As artificial intelligence increasingly moves from experimentation to infrastructure, one of its most transformative applications is emerging at the intersection of energy, finance, and automation. Distributed clean energy, long fragmented by hardware complexity, manual processes, and rigid credit models, is now being reimagined through AI-native platforms that treat energy assets as data-driven systems rather than one-off installations.
In this interview with AI Spectrum, Jodok Betschart, Co-Founder & CEO of Cloover GmbH, shares how the company is building an operating layer for decentralised energy, one that embeds AI-powered underwriting, predictive asset intelligence, and automated financial workflows directly into the installer and household journey. From shifting risk assessment away from traditional credit scores toward long-term energy performance, to using AI as a transparency and orchestration engine for institutional capital, Cloover’s approach illustrates how machine intelligence can unlock scale, trust, and accessibility in the energy transition. The conversation explores how AI is quietly becoming the connective tissue between physical infrastructure, capital markets, and future energy networks and what that means for Europe’s path to energy independence.
What core technological and architectural principles underpin this vision, and how is AI central to your platform?
Cloover is an operating layer that connects energy assets, software, and financing into one cohesive system. Our goal is to make clean energy projects simple to deploy, finance, and operate.
This vision is built on four key principles:
Asset-First: Every project is built around the lifecycle of the physical energy asset —from its initial specification and financing to its long-term performance and maintenance. This ensures that all decisions are grounded in the asset’s ability to generate value.
Embedded Financing: Financing is not an afterthought; it is a native component of the platform. This allows capital to be deployed seamlessly at the point of sale, directly within the installer’s workflow, removing friction for both the installer and the end customer.
API-First and Modular: We provide a modular, API-first architecture. This allows our partners—installers, manufacturers, and capital providers—to integrate their own tools and systems with our platform without having to overhaul their existing workflows, ensuring maximum flexibility and adoption.
Automation: Our platform is designed to replace complex, manual processes with efficient, software-driven workflows. This reduces administrative overhead, minimizes errors, and enables all participants in the ecosystem to operate at scale.
AI’s Role: Reducing Friction, Not Replacing Judgment
AI is the intelligence layer that makes our platform scalable and efficient. Its primary role is to structure complex data and automate decisions to reduce friction across the ecosystem.
Specifically, AI: Supports Risk and Pricing: It analyzes thousands of data points to support our underwriting and pricing models, ensuring that financing is both accessible and sustainable.
Forecasts Asset Performance: AI powers the predictive models that forecast an asset’s energy production and financial returns, which is the cornerstone of our asset-first approach. Improves
Operations at Scale: It automates repetitive tasks, from document verification to performance monitoring, allowing our team and our partners to focus on higher-value activities. Crucially, we use AI to augment human expertise, not to replace it. It provides the data and recommendations to enable faster, better decisions, ensuring that the entire system remains robust, reliable, and trustworthy.
Your model evaluates long-term energy savings rather than traditional credit metrics. How does this improve risk assessment and expand access to financing?
Our AI-powered underwriting model represents a fundamental shift from evaluating a borrower’s past to underwriting a project’s future. This improves risk assessment and expands access in two key ways:
Improved Risk Assessment:
Focus on Asset Performance: Traditional credit models assess a borrower’s ability to repay based on historical financial behavior. Our model, while incorporating these traditional metrics as a baseline , primarily assesses the asset’s ability to generate cash flow (in the form of energy savings). We underwrite the project, not just the person. Our AI analyzes vast datasets—including geographic location, weather patterns, hardware specifications, and household consumption profiles—to accurately forecast the energy and cost savings a project will generate. This provides a more direct and relevant measure of a project’s financial viability and its ability to self-finance.
Dynamic Risk Monitoring: Unlike a static credit score, our risk assessment is continuous. By monitoring the real-time performance of the installed assets, our platform can detect deviations from the forecast early on . This allows for proactive risk management, such as flagging a hardware issue or adjusting optimization algorithms, thereby protecting the underlying asset’s value and the investor’s capital.
