Deep Tech
What is Deep Tech?
Deep tech, or deep technology, refers to technology grounded in genuine scientific or engineering advances. These innovations push the boundaries of what is technically possible and often involve long research and development cycles, high technical uncertainty, and significant investment before reaching the market.
Unlike incremental or purely digital products, deep tech creates enduring value through intellectual property, specialised know-how, and the potential for transformative social and environmental impact.
Why I Focus on Deep Tech
I focus on Deep tech because it enables solutions that reach beyond short-term market trends. By converting fundamental research into practical applications, it builds technologies with long lifespans and strong competitive advantage.
Deep tech also bridges disciplines — science, design, engineering, business, and policy — to address the systemic problems that define our time, from clean energy to health resilience and climate adaptation. Supporting this kind of innovation means investing in a better future.
Fields of Deep Tech Innovation
Deep tech spans many domains, each driven by scientific progress and engineering depth. These include advanced materials, clean energy systems, artificial intelligence, biotechnology, robotics, quantum computing, advanced manufacturing, and secure digital infrastructure.
Although the fields vary widely, what connects them is a shared pursuit of fundamental improvement — building technologies that redefine industries rather than simply optimise them.
Advanced Computing / Quantum Computing
This area focuses on innovations in high-performance computing to handle large-scale data processing and operations efficiently. It is closely linked with semiconductor development and the growth of Big Data generated by IoT, 5G, and other digital operations. Key technologies include:
Quantum Computing: Using subatomic particles like electrons and photons, along with qubits, to process information in multidimensional states. Applications range from fundamental quantum research and prototype development to applied solutions in sectors such as climate science and healthcare.
Edge Computing: Bringing computation and analytics closer to the data source. This includes methods for handling sensor networks, high-volume data streams, predictive analytics, and reducing latency and bandwidth issues, with applications in manufacturing, energy, finance, and retail.
Cloud Computing: Improving the efficiency, security, and speed of data operations hosted online. It encompasses optimisation of software, hardware, networks, databases, analytics, and intelligent systems.
Other Technologies: Research into new computer architectures, software systems, programming languages, next-generation high-performance computing, and energy-efficient runtimes.
Advanced Manufacturing
This domain covers diverse production technologies, often overlapping with robotics, AI/ML, VR/AR, 5G, digital twins, and edge computing:
Industry 4.0: Technologies at the intersection of robotics, AI, biotechnology, IoT, 5G, 3D printing, nanotechnology, and advanced computing.
Robotics: Industrial automation through robots and collaborative robots (cobots) for a wide range of applications, including factory floors, warehouses, and energy sectors.
Rapid Prototyping: Includes 3D and 4D printing technologies for rapid product development.
Circular Manufacturing: Solutions for sustainable production, including recycling, energy efficiency, and low-carbon processes.
Digital Twins: Digital replicas of manufacturing workflows to monitor, model, and optimise productivity.
IoT and Sensoring: Using IoT devices and sensors to track production performance, quality, durability, and traceability.
Advanced Materials
This area involves the design, development, and production of materials with engineered properties, such as ceramics, metals, composites, polymers, and biomaterials:
Polymers: Functional polymers for gas separation, filtration, medical devices, and consumer electronics.
Nanostructured Materials: Carbon composites, nanotubes, and other nanoscale structures.
Synthetic Fabrics and Wearables: Smart textiles with technological, thermal, or water-resistant properties.
High Value-Added Metals and Materials: Metals and ceramics engineered for high resistance, conductivity, or extreme environments like space and subsurface exploration.
Biomaterials: Engineered biological or synthetic materials for medical or biological applications.
Other Innovative Materials: Composites, enhanced wood-based products, and other advanced materials.
Aerospace, Automotive & Remote Sensing
This domain focuses on mobility, transport, space technology, and the associated sensing and data systems:
Automotive Technology: Autonomous vehicles, AI-driven sensors, clean energy, decarbonisation, energy storage, smart transport applications, and novel materials.
Aviation Technology: Drones, self-piloting and VTOL aircraft, aviation decarbonisation, AI-assisted platforms, and new materials.
