Deep Tech

• Scientific Foundation
  Deep tech innovations are built on groundbreaking scientific discoveries or cutting-edge engineering advancements. These breakthroughs often emerge from years of rigorous research conducted in academic institutions or corporate laboratories. The scientific foundation of deep tech sets it apart from conventional technology, as it pushes the boundaries of current knowledge and capabilities.
• Long R&D Cycles
  The development of deep tech solutions typically requires extended periods of research and experimentation, often spanning a decade or more. This prolonged R&D phase is necessary to refine the technology, overcome technical challenges, and prove its viability. The lengthy development cycle also means that outcomes are often uncertain, requiring patience and persistence from investors and innovators alike.
• High R&D Intensity
  Deep tech ventures are characterized by their intense focus on research and development, particularly in the early stages. This high R&D intensity often involves significant technical risks as companies work to overcome complex scientific and engineering challenges. Substantial financial resources are typically allocated to technology development, with a particular emphasis on hardware-related innovations that can take years to perfect.
• Ambitious Goals
  Deep tech projects are driven by audacious objectives that aim to revolutionize entire industries or create entirely new market segments. These ambitious goals often address complex, large-scale societal challenges that conventional technologies have struggled to solve. By pursuing such lofty aims, deep tech has the potential to reshape our world and improve lives on a global scale.
• Mission-Driven
  Many deep tech ventures are fueled by a strong sense of purpose, focusing on solving pressing global issues such as climate change, sustainable energy production, or incurable diseases. This mission-driven approach often attracts passionate individuals who are committed to making a significant positive impact on society. The alignment of technological innovation with societal needs gives deep tech ventures a unique position in the innovation landscape.
• Capital Intensive
  Deep tech initiatives typically require substantial upfront investments from specialized investors who understand the long-term nature of these projects. The capital-intensive nature of deep tech is due to the need for advanced research facilities, cutting-edge equipment, and highly skilled personnel. These significant financial requirements often pose a challenge for deep tech startups, necessitating strategic partnerships and patient capital to bring their innovations to market.
• Global Scope
  Deep tech ventures often have a global outlook from their inception, recognizing that their innovations have the potential to address worldwide challenges. This international perspective influences everything from research collaborations to market strategies. The global nature of deep tech also means that these ventures must navigate complex international regulations, cultural differences, and diverse market conditions.
• Founding Teams with Advanced Technical Backgrounds
  Deep tech companies are typically founded by individuals with extensive technical expertise and academic credentials. These founders often bring years of specialized knowledge and research experience to their ventures, having spent significant time in higher education or corporate R&D environments. The advanced technical backgrounds of deep tech founders enable them to navigate complex scientific challenges and translate cutting-edge research into practical applications.
• Intellectual Property
  Intellectual property (IP) plays a crucial role in the deep tech ecosystem, with companies often relying on patents and other forms of IP protection to safeguard their innovations. Strong IP portfolios not only protect a company’s technological advancements but also serve as valuable assets that can attract investors and partners. The process of securing and maintaining IP rights is often complex and costly for deep tech ventures, requiring careful strategy and significant resources.

