logoAiPathly

Generate Capital

G

Overview

Generate Capital, founded in 2014 by Jigar Shah, Matan Friedman, and Scott Jacobs, is a leading investment firm specializing in sustainable infrastructure. The company focuses on developing, owning, operating, and financing projects across various sectors:

  • Sustainable Energy: Energy efficiency, storage, fuel cells, green hydrogen, and solar
  • Sustainable Mobility: Charging stations, electric and hydrogen vehicles, and sustainable fuels
  • Sustainable Water, Waste & Agriculture: Biogas, renewable natural gas (RNG), precision agriculture, carbon capture and storage, and recycling Generate Capital operates on an Infrastructure-as-a-Service model, providing cost-effective and dependable resource solutions for businesses, governments, and communities. The firm collaborates with over 40 technology and project developers globally, managing a portfolio exceeding 2,000 assets across clean energy, transportation, waste, and water sectors. Since its inception, Generate Capital has raised over $10 billion in capital, including a recent $1.5 billion equity raise from institutional investors and pension funds, as well as a $1.2 billion corporate credit facility and term loan to support sustainable infrastructure growth. The company's impact is significant, having produced over 320GWh of sustainable power and processed more than 715Kt of organic waste. Generate Capital's investments aim to accelerate cost savings, resilience, and decarbonization across various sectors. Headquartered in San Francisco, California, with additional offices in New York, Washington, and London, Generate Capital has formed strategic partnerships with entities such as the California State Teachers' Retirement System (CalSTRS) and the New York Green Bank (NYGB). The firm's commitment to sustainability is reflected in its financing, which includes sustainability-linked pricing adjustments. Generate Capital's mission is to be the capital partner for the infrastructure transition to a clean energy economy, driving positive environmental and social impact through its investments and operations.

Leadership Team

Generate Capital's robust leadership team drives its strategic vision and oversees various initiatives. Key members include:

  • Scott Jacobs: Chief Executive Officer and Co-Founder, guiding the company's overall strategy and direction.
  • Bill Sonneborn: President, bringing nearly three decades of experience in scaling alternative investment and asset management firms, including roles at EIG, TCW, and the IFC.
  • Matan Friedman: Chief Investment Officer and Co-Founder, responsible for the company's investment strategies and initiatives.
  • Aaron Bielenberg: Head of Portfolio Management, with over 20 years of global experience advising energy and infrastructure investors, operating companies, and governments. Previously worked as a Managing Director and Partner at Boston Consulting Group and McKinsey & Co.
  • Nancy Tsang: Chief Risk Officer, enhancing Generate's risk framework and embedding risk practices into portfolio management. Has nearly two decades of experience covering financial and non-financial risks, primarily at Morgan Stanley.
  • Jonah Goldman: Head of External Affairs and Impact, overseeing communications, government engagement, and impact assessment and strategy. Previously led Bill Gates' Breakthrough Energy.
  • Mayanka Melville: Head of Data, applying advanced analytics to improve decision quality across Generate. Brings two decades of investment management experience, including data science, investment product development, and risk management.
  • Chris Baker: General Manager of Clean Bus Solutions, LLC, part of a joint venture with Blue Bird focused on fleet electrification-as-a-service. This leadership team combines diverse expertise in sustainable infrastructure, finance, risk management, and external affairs, crucial for Generate Capital's continued growth and impact in the sustainable development sector.

History

Generate Capital, a leading investment and operating platform for sustainable infrastructure, was founded in 2014 by Jigar Shah, Scott Jacobs, and Matan Friedman. The company's mission is to accelerate the transition to a low-carbon, resource-efficient economy by investing in and operating sustainable infrastructure projects. Key milestones and achievements:

  1. Founding and Early Focus:
  • Established with a focus on renewable energy, energy storage, water treatment, waste management, transportation, and digital infrastructure.
  • Co-founders brought extensive experience from renewable energy, consulting, and venture capital backgrounds.
  1. Strategic Partnerships and Growth:
  • Forged partnerships with over 50 project development and technology companies.
  • Collaborated with major investors, including CalSTRS, HESTA, QIC, and AustralianSuper.
  1. Capital Raised:
  • Raised over $10 billion in capital since founding.
  • Recent round of $1.5 billion in new capital commitments from global institutional investors.
  1. Project Portfolio:
  • Built a diverse portfolio of thousands of sustainable infrastructure projects globally.
  • Includes solar energy systems, energy storage facilities, water treatment plants, and waste-to-energy projects.
  1. Notable Initiatives:
  • Launched the Viridis Initiative with McKinstry for energy-as-a-service solutions.
  • Established Clean Bus Solutions with Blue Bird Corporation for electric school buses.
  • Implemented significant energy efficiency projects, such as the one with Hillsborough County Public Schools, avoiding $13 million in annual utility costs and reducing CO2 emissions by 45,000 metric tons.
  1. Business Model:
  • Operates under an Infrastructure-as-a-Service model.
  • Provides affordable, reliable, and sustainable resources to various clients.
  • Offers financial services products, including short-term asset-based financing, equipment leasing, and small-scale project finance. Generate Capital has established itself as a leader in the sustainable infrastructure industry, driving innovation and growth through its unique approach to financing and operating sustainable projects. The company's success is reflected in its strong financial performance, consistent returns to investors, and significant environmental and social impact.

Products & Solutions

Generate Capital offers a diverse range of products and solutions focused on sustainable infrastructure and resource technologies. Their offerings can be categorized into several key areas:

  1. Infrastructure-as-a-Service™: This innovative model allows organizations to adopt sustainable technologies without upfront capital investments or operational risks. Customers pay for infrastructure on a service basis, similar to utility payments.
  2. Sustainable Energy Solutions: Generate invests in and operates various technologies, including:
  • Microgrids
  • Solar energy
  • Energy storage systems
  • Lighting and HVAC systems
  • Fuel cells
  • Geothermal and biomass/biogas systems
  • Building automation and sensors
  • Heat pumps and smart meters
  1. Sustainable Mobility: The company supports initiatives through investments in:
  • Electric and hydrogen vehicles
  • Autonomous vehicles
  • Charging infrastructure
  • Fleet management
  1. Sustainable Water, Waste, and Agriculture: Solutions include:
  • Anaerobic digesters
  • Wastewater treatment
  • Desalination
  • Food waste management
  • Recycling/reuse
  • Precision agriculture
  • Farm automation
  • Irrigation systems and sensors/meters
  1. Custom Capital Solutions: Generate provides non-dilutive growth capital, project financings, and other financial structures to help technology companies scale their innovative resource solutions.
  2. Project Development and Implementation: The company identifies, develops, implements, and funds infrastructure projects for its partners, ranging from traditional energy conservation measures to complex efficiency projects.
  3. Financial and Operational Support: Generate offers expertise to help companies manage and scale their sustainable infrastructure projects, including arranging credit facilities and providing project financing. Generate Capital's approach centers on providing flexible capital solutions and operational support to accelerate the deployment of sustainable energy and resource technologies, making sustainability more accessible and cost-effective for a wide range of customers.

Core Technology

Generate Capital focuses on investing in, operating, and financing proven sustainable infrastructure technologies rather than developing new technologies themselves. Their core areas of involvement include:

  1. Sustainable Energy
  • Microgrids
  • Solar energy
  • Energy storage
  • Lighting and HVAC systems
  • Fuel cells
  • Geothermal
  • Biomass & biogas
  • Building automation & sensors
  • Heat pumps
  • Smart meters
  1. Sustainable Mobility
  • Electric vehicles
  • Hydrogen vehicles
  • Autonomous vehicles
  • Charging depots & infrastructure
  • Fleet management
  1. Sustainable Water, Waste & Agriculture
  • Anaerobic digesters
  • Wastewater treatment
  • Desalination
  • Food waste management
  • Recycling/reuse
  • Precision agriculture
  • Farm automation
  • Irrigation systems
  • Sensors & meters Generate Capital's innovative approach involves applying new business and financing models to these existing technologies, making them more accessible and scalable. Their Infrastructure-as-a-Service model allows customers to pay for solutions on a service basis rather than through upfront capital purchases, thereby accelerating the adoption of sustainable technologies across various sectors.

Industry Peers

Generate Capital operates within the renewable energy and sustainable infrastructure sector, competing with several industry peers. These companies can be categorized into three main groups:

  1. Renewable Energy Project Developers and Infrastructure Investment Firms
  • BlackRock Renewable Power: Focuses on investing in and developing renewable energy projects.
  • Brookfield Renewable Partners: Owns and operates renewable power assets globally.
  • Capital Dynamics: An investment firm specializing in clean energy and sustainable infrastructure investments.
  • Macquarie Infrastructure and Real Assets: A global alternative asset manager investing in infrastructure projects, including renewable energy.
  1. Specialized Renewable Energy Financing and Solutions
  • LevelTen Energy: Provides a marketplace platform for renewable energy buyers and sellers.
  • Bluestar Energy Capital: An investment platform delivering investable clean energy projects.
  • Bullfinch: A fintech company offering financing solutions for renewable energy projects.
  • Leyline Renewable Capital: Focuses on accelerating renewable energy deployment through flexible capital solutions.
  • Ygrene Energy Fund: Provides financing for clean energy and sustainable home improvement projects.
  1. Other Industry Players
  • CapeZero: Specializes in clean energy finance ecosystem, offering software solutions for tax equity structuring models.
  • Pexapark: Offers software and advisory services for post-subsidy renewable energy sales and risk management.
  • Lacuna Sustainable Investments: Invests in early-stage renewable energy projects.
  • Lotus Infrastructure: A private equity firm focused on energy and infrastructure asset acquisition and development. These companies compete with Generate Capital in various aspects of the renewable energy and sustainable infrastructure market, including project development, financing, and operations. Generate Capital differentiates itself through innovative financing solutions, strong partnerships, and a focus on sustainability and environmental stewardship. The company's unique Infrastructure-as-a-Service model and comprehensive approach to sustainable technologies set it apart in this competitive landscape.

More Companies

A

AI Implementation Engineer specialization training

Specializing as an AI Implementation Engineer requires a combination of technical skills, practical experience, and a deep understanding of AI and machine learning concepts. Here's a comprehensive overview of the key aspects and training paths: ### Core Skills and Knowledge - **Programming**: Proficiency in languages such as Python, Java, or C++ is essential. A strong foundation in software engineering is crucial. - **Mathematics and Statistics**: Understanding linear algebra, probability, and statistics is vital for developing and optimizing AI models. - **Machine Learning and Deep Learning**: Knowledge of algorithms, neural networks, and frameworks like TensorFlow, PyTorch, and Keras is fundamental. ### Responsibilities and Tasks - Developing AI Models: Design, test, and deploy models using various algorithms. - Data Management: Build data ingestion and transformation infrastructure. - Integration and Deployment: Convert machine learning models into APIs and integrate them into existing systems. - Collaboration: Work closely with cross-functional teams to ensure AI solutions meet organizational goals. ### Training and Educational Pathways - Bachelor's Degree: Computer science, data science, or related field. - Master's Degree: Optional, but enhances qualifications in AI or machine learning. - Certifications: AWS Certified Machine Learning, Microsoft Certified: Azure AI Engineer Associate. ### Specialized Training Programs - AI Engineering Specialization: Focus on building next-generation apps powered by generative AI. - Generative AI Engineering: Design, develop, and maintain generative AI models. ### Practical Experience - Hands-on Projects: Engage in capstone projects, research assistantships, or internships. - Applied Learning: Build AI-powered apps as part of specialization courses. ### Advanced Roles and Specializations - Senior Roles: Strategic decision-making, leading AI projects, mentoring junior engineers. - Research and Development / Product Development: Contribute to advancing AI or create innovative AI-powered products. By combining these elements, aspiring AI Implementation Engineers can gain the comprehensive skills and knowledge required to excel in this dynamic field.

A

AI DevSecOps Engineer specialization training

To specialize as a DevSecOps Engineer, consider these comprehensive training programs: 1. Whizlabs Hands-on Learning for AWS DevSecOps Engineer - Focuses on integrating security into AWS cloud application development - Includes 20+ hands-on labs and 3 challenges - Covers AWS services like CloudWatch, CloudTrail, Trusted Advisor, and Security Manager - Prerequisites: Familiarity with core AWS services, Linux, CI/CD pipelines, and security threats - Suitable for IT professionals, developers, cloud architects, and security engineers 2. Tonex Inc. DevSecOps Engineer Certification (DSOEC) - Equips professionals to integrate security into DevOps pipeline - Covers automation, threat modeling, vulnerability assessment, risk management, and container security - Includes hands-on projects and prepares for DSOEC exam - Key areas: CI/CD pipelines, containerization, cloud security, and incident response 3. EC-Council Certified DevSecOps Engineer (E|CDE) - InfosecTrain - Comprehensive overview of designing, developing, and maintaining secure applications - Covers theoretical knowledge and hands-on experience - Focuses on integrating tools and methodologies in on-premises and cloud environments - Key topics: DevSecOps planning, development, build, test, release, deployment, and monitoring - Certification requires passing an exam with 100 multiple-choice questions 4. DevOn Academy DevSecOps Engineer Learning Journey - Focuses on designing secure systems and incorporating security at a higher level - Covers cloud security, container security, threat modeling, and compliance - Includes modules on defensive programming, Docker security, and AWS Security Specialty prep - Emphasizes balanced soft, process, functional, and technical skills 5. Coursera Introduction to DevSecOps - Provides an overview of DevSecOps principles and practices - Covers CI/CD, Agile development, and version control systems - Includes modules on planning DevSecOps transformation and task automation - Suitable for intermediate IT professionals or those managing IT teams Choose the program that best aligns with your career goals and current skill level.