Expanded Access to Financing:
Unlocking New Customer Segments: By focusing on the project’s future savings, we can provide financing to a broader range of customers. A household with a moderate traditional credit score but a home with high potential for solar energy savings may represent a very low-risk investment from our perspective. This approach unlocks a significant segment of the market that is currently underserved by traditional banks, which is key to achieving mass-market adoption.
Instantaneous Feedback at Point of Sale: The AI-driven automation of standard checks and document processing allows installers to give customers near-instantaneous feedback on their financing application at the point of sale. This removes the long waiting periods and uncertainty associated with traditional loan applications, dramatically improving the customer experience and increasing conversion rates for our installer partners.
In essence, our AI underwriting democratizes access to clean energy by judging applications on the merit and future potential of the project itself, not just the financial history of the applicant.
With over $1.2 billion in commitments secured, how will this funding accelerate platform adoption and household access to decentralised energy solutions across Europe?
The capital commitment is the fuel for our operating system. The vast majority of this funding is not for corporate expenses but is operational capital that will be deployed directly through our platform to finance the hardware and installation costs for households. This accelerates adoption and access in a direct, powerful loop:
- Eliminating the Upfront Cost Barrier: The single greatest obstacle to residential clean energy adoption is the high upfront cost . The debt facility allows our installer partners to offer financing at the point of sale, effectively removing this barrier. Households can adopt solar panels, batteries, or heat pumps with little to no initial investment, paying for the system via a monthly installment that is often lower than their previous energy bill. This immediately makes clean energy accessible to millions of households that were previously priced out of the market.
- Empowering Installers to Scale: The capital empowers our installer partners to grow their businesses exponentially. With access to our embedded financing and working capital solutions, they can close more sales, serve more customers, and shorten their cash cycles. This creates a powerful flywheel effect: as installers grow their business using Cloover, they drive wider platform adoption and bring more households into the ecosystem. The availability of capital turns our platform from a simple software tool into an indispensable growth engine for the tens of thousands of SMEs that form the backbone of the European energy transition.
- Driving Geographic Expansion: A significant portion of this capital is earmarked for our expansion into new European markets, including France, Italy, the UK, and Austria . By providing the necessary funding to launch our financing products in these countries, we can rapidly replicate our model, onboard local installers, and accelerate the energy transition on a pan-European scale. The capital gives us the credibility and firepower to enter new markets and immediately begin enabling projects.
In short, the $1.2 billion is not just funding for Cloover; it is funding for the entire European energy transition, channeled through our platform to the installers and households who need it most.
How do Cloover’s AI Finance co-pilot and workflow tools address capital flow constraints and operational inefficiencies for energy installers?
Our workflow automation tools and the AI Finance Co-pilot are specifically designed to solve the core operational and financial frustrations that our founders identified in their initial research with hundreds of installers. They address these constraints directly:
Addressing Capital Flow Constraints:
Embedded Working Capital: The platform provides installers with access to working capital, solving the critical cash flow problem of having to purchase expensive equipment upfront and wait weeks or months for customer payment. This frees up their liquidity, allowing them to take on more projects simultaneously.
Pre-Financing of Subsidies: Navigating and waiting for government subsidies is a major administrative and financial burden for both installers and homeowners. Our platform automates the application process and pre-finances these subsidies, meaning the benefit is applied instantly at the point of sale . This simplifies the offer for the customer and removes a significant cash flow delay for the installer.
Instantaneous Financing Decisions: The AI Finance Co-pilot provides immediate feedback on financing applications. This eliminates the risk of an installer completing work only to find out the customer’s financing fell through, a major source of financial loss and uncertainty.
Tackling Operational Inefficiencies:
End-to-End Workflow Integration: Installers typically rely on a patchwork of fragmented software and manual processes for everything from lead management and quoting to procurement and project management. Our platform integrates these functions into a single, seamless operating system. This drastically reduces administrative overhead, minimizes errors, and allows installers to increase their project throughput.
Automated Procurement: The platform streamlines the procurement process, connecting installers with manufacturers and distributors. This simplifies ordering, reduces paperwork, and provides access to better pricing through economies of scale.