• Artificial Intelligence and Machine Learning
  AI and ML are transforming industries by enabling machines to learn from data and make intelligent decisions. Advanced AI systems are now capable of natural language processing, allowing for more intuitive human-computer interactions. Computer vision technologies are enhancing image and video analysis capabilities, while predictive analytics is revolutionizing decision-making processes across various sectors.
• Robotics and Automation
  The field of robotics is rapidly evolving, with next-generation industrial robots increasing efficiency and precision in manufacturing. Humanoid service robots are being developed to assist in healthcare and customer service settings. Surgical bots are enhancing the capabilities of medical professionals, while autonomous drones are finding applications in logistics, agriculture, and surveillance.
• Biotechnology and Genomics
  Advancements in genetics and genomics are paving the way for personalized medicine and more effective treatments. Synthetic biology is enabling the creation of novel materials and sustainable fuels. These technologies are also revolutionizing agriculture, allowing for the development of more resilient and nutritious crops.
• Quantum Computing
  Quantum computers are being developed to tackle complex problems that are beyond the capabilities of classical computers. These systems have the potential to revolutionize cryptography, accelerate drug discovery processes, and optimize financial models. Quantum algorithms are being designed to solve specific problems in various fields, promising significant advancements in computational power.
• Blockchain
  Blockchain technology is creating secure and transparent systems that extend far beyond cryptocurrencies. This decentralized approach is being applied to supply chain management, voting systems, and digital identity verification. Blockchain’s potential for creating trust in digital transactions is opening up new possibilities for secure and efficient data management across industries.
• Advanced Materials
  Scientists are engineering materials at the molecular level to create products with unprecedented properties. These advanced materials offer enhanced electrical conductivity, thermal resistance, and structural integrity. Applications range from more efficient solar panels to lightweight yet strong materials for aerospace and automotive industries.
• Nanotechnology
  By manipulating matter at the atomic and molecular scale, nanotechnology is enabling the development of materials and devices with unique properties. This field is driving innovations in medicine, electronics, and energy storage. Nanotech applications include targeted drug delivery systems, ultra-efficient batteries, and self-cleaning surfaces.
• Clean Energy Technologies
  The development of advanced power production methods is crucial for addressing global energy challenges. Research in nuclear fusion promises a potentially limitless and clean energy source. Advanced battery technologies are improving energy storage capabilities for renewable sources. Innovations in solar, wind, and other renewable energy solutions are making clean energy more accessible and efficient.
• Aerospace and Space Technology
  Innovations in spacecraft design are making space exploration more feasible and cost-effective. Advanced satellite systems are improving global communication and Earth observation capabilities. New propulsion technologies and materials are enabling longer and more ambitious space missions, paving the way for potential human colonization of other planets.
• Photonics and Electronics
  Advancements in light-based technologies are revolutionizing communications and computing. Next-generation electronic systems are becoming smaller, faster, and more energy-efficient. These technologies are enabling the development of high-speed optical communications, advanced sensing devices, and more powerful computing systems.

• Funding and Investment
  Deep tech ventures require substantial capital due to long R&D cycles and high initial costs. Securing adequate funding, especially for early-stage companies, remains a challenge.
• Talent and Expertise
  Attracting and retaining specialized talent in advanced scientific and engineering domains is difficult, particularly in competitive markets.
• Regulatory and Legal Hurdles
  Deep tech innovations often face complex regulatory landscapes, as existing regulations may not adequately cover novel technologies.
• Technology Adoption and Market Acceptance
  Introducing disruptive deep tech solutions to the market can be challenging, requiring companies to overcome resistance to change and demonstrate clear benefits over existing solutions.
• Scaling and Commercialization
  Deep tech startups face multiple “valleys of death” when transitioning from research to viable products, including the initial commercialization gap, post-seed capital crunch, and market validation cliff.
• Intellectual Property Protection
  Ensuring robust IP protection is crucial but complex and expensive, especially when dealing with international patent laws.
• Collaboration and Ecosystem Development
  Establishing strong partnerships and fostering a supportive ecosystem among academia, industry, and government is essential but challenging.
• Energy and Infrastructure Requirements: As AI and other computationally intensive technologies continue to dominate deep tech, addressing the energy requirements for development and deployment is becoming a critical challenge.

• Scientific Foundation
  Deep tech is rooted in significant scientific advances or high-tech engineering innovations, often originating from academic research or corporate R&D labs.
• Long R&D Cycles
  Deep tech typically requires extensive research and development periods, often spanning 10 to 15 years or more.
• High R&D Intensity
  These ventures are characterized by intense early-stage research and development and elevated technical risks.
• Ambitious Goals
  Deep tech projects aim for breakthroughs that can fundamentally change industries or create entirely new ones, often addressing large-scale societal challenges.
• Capital Intensive
  Deep tech initiatives generally demand substantial initial investments from specialized investors, along with specialized equipment, facilities, and skills.
• Intellectual Property
  Deep tech companies often own patents or other forms of intellectual property protection for their innovations.

• Market-Ready Solutions
  High-tech companies typically develop products or services that are closer to market readiness compared to deep tech innovations.
• Shorter Development Cycles
  While still involving advanced technology, high-tech products generally have shorter development timelines than deep tech innovations.
• Application-Focused
  High tech often involves applying existing technologies in innovative ways to solve practical problems or improve existing solutions.
• Lower Entry Barriers
  Compared to deep tech, high-tech ventures generally face lower entry barriers in terms of initial investment and technical expertise required.
• Rapid Iteration
  High-tech companies often employ agile development methodologies, allowing for quick iterations and adaptations based on market feedback.

