce environmental and social considerations before an asset becomes operational. For development-stage projects, relevant factors may include land use, power availability, water requirements, construction impacts, permitting, local infrastructure, workforce requirements, and community relationships.
These considerations form part of the broader technical, financial, operating, and risk assessment as projects progress from planning toward operation.
Explore Strategic ProjectsPlanning for Long-Term Operating Conditions
Physical infrastructure may be exposed to changing environmental conditions over long operating periods.
Where material, assessment may consider extreme temperatures, water availability, flooding, severe weather, grid resilience, and other physical conditions capable of affecting operations. These factors may influence site selection, infrastructure design, insurance requirements, operating procedures, and long-term capital planning.
Focused on Material Indicators
ESG monitoring is based on factors relevant to the characteristics and operating environment of each underlying asset. Depending on the strategy and availability of reliable information, indicators may include:
Not every indicator is applicable to every asset or strategy.
Reporting What Is Relevant
Where material ESG information is available and relevant to a strategy, Synapse Capital seeks to incorporate it into portfolio monitoring and reporting.
Our objective is to provide useful information based on measurable indicators while avoiding unsupported environmental or social claims.
As data quality, technology, regulatory expectations, and reporting standards continue to develop, our approach may evolve accordingly.
Reporting Framework
Material Indicators · Measurable Data
Practical. Material. Accountable.
Focus on Materiality
Prioritize factors relevant to the characteristics, risk, and long-term value of each asset.
Measure Where Possible
Prefer measurable indicators and verifiable information over broad or unsupported claims.
Consider the Full Lifecycle
Assess ESG factors from development through operation and eventual disposition.
Apply Technology Responsibly
Recognize the governance and oversight expectations associated with intelligent systems.
Evolve With the Market
Adapt our approach as data quality, technology, regulation, and market standards develop.
Application of This Policy
This policy describes Synapse Capital's general approach to environmental, social, and governance considerations across its strategies and asset-management activities.
The relevance and application of individual ESG factors vary according to strategy, asset type, geography, development stage, available information, and applicable requirements.
ESG considerations form part of the broader assessment and asset-management framework and are considered alongside financial, operational, technology, legal, and risk factors.
Disclaimer: ESG integration does not guarantee positive environmental or social outcomes, reduce risk, or ensure financial performance. The relevance and weight of individual ESG factors vary by strategy and underlying asset.