Space Technology: Satellite and spacecraft innovation, micro-satellites, launch methods, space debris management, cryogenic technologies, and materials for space exploration.
Sensoring and Data: Advanced sensing, data collection, and analysis systems including laser or camera-based technologies and AI for image recognition.
AI, Machine Learning & Big Data
This area explores the use of data science and algorithms to extract insight and automate tasks:
Big Data: Collecting, processing, and analysing large-scale data from IoT, finance, retail, and other sectors.
Data Mining: Identifying patterns, anomalies, and correlations in large datasets for predictive analytics.
Machine Learning: Developing algorithms that learn from data using supervised, unsupervised, or reinforcement methods, including neural networks and computational statistics.
Artificial Intelligence: Applying algorithms to simulate human intelligence in areas such as natural language processing, computer vision, expert systems, and automation.
Biotechnology & Life Sciences
This field covers natural and synthetic materials, genetics, and digital tools for health and bioeconomy:
Data-Intensive Science & Bioinformatics: Using large datasets for health and biological research.
Clinical Research: Advanced trials and analysis of treatments.
Cellular and Gene Technologies: Gene therapies, cell analysis, and bio-manufacturing.
Medical Devices & Implants: Improving devices, including neural implants and minimally invasive surgery.
Precision Medicine: Data-driven optimisation of treatment and pharmaceutical delivery.
Circular Bioeconomy & Agri-Tech: Sustainable materials, food-chain solutions, and organic recycling.
Open Source Medical Innovation: Shared research and collaborative solutions in healthcare.
Communications & Networks
This area develops high-performance and secure communication systems:
5G / 6G Networks: High-speed, high-capacity networks for data-intensive applications, AR/VR, and edge computing.
Other Communications Technologies: Fiber optics, lasers, microwave systems, and RF spectrum management.
Navigation Systems: Satellite, underwater, and marine navigation technologies.
Telematics and Materials: Smart antennas, distributed antennas, circuit boards, and vehicle communication technologies.
Communications Security: Encryption, quantum keys, and intrusion testing for secure communications.
Cybersecurity & Data Protection
Focuses on safeguarding networks, data, and critical infrastructure:
IoT and 5G Security: Ensuring safe operation of connected devices and communication networks.
ML and AI in Security: Applying algorithms for encryption, intrusion detection, and threat analysis.
Encryption Systems: Developing and testing new cryptography methods, including quantum encryption.
Intrusion Detection: Signature, anomaly, and hybrid detection methods.
Privacy-Enhancing Technologies: GDPR and privacy-focused solutions.
Electronics & Photonics
This field includes technologies used in semiconductors, quantum computing, and photonics:
Quantum Computing: Multidimensional information processing with qubits.
Microelectronics & Circuit Boards: Advancing chip design, memory, speed, and efficiency, including nanomaterials and 3D structures.
Photonic Engineering: Lasers, sensors, imaging systems, displays, and energy applications.
Haptic, AI, and VR/AR Engineering: Micro-scale testing and simulation using immersive technologies.
Power Management: Optimising power for electronics and photonic systems.
Internet of Things, W3C, Semantic Web
Covers interconnected devices, protocols, and systems:
IoT Devices: Intelligent devices capable of communication and sensing.
Communications Protocols: Standards for interoperability, including Bluetooth, 5G, Matter, and Thread.
Mesh and Embedded Systems: Distributed computing and sensor-enabled systems.
Automation & Sensoring: Intelligent monitoring and control in industrial or building environments.
W3C / Semantic Web: Classifying and making internet data machine-readable.
Robotics
Includes automation hardware and software for a variety of applications:
Robotic Process Automation (RPA): Software-based automation of human tasks.
Factory Robots / Cobots: Industrial automation for tasks like assembly, transport, and warehouse operations.
Humanoid / AI Robots: Intelligent robots capable of decision-making, object recognition, and complex task execution.
Drones & Transport Solutions: Autonomous aerial, underwater, and land vehicles for transport and delivery.
Semiconductors (microchips)
Focuses on the design, fabrication, and applications of microchips:
Advanced Microchip Manufacturing: Miniaturisation, lithography, epitaxy, and 3-5 nm chip development.