• Innovation Depth
  • Deep Tech: Focuses on groundbreaking scientific advancements and fundamental research.
  • High Tech: Emphasizes practical applications with incremental improvements to existing technologies.
• Development Complexity
  • Deep Tech: Involves intricate scientific understanding and high technological barriers.
  • High Tech: Generally, has lower entry barriers and is more accessible to a broader range of entrepreneurs and companies.
• Impact Horizon
  • Deep Tech: Aims for transformative, long-term impact on industries and society.
  • High Tech: Often targets immediate, practical impact with shorter-term considerations.
• Research and Development
  • Deep Tech: Requires longer development cycles, often involving interdisciplinary collaboration.
  • High Tech: Typically has shorter development timelines, responding more quickly to market demands.
• Funding Requirements
  • Deep Tech: Often requires substantial capital investment over extended periods.
  • High Tech: While still capital-intensive, generally requires less initial investment than deep tech ventures.
• Risk Profile
  • Deep Tech: Faces higher technical risks due to the uncertainty of scientific research outcomes.
  • High Tech: While still risky, generally faces lower technical risks but may encounter higher market risks.
• Talent Requirements
  • Deep Tech: Often requires highly specialized talent with advanced degrees in specific scientific or engineering fields.
  • High Tech: While still needing skilled professionals, may have a broader talent pool to draw from.

• Deep Tech Examples
  • Quantum computing: This revolutionary technology harnesses the principles of quantum mechanics to perform complex calculations exponentially faster than classical computers. Quantum computers have the potential to solve problems that are currently intractable, such as simulating molecular interactions for drug discovery or optimizing complex financial models. The development of quantum computing requires overcoming significant scientific and engineering challenges, including maintaining quantum coherence and scaling up the number of qubits.
  • CRISPR gene editing: CRISPR-Cas9 is a groundbreaking gene-editing tool that allows scientists to make precise changes to DNA sequences in living organisms. This technology has the potential to revolutionize medicine by enabling the treatment of genetic disorders, developing new therapies for cancer, and even enhancing crop resistance to pests and climate change. The development of CRISPR technology required fundamental breakthroughs in molecular biology and continues to push the boundaries of our understanding of genetics.
  • Nuclear fusion energy: Nuclear fusion, the process that powers the sun, promises to provide a nearly limitless source of clean energy. Achieving controlled fusion on Earth requires overcoming immense scientific and engineering challenges, such as containing plasma at temperatures hotter than the sun’s core. Successful development of fusion energy could revolutionize global power production and help address climate change.
  • Advanced materials science: This field involves the discovery and development of new materials with extraordinary properties, often at the atomic or molecular level. Advanced materials, such as graphene, metamaterials, and smart polymers, have the potential to revolutionize industries ranging from electronics to aerospace and healthcare. The development of these materials often requires interdisciplinary research combining physics, chemistry, and engineering.
  • Brain-computer interfaces: These devices create direct communication pathways between the brain and external devices, potentially allowing control of computers or prosthetics through thought alone. The development of brain-computer interfaces involves complex challenges in neuroscience, signal processing, and bioengineering. Successful implementation could transform the lives of people with disabilities and open up new frontiers in human-machine interaction.
• High Tech Examples
  • Smartphone technology: Modern smartphones combine advanced computing power, high-resolution displays, and multiple sensors in a compact, portable device. They leverage existing technologies in novel ways to provide a wide range of functionalities, from communication and photography to navigation and health monitoring. The rapid evolution of smartphone technology demonstrates the iterative nature of high-tech innovation, with new models introducing incremental improvements in performance and features.
  • Cloud computing services: Cloud computing provides on-demand access to computing resources over the internet, enabling businesses and individuals to scale their IT capabilities without significant upfront investments. This technology leverages existing networking and virtualization technologies to create flexible, scalable computing environments. The development of cloud services has transformed the IT industry and enabled new business models across various sectors.
  • Electric vehicles: Electric cars represent a high-tech evolution of traditional automobiles, replacing internal combustion engines with electric motors and batteries. While based on established principles of electric propulsion, modern EVs incorporate advanced technologies in battery management, power electronics, and regenerative braking. The rapid advancement of electric vehicle technology demonstrates how high-tech innovation can drive significant changes in established industries.
  • 5G networks: The fifth generation of cellular network technology offers significantly faster data speeds, lower latency, and increased connectivity compared to previous generations. 5G technology builds upon existing telecommunications infrastructure while introducing new techniques such as massive MIMO and beamforming. The rollout of 5G networks is enabling new applications in areas such as IoT, autonomous vehicles, and augmented reality.
  • Advanced manufacturing robotics: Industrial robots have become increasingly sophisticated, incorporating advanced sensors, machine vision, and AI to perform complex manufacturing tasks with high precision and flexibility. These robots build upon decades of development in automation and control systems, with recent advancements focusing on collaborative robots that can safely work alongside humans. The integration of advanced robotics in manufacturing demonstrates how high-tech innovations can significantly enhance productivity and quality in traditional industries.