Simplified Sales Process: By embedding a powerful financing calculator and proposal generator directly into the sales workflow, we turn a complex, multi-step process into a simple, one-stop solution. Installers can generate a comprehensive quote—including hardware, installation, financing, and subsidies—in minutes, dramatically shortening the sales cycle.
By solving these fundamental capital and operational challenges, our tools empower installers to be more efficient, more profitable, and ultimately, to install more clean energy systems.
How important is AI-driven transparency and impact tracking in attracting institutional capital to distributed energy as a new infrastructure asset class?
For institutional capital, transparency and data-driven tracking are not just important; they are essential. Large-scale investors, such as pension funds and insurance companies, require predictable, de-risked, and standardised assets. The fragmented nature of distributed energy has historically made it unattractive. Our AI-driven platform is designed to solve this by transforming thousands of disparate installations into a coherent, institutional-grade asset class.
Standardisation and Transparency: AI is the engine that creates this standardisation. It ingests and processes a vast array of data from different hardware, locations, and project types, and translates it into a uniform set of Key Performance Indicators (KPIs) that investors understand: expected yield, default rates, cash flow projections, and asset depreciation. This provides a level of transparency and comparability that is impossible to achieve manually, making the asset class legible and investable.
Verifiable Impact Tracking: Modern institutional investors are increasingly driven by ESG (Environmental, Social, and Governance) mandates. They don’t just need financial returns; they need to prove the positive impact of their investments. Our platform provides verifiable, real-time impact tracking. We can quantify and report the exact amount of CO2 emissions avoided, the renewable energy generated, and the number of households transitioned to clean energy. This auditable impact data is critical for attracting capital from ESG-focused funds.
De-Risking the Asset Class: By providing granular, real-time performance data and predictive risk analytics, our platform significantly de-risks the investment. Investors are not investing blindly into a black box of loans. They have a dynamic, transparent view of the underlying assets’ performance. This confidence, backed by data, is what convinced a major European bank and the European Investment Fund to commit over a billion dollars to our platform.
In essence, our AI-driven platform serves as the trusted intermediary that provides the data, transparency, and standardisation required to give institutional investors the confidence to deploy capital at scale into the distributed energy ecosystem.
How do you see AI-powered platforms reshaping the distributed energy ecosystem over the next decade, and what role will Cloover play?
Over the next decade, AI-powered platforms will fundamentally reshape the distributed energy ecosystem, moving it from a collection of static, isolated assets to a dynamic, intelligent, and interconnected network. The evolution will proceed in two main phases:
Phase 1: The Transactional Layer (Present): Today, platforms like Cloover are primarily focused on solving the transactional and financial friction. We are building the “Shopify of Energy”—the essential backbone for financing, procurement, and installation. The primary role of AI is to make these transactions seamless, efficient, and scalable, thereby accelerating the deployment of assets.
Phase 2: The Orchestration Layer (Future): As millions of homes become energy independent, with solar, batteries, and EVs, they cease to be passive consumers and become active participants in the energy market. The next frontier for AI platforms is to orchestrate these distributed assets. This involves:
Virtual Power Plants (VPPs): AI will aggregate and control thousands of residential batteries to act as a single, massive power plant. This VPP can sell energy back to the grid during peak demand, provide grid stabilisation services, and generate new revenue streams for homeowners. Intelligent
Energy Management: AI-driven Energy Management Systems (EMS) will move beyond simple optimisation for a single home. They will make predictive decisions based on grid prices, weather forecasts, and community-level energy demand, deciding when to store energy, when to sell it, and when to share it with a neighbour.
Peer-to-Peer Energy Markets: Platforms will enable true peer-to-peer energy trading, where a household with excess solar power can sell it directly to a neighbor who is charging their EV, all managed seamlessly and automatically by an AI.
Cloover’s role is to be the foundational operating system upon which this future is built. We are already laying the groundwork. By connecting the hardware, standardizing the data, and building the trust of homeowners and installers, we are creating the network of connected assets that is the prerequisite for the orchestration layer. Our long-term vision is not just to finance the transition to energy independence, but to provide the intelligence that will power it.