A

AI Governance Specialist specialization training

AI Governance Specialist specialization training equips professionals with the knowledge and skills to develop, integrate, and deploy trustworthy AI systems in compliance with emerging laws and policies. The training covers several key areas: **Course Objectives and Coverage** - Understanding AI foundations, development lifecycle, and societal impacts - Mastering responsible AI principles and risk management - Ensuring regulatory compliance and ethical AI implementation **Key Topics and Modules** 1. Foundations of AI: AI and machine learning basics, types of AI systems, and technology stack 2. AI Impacts and Responsible AI Principles: Core risks, trustworthy AI characteristics, and ethical guidelines 3. AI Development Lifecycle: Risk management, ethical guidance, and relevant laws (e.g., GDPR) 4. Regulatory Compliance and Risk Management: Compliance strategies and risk management frameworks 5. Implementation and Governance: AI project planning, system testing, and post-deployment monitoring **Learning Objectives** - Understand AI governance principles and frameworks - Implement risk management strategies for AI systems - Ensure regulatory compliance and alignment with organizational goals - Foster ethical AI decision-making and accountability - Build transparent AI systems and implement effective auditing processes **Target Audience** The training is designed for professionals in various fields, including: - Compliance, privacy, and security experts - Risk management and legal professionals - Data scientists and AI project managers - Business analysts and AI product owners - Model ops teams and HR professionals **Certification and Assessment** Courses often lead to certifications such as: - Artificial Intelligence Governance Professional (AIGP) - Certified AI Governance Specialist (CAIGS) These certifications typically involve comprehensive exams covering AI governance principles, ethical practices, risk management, and regulatory compliance. **Delivery and Resources** Training is delivered through various formats, including: - Online modules and interactive video-based training - Lectures and interactive discussions - Hands-on workshops and case studies Participants usually have access to official learning materials, exam vouchers, and additional resources to support their learning journey. By completing these courses, professionals gain the necessary expertise to ensure the safe, ethical, and compliant development and deployment of AI systems within their organizations.

A

AI Edge Computing Engineer specialization training

To specialize as an AI Edge Computing Engineer, focus on these key areas and skills: ### Core Responsibilities - Model Development and Optimization: Design and implement ML models optimized for edge devices, considering constraints like limited computational power, memory, and energy consumption. - Data Management: Handle data collection, preprocessing, and storage at the edge, ensuring integrity, security, and compliance. - Deployment and Integration: Deploy AI models on various edge devices and ensure seamless integration with existing systems. - Hardware and Software Selection: Choose appropriate hardware components and software platforms for edge computing applications. - Networking and Connectivity: Design network architectures supporting efficient data transmission between edge devices and central systems. - Edge Analytics and AI: Develop systems for real-time data analytics at the edge, implementing ML models and data processing algorithms. - Security and Compliance: Implement robust security measures and ensure compliance with relevant regulations. ### Technical Skills - Programming Languages: Python, C/C++, Java, or Rust - Machine Learning Frameworks: TensorFlow, PyTorch, TensorFlow Lite, PyTorch Mobile, or ONNX - Edge Computing Platforms: NVIDIA Jetson, Google Coral, ARM Cortex - Data Processing: Experience in data preprocessing and pipeline optimization - Software Development: Best practices, DevOps, version control, and CI/CD processes ### Training and Coursework - Fundamentals of Edge Computing: Principles, applications, and differences from cloud computing - Edge AI and Edge Computer Vision: Applications, hardware evaluation, and model deployment - Practical Experience: Hands-on learning with tools like TensorFlow and edge computing hardware - Advanced Topics: Model optimization techniques, data management at the edge, and AI integration with edge computing solutions ### Career Progression and Industry Trends - Progress from junior roles in AI model development to senior roles involving strategic AI initiatives - Stay updated on trends such as increased IoT adoption, 5G technology advancements, and privacy-focused edge AI solutions By focusing on these areas, you can excel as an AI Edge Computing Engineer, creating efficient, low-latency AI solutions for various applications.