• Investment Strategies
  Venture capitalists and investors may adopt different approaches when funding deep tech versus high-tech ventures, considering the varying risk profiles and time horizons.
• Government Support
  Many governments provide specific support and funding programs for deep tech research and development, recognizing its potential for long-term economic and societal impact.
• Educational Focus
  Universities and research institutions may align their programs and collaborations differently to support deep tech versus high-tech innovation.
• Corporate Strategy
  Large technology companies often maintain a portfolio of both high-tech products and deep tech research initiatives to balance short-term market needs with long-term innovation goals.

• Manufacturing and Industry 4.0
  Deep tech is driving the fourth industrial revolution, known as Industry 4.0. Smart factories are emerging based on industrial IoT sensors, adaptive robotics, AI process control, and advanced simulation. These technologies enable:
  • Real-time equipment performance monitoring
  • Optimized workflows through machine learning algorithms
  • Precision handling of delicate parts by robotic arms
  • Automated quality control using computer vision
  • Novel product architectures through generative design

The integration of these technologies is leading to increased efficiency, reduced downtime, and higher quality products.

• Healthcare and Biotechnology
  In healthcare, deep tech is enabling more accurate diagnostics, personalized medicine, advanced gene therapies, robotic surgery, and improved drug discovery. Specific advancements include:
  • AI-powered analysis of radiological images for early tumor detection
  • DNA test screening for targeted treatments based on patient genetics
  • Accelerated pharmaceutical R&D through quantum computing simulations
  • Enhanced surgical precision using advanced robotics

These innovations are not only improving patient outcomes but also potentially reducing healthcare costs and increasing accessibility to advanced treatments.

• Transportation and Mobility
  The transportation industry is being revolutionized by deep tech through:
  • Autonomous vehicles guided by deep learning algorithms
  • Ultra-precise positioning using quantum sensors
  • Lightweight, stronger vehicle components developed through computational modelling
  • Efficient fleet management and delivery optimization using AI algorithms

These advancements promise to enhance safety, reduce environmental impact, and transform urban mobility.

• Energy and Sustainability
  Deep tech is driving the transition to renewable resources and smarter, more resilient energy grids. Key developments include:
  • Advanced batteries for cost-effective storage of solar and wind energy
  • New catalysts for clean hydrogen fuel production
  • Quantum techniques for identifying carbon-absorbing materials
  • AI-powered balancing of electricity supply and demand in smart grids

These innovations are crucial in addressing climate change and ensuring sustainable energy production for the future.

• Solving Complex Global Challenges
  Deep tech ventures are often motivated by a desire to solve significant societal challenges, such as climate change, energy transitions, or chronic diseases. By addressing these issues, deep tech has the potential to improve quality of life on a global scale.
• Economic Growth and Job Creation
  The deep tech sector is driving economic growth and job creation. A Boston Consulting Group study revealed that global private investment in deep tech fields increased more than 20% annually from 2015, reaching almost $18 billion in 2018. This growth is creating new industries and job opportunities, particularly in high-skilled sectors.
• Education and Skill Development
  The rise of deep tech is reshaping educational needs and workforce skills. There is an increasing demand for individuals with advanced technical backgrounds, often requiring five to seven years in higher education. This trend is driving changes in educational curricula and professional development programs.
• Ethical Considerations and Societal Debates
  As deep tech advances, it raises important ethical questions and societal debates. Issues such as data privacy, algorithmic bias, and the societal implications of technologies like AI and genetic engineering are becoming increasingly important topics of public discourse.