Other Applications: Mobile communication, gaming, optoelectronic integration, and operation in harsh environments.
Non-Conventional Systems: Quantum, spin-based, parallel, and distributed computing architectures.
Haptic, AI, VR/AR: Supporting micro-scale simulation and production.
Power Management & Safety: Optimising energy usage and ensuring circularity and occupational safety.
Sustainable Energy & Clean Technologies
Technologies for renewable energy, storage, efficiency, and decarbonisation:
New Energy Production: Fusion, hydrogen fuel cells, electrolysers, and related technologies.
Advanced Renewables: Solar, wind, hydro innovations, and material improvements.
Energy Storage: Battery systems, addressing intermittency and efficiency challenges.
Energy Efficiency: Smart materials, building systems, and energy management solutions.
Sustainability & Cleantech: Circular economy, automation, and data-driven solutions.
Climate Change & Decarbonisation: CO2 reduction, capture, upcycling, and emission management.
Energy Forecasting & Optimisation: Using AI and Big Data to improve supply, demand, and distribution.
Virtual Reality, Augmented Reality, Metaverse
Technologies for immersive digital experiences:
Augmented Reality: Overlaying digital content on real-world environments for education, manufacturing, gaming, and more.
Virtual Reality: Fully digital environments with tracking, haptics, and immersive sensory systems.
Metaverse: Large-scale or closed 3D virtual spaces enabling interaction, commerce, and collaboration.
Other Digital Applications: Digital twins, high-fidelity simulations, wearables, and immersive display technologies.
Web 3.0, including Blockchain, Distributed Ledgers, NFTs
Next-generation internet and decentralised technologies:
Web 3.0: Decentralised, AI-enabled internet with token-based economic systems.
Blockchain: Distributed ledgers for transactions, digital ownership, and traceability.
NFTs: Unique digital tokens enabling ownership and provenance on blockchain networks.
What Deep Tech is Not
Deep tech is a very specific type of innovation, and not every technology or startup falls into this category. That doesn’t make other innovations any less valuable — it simply means they operate in a different space than the one I focus on.
Non-deep-tech innovations typically rely on existing technologies or business models, often improving usability, design, or convenience rather than creating breakthroughs in science or engineering. Examples include software tools built on established platforms, digital marketplaces, lifestyle apps, or services that optimise existing processes without requiring fundamental research.
The defining difference is that deep tech begins with a scientific or engineering discovery, and carries technical uncertainty that demands experimentation, prototyping, and often years of development before it can reach the market. By contrast, many non-deep-tech solutions can be scaled quickly because they build on proven systems rather than pushing the boundaries of knowledge or capability.
Some examples of innovations that are not considered deep tech include:
Apps or software built on existing platforms: Workflow tools, dashboards, or analytics applications that use existing technology rather than creating new algorithms or hardware.
- LLM wrappers or AI frontends: Software that adds a user interface or workflow to an existing AI model — the deep technical innovation lies in the model itself, not the wrapper.
Digital marketplaces or e-commerce platforms: Solutions that optimise buying, selling, or service delivery without underlying scientific or engineering breakthroughs.
Data visualisation or reporting tools: Dashboards or interfaces that summarise information from existing datasets.
Automation of standard processes: Robotic process automation or scripts that improve efficiency without introducing new technology.
Consumer electronics with incremental improvements: Devices that enhance usability, battery life, or interface design without fundamentally new materials, sensors, or engineering.
Optimisation of existing hardware or cloud systems: Improvements in deployment, scaling, or latency of networks or servers that don’t involve scientific breakthroughs.
The key difference is that deep tech starts with a scientific or engineering discovery, carries technical risk, and often requires interdisciplinary collaboration to translate into real-world impact. Everything else, while important, is best described as applied technology, product innovation, or software engineering.
Get in Touch
Deep tech is challenging, exciting, and full of potential — and supporting founders who work at the frontier of science and engineering is where I can add the most value. If you’re working on a breakthrough idea, navigating technical uncertainty, or exploring how to turn deep research into real-world impact, I’d love to hear from you.
Whether you’re seeking guidance, collaboration, or simply want to discuss your project, let’s connect and explore how we can bring your deep tech innovation closer to reality.