Arken

Data platform to automate operations and forecast the deployment of clean energy.

The idea

Problem: Distributing clean energy produced by distributed energy resources (DERs) relies on manually estimating annual electric usage for recipients, a slow and inefficient process for subscription models. This limits access to clean energy, especially for the rental market with frequent tenant turnover and a lack of historical data.

Arken empowers clean energy developers to streamline their operations and expand their addressable market with a data platform.

• Automatic Monitoring & Allocation: Arken continuously tracks electric usage per account, automatically updating energy allocation for efficient management and improved customer satisfaction.

• Machine Learning for Data Deserts: Arken's machine learning model forecasts usage for accounts with limited data, unlocking the rental market and other previously inaccessible segments for clean energy adoption.

Below: Arken Prototype based on K-Nearest Neighbors (KNN) algorithm, a popular machine learning technique, and used to identify an average monthly consumption of electricity.

Competitors / Substitutes

EnergySage: Self-serve solar marketplace, enrollment software

SunCentral: Asset owner and subscription management portal, enrollment software

Solstice: Financing software and a community solar subscription management company, enrollment software

Perch Energy: Community solar subscription management company, enrollment software

Arcadia: Community solar subscription management company, enrollment software

Arken reviewed the market landscape to see what was offered and consistent pain points. There were strong themes in service-first, not technology-first business practices. In 2024, there were more startups entering the market in order to provide software solutions to manage DERs and launch VPP programs.  Overall, there was a lack of data-driven offerings and Arcadia’s Arc product was the main competitor due to their value proposition as a data aggregator from more than 80% of US electric accounts.

Our differentiation angle(s)

Market competitors were focused on the acquisition and enrollment software for energy developers providing a direct supply product. Arken’s product focused on data-first and automation in order to improve forecasting and management of community solar subscriptions, one format for deploying DER generation.

Goals for Arken were also a differentiating factor. The cost of third-party operations for clean energy developers are notoriously high and too expensive. Additionally, there are Department of Energy programs to try and accelerate the workforce development. With aggressive goals to triple the size of the market by 2025, Arken is providing a new option for how to lower costs, scale the management of DERs deployed, and offer a solution for the labor shortage.

Arken was a data-driven and software-first company. 

Amount raised (if any)

Received a termsheet for $750K for 12% - team disbanded prior to further discussion

Duration from Start to End

1 year 14 months

Team size

3

Challenges and what you'd do differently

Product Market Fit

• With a minimum viable product (MVP), Arken struggled to identify clean energy developers for our pilot program. In the market, a number of sales prospects were in the market for more than data analytics and automated operations. There were several requests for billing software and an optical character recognition (OCR) product in order to improve the existing operational processes.

• In the early days, Arken identified and took meetings with a number of developers who were embarking on their first clean energy project. We posted in the National Community Solar Partnership (NCSP) and offered resources alongside office hours for private Q&A sessions. These sales prospects had too wide of a scope for Arken.

Team / Partners

• The team lacked the technical expertise in data forecasting and industry knowledge for clean energy processes. Additionally, the team did not have previous experience implementing a tool that would require data mapping. We were unable to find the right people to bring on in order to complete technical onboarding for a pilot. In the clean energy industry, there are a number of regulatory and policy-based considerations to translate into rules for the product. These are determinants for feasibility, how to prioritize features, and necessary skills for interviewing our users during the crucial first meetings where we collect technical requirements. 

• Timing does matter. Arken sequenced the product before assembling the right team and we were unable to deliver the pilot program. We received demand and validation for our product market fit. However, we were unable to deploy the product.

• Investors voiced concerns about the team and no co-founder during the initial fundraising meetings.

Notes above shared by founder/CEO Clara Zou