• New Business Models and Market Opportunities
  Deep tech is ushering in a new era of innovation, giving rise to entirely new markets and revolutionary business models. Companies that successfully harness deep tech innovations have the potential to disrupt existing industries or even create entirely new ones. This transformative power of deep tech is reshaping the competitive landscape across various sectors.
• Investment Landscape
  The deep tech sector has become a magnet for significant investment, with Europe alone expected to generate over 8 trillion euros in value creation by 2030. This immense potential is causing a shift in investment strategies, with venture capitalists and large corporations increasingly directing their focus and resources towards deep tech startups. The growing interest in deep tech is reshaping the funding ecosystem, creating new opportunities for innovative companies to secure the capital they need to bring their groundbreaking ideas to market.
• Corporate Strategy and Innovation
  Large companies are increasingly recognizing deep tech as a critical factor in maintaining their long-term competitiveness in a rapidly evolving business environment. To tap into the potential of deep tech innovations, many corporations are establishing dedicated R&D units, forging partnerships with startups, or creating venture funds. This strategic shift reflects the growing understanding that deep tech is not just a passing trend, but a fundamental driver of future growth and innovation across industries.
• Global Competition
  Deep tech has emerged as a key battleground in global economic competition, with countries and regions vying for leadership in various deep tech fields. Nations are recognizing the potential of deep tech to drive future economic growth, enhance technological sovereignty, and secure a competitive edge in the global marketplace. This intensifying competition is spurring increased investment in research, development, and commercialization of deep tech innovations at a national and regional level.

• Cross-disciplinary Innovation
  Deep tech often requires expertise from multiple disciplines. Collaboration enables the formation of multidisciplinary teams, enhancing problem-solving capabilities and driving more holistic solutions. For instance, projects that bring together experts in AI, material science, and biology can lead to breakthroughs in areas like advanced robotics or synthetic biology.
• Resource Optimization
  Deep tech ventures typically require substantial financial and human resources. Collaboration leads to resource optimization by pooling expertise, sharing infrastructure, and reducing redundant efforts. Shared research facilities and open innovation platforms allow multiple entities to leverage advanced equipment and data, reducing costs and duplication.
• Risk Mitigation
  The high-risk nature of deep tech projects makes risk mitigation a priority. Collaborative ecosystems enable the distribution of risks across multiple stakeholders, making it easier to manage and absorb setbacks. This risk-sharing approach encourages more bold and ambitious projects, as potential losses are not borne by a single entity.
• Knowledge Exchange
  Collaboration fosters the cross-pollination of ideas. When organizations share knowledge, they enable collective problem-solving, leading to more robust and diverse solutions. Partnerships between academia and industry can bridge the gap between theoretical research and practical application, enhancing the relevance and scalability of technological advancements.

• Nurturing Innovation
  A well-developed ecosystem provides the necessary support structure for deep tech ventures to thrive. This includes access to funding, mentorship, and specialized facilities. For example, the European Innovation Council (EIC) is set to invest €1.4 billion in 2025 to support deep tech research and high-potential startups.
• Talent Development
  Ecosystems play a crucial role in attracting, developing, and retaining specialized talent. They create environments where experts from various fields can collaborate and grow. Deep tech ventures typically require founders with strong technical backgrounds, often with five to seven years in higher education.
• Market Access
  Collaborative ecosystems can facilitate market expansion by combining complementary technologies and expertise. Strategic partnerships can create more comprehensive solutions that address broader market needs, making it easier to enter new markets and attract a diverse customer base.
• Policy and Regulatory Support
  Ecosystems often involve government participation, which can lead to favourable policies and regulatory frameworks. This support is crucial for deep tech ventures, which often face complex regulatory landscapes due to their innovative nature.

• Open Source Initiatives
  Open source has played a transformative role in deep tech by fostering collaboration, transparency, and rapid innovation. Examples include the success of open-source AI frameworks like TensorFlow and PyTorch, which demonstrate how community involvement can drive rapid advancements and adoption.
• Research Alliances and Consortia
  Formal frameworks for collaboration, such as research alliances and consortia, bring together different stakeholders, including corporations, startups, academic institutions, and government bodies. These frameworks outline clear guidelines for IP sharing, data use, and governance to ensure equitable and effective collaboration.
• Deep Tech Hubs and Incubators
  Specialized hubs and incubators provide crucial support for deep tech startups. For instance, the DeepTech Alliance, a collaboration of 11 European startup hubs, connects deep tech startups with investors and established companies. Such initiatives have led to significant results, including 123 collaborations between startups and established companies.
• Corporate-Startup Partnerships
  Collaborations between large corporations and deep tech startups can be mutually beneficial. Corporates provide resources, market access, and business guidance, while startups bring innovative technologies and agile approaches. Companies like BCG and Hello Tomorrow play a role in connecting deep tech entrepreneurs with corporations and investors.

• Intellectual Property Concerns
  Intellectual property (IP) management is a critical and complex issue in deep tech collaborations. Deep tech companies often rely heavily on their patents and other forms of IP protection to safeguard their innovations and maintain competitive advantage. Balancing the need for open collaboration with the imperative to protect valuable IP requires careful negotiation and clear guidelines, especially in multi-party projects involving academia, startups, and established corporations.
• Cultural Differences
  The deep tech ecosystem brings together entities with vastly different cultures, priorities, and working styles. Academic institutions typically focus on long-term research and publication, while startups prioritize rapid development and market entry, and corporations often emphasize scalability and profitability. Bridging these cultural gaps requires mutual understanding, clear communication, and flexible collaboration frameworks that can accommodate diverse perspectives and goals.
• Long-term Commitment
  The extended development cycles characteristic of deep tech projects pose significant challenges for maintaining stakeholder commitment. With timelines often spanning a decade or more, it can be difficult to sustain funding, team motivation, and strategic focus over such long periods. This challenge is particularly acute for startups and academic partners, who may face pressure for shorter-term results or shifts in research priorities.
• Global Competition
  While global competition in deep tech can drive innovation, it can also create barriers to international collaboration. Nations and regions competing for leadership in strategic deep tech fields may implement protectionist policies or restrict knowledge sharing. Navigating this competitive landscape while fostering necessary international collaborations requires careful diplomacy and a balance between national interests and global scientific advancement.

• Long Development Cycles
  Deep tech projects often have extended R&D periods, which can span 10 to 15 years or more. This long timeline necessitates careful planning of IP strategies to ensure protection throughout the development process and beyond.
• High Costs
  Securing and maintaining IP protection, especially on a global scale, can be expensive. This presents a significant challenge for early-stage deep tech startups with limited resources.
• Complex Patent Landscapes
  Many deep tech fields involve intricate patent landscapes, requiring careful navigation to avoid infringement while ensuring broad protection for innovations.
• Balancing Disclosure and Protection
  Deep tech companies must balance the need to protect their innovations with the imperative to publish research findings, particularly when collaborating with academic institutions.
• International Considerations
  Given the global nature of deep tech, companies must navigate international IP laws and treaties, which can be complex and vary significantly between jurisdictions.

• Early Engagement
  Initiating IP strategies at the earliest stages of development is crucial for deep tech companies. This proactive approach allows for the creation of a comprehensive IP pipeline, encompassing patents, trade secrets, and other valuable assets. By engaging early, companies can ensure that their innovations are protected from the outset, potentially deterring competitors and securing a strong market position.
• Diverse IP Portfolio
  Building a diverse IP portfolio is essential for creating a robust defence against potential competitors. This strategy involves leveraging various forms of IP protection, including patents, trade secrets, copyrights, and trademarks. A well-rounded IP portfolio not only protects different aspects of a company’s innovations but also provides flexibility in enforcement and licensing strategies.
• Strategic Patenting
  Adopting a forward-thinking patent strategy is critical for long-term success in the deep tech sector. This approach involves anticipating future technological trends and potential market expansions when filing patents. By strategically patenting key innovations and their potential applications, companies can secure a competitive advantage in emerging markets and technologies.
• Collaboration Agreements
  When engaging in collaborative projects, especially with academic institutions or industry partners, it’s crucial to establish clear IP guidelines. These agreements should outline ownership rights, usage permissions, and confidentiality requirements. Clear IP guidelines help prevent disputes, protect each party’s interests, and ensure smooth collaboration throughout the project lifecycle.
• Continuous Monitoring
  Regular monitoring of the IP landscape is essential for identifying both risks and opportunities. This ongoing process helps companies detect potential infringement of their IP rights by competitors. Additionally, it can reveal opportunities for licensing or acquiring complementary technologies, enabling companies to strengthen their market position and expand their technological capabilities.
• Global Protection
  For deep tech companies with international ambitions, utilizing global IP protection mechanisms is crucial. The Patent Cooperation Treaty (PCT) and other international agreements can streamline the process of securing IP rights across multiple jurisdictions. This approach helps companies protect their innovations in key markets worldwide, providing a foundation for global expansion and partnerships.
• Open Innovation
  Embracing open innovation platforms for non-core IP can be a strategic move for deep tech companies. This approach can extend the applications of a company’s technology beyond its primary focus. Open innovation can also generate new revenue streams through partnerships and collaborations, allowing companies to benefit from external expertise and resources while maintaining control over their core IP.