How Corporates and Startups Can Drive Deep Tech Innovation

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21 Feb 2025
4 min read

Post Highlight

Deep tech is emerging as a transformative force in global innovation, reshaping industries with groundbreaking scientific advancements. Unlike traditional digital ventures that rely on existing technologies, deep tech focuses on pioneering "first-of-a-kind" innovations, addressing complex challenges in sectors ranging from healthcare and infrastructure to finance and retail.

With venture capital and government support for deep tech doubling in the past decade, corporates and startups must rethink how they collaborate to drive innovation. Large corporations offer essential resources such as market access, technical expertise, and funding, while deep tech startups bring cutting-edge research and disruptive technologies to the table.

However, bridging the gap between scientific discovery and commercial success requires overcoming significant challenges, including high R&D costs, long development timelines, and commercialization risks.

This blog explores how corporates can effectively unlock deep tech’s potential, the critical role startups play in innovation ecosystems, and successful strategies for fostering long-term collaboration.

By embracing strategic partnerships, integrating scientific expertise, and adopting innovative funding models, businesses can position themselves at the forefront of technological breakthroughs, driving progress that benefits both industries and society.

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Deep Tech Strategies for Corporates and Startups to Succeed

The Growing Influence of Deep Tech

A Surge in Investment and Government Support

Venture capital and private equity funding for deep tech solutions addressing society’s most pressing challenges have doubled globally over the past decade. Simultaneously, governments are prioritizing deep tech due to its dual-use applications in both civilian and military domains. Through industrial and security policies, nations aim to reduce reliance on foreign technology and enhance their security.

The Need for New Collaboration Models

As deep tech gains prominence, it becomes imperative to establish collaboration models that unite research institutions, corporations, and governments. These partnerships can foster innovation ecosystems capable of supporting long-term technological breakthroughs. However, this growing emphasis on deep tech raises several fundamental questions.

Understanding Deep Tech: How It Differs from Digital Innovation

Defining Deep Tech

A crucial starting point is to define deep tech and differentiate it from digital innovation. According to deep tech expert Stefan Raff-Heinen, three key attributes set deep tech apart from traditional digital ventures.

  1. Scientific Innovation as a Foundation
    Deep tech is rooted in groundbreaking scientific advancements, often involving "first-of-a-kind" innovations that stem from extensive research. In contrast, digital startups typically create "difference-in-kind" innovations by repurposing existing digital technologies into new products or services.

  2. Navigating a Dual Risk Landscape
    Unlike digital ventures that primarily focus on commercialization challenges, deep tech startups face both technological and engineering risks. The complexity of scientific advancements adds another layer of uncertainty, making commercialization even more challenging.

  3. Hardware-Driven with Strong Intellectual Property
    Deep tech startups are often built around tangible hardware assets and highly defensible intellectual property (IP), providing a significant competitive edge. This makes them fundamentally different from software-driven businesses, which rely on fast iterations and agile development cycles.

Strategies for Corporates to Unlock Deep Tech’s Potential

Identifying Beneficial Sectors

One of the critical steps in leveraging deep tech is identifying sectors that stand to gain the most. As per Raff-Heinen, deep tech is not limited to traditional science-heavy industries. Financial services, infrastructure, and retail—sectors with relatively low R&D spending—can also benefit significantly. However, many corporations in these industries lack experience working with emerging scientific technologies.

Overcoming Common Barriers

Deep tech commercialization comes with significant hurdles, including high investment costs, lengthy development timelines, and unfamiliarity with scientific innovation. To address these challenges, Raff-Heinen, along with experts Murray and Murmann, suggests three essential strategies:

  1. Building Specialized Expertise
    Corporations must invest in hiring professionals who can navigate partnerships with scientific ventures. These specialists act as translators, bridging the gap between highly technical research and corporate objectives.

  2. Innovative Financial Strategies
    Given the high capital requirements, companies with limited R&D capabilities must explore alternative financing models. This could include forming strategic partnerships, securing government grants, and adopting shared-risk investment structures.

  3. Defining Milestones to Ensure Progress
    To align deep tech projects with corporate strategies, businesses need to establish clear milestones. Demonstrating progress is crucial to securing leadership buy-in and ensuring that initiatives continue beyond the tenure of individual executives.

Also Read: How to Attract Investors for Your Startup?

Deep Tech Startups: What They Need from Corporates

The Demand for Long-Term Partnerships

From the perspective of deep tech startups, corporate partnerships are crucial. A 2017 survey conducted by BCG and Hello Tomorrow revealed that 95% of deep tech startups seek long-term collaborations with corporations. However, only 57% have successfully formed such partnerships.

The Value Corporates Bring to Startups

Corporations offer startups invaluable resources, including:

  • Market Access – Large corporations provide customer networks and distribution channels that can help startups scale their solutions faster.

  • Technical Expertise – Collaborations allow startups to access specialized knowledge and infrastructure that may otherwise be unavailable.

  • Business Acumen – Startups benefit from corporate experience in regulatory navigation, operational management, and commercial strategy.

Case Study: Toyota and Pony.ai’s Collaboration

An exemplary corporate-startup partnership is Toyota’s collaboration with autonomous vehicle startup Pony.ai. In 2023, Toyota invested $139 million through its joint venture with GAC (a state-owned Chinese automaker) to develop a fleet of fully autonomous robotaxis.

This investment built on Toyota’s previous $400 million commitment in 2020 to accelerate the commercialization of self-driving technology. Such collaborations highlight how deep tech startups and corporates can mutually benefit from strategic partnerships.

Fostering a Collaborative Deep Tech Ecosystem

The Role of Corporates in Supporting Innovation

To unlock deep tech’s full potential, corporations must cultivate innovation-friendly environments. This includes:

  • Fostering Long-Term Partnerships – Corporates should be willing to commit to multi-year collaborations, recognizing that deep tech advancements require extended development cycles.

  • Sharing Resources – Providing access to infrastructure, testing facilities, and customer insights can help startups scale their solutions more effectively.

  • Integrating Scientific Expertise – Encouraging collaboration between corporate teams and academic researchers can drive breakthrough innovations.

The Role of Startups in Strengthening Collaborations

For deep tech startups to maximize their opportunities, they must:

  • Clearly Define Their Value Proposition – Articulating how their innovation aligns with corporate objectives can improve the chances of securing partnerships.

  • Align Goals with Corporate Priorities – Understanding and adapting to corporate strategies ensures a more seamless integration.

  • Leverage Partnerships for Commercialization – Startups should actively seek corporate support in navigating regulatory landscapes and expanding market reach.

Bridging the Gap Between Science and Market Applications

By fostering collaboration between deep tech startups and corporates, the industry can bridge the gap between groundbreaking scientific research and practical market applications. Establishing innovation-friendly ecosystems, securing financial backing, and aligning corporate and startup objectives will be key to unlocking deep tech’s transformative potential.

Top 10 Emerging Tech Startups

1. OpenAI: Pioneering the Future of Artificial Intelligence

Founders of OpenAI:

Sam Altman, Elon Musk, et al.

Total Funding of OpenAI:

$6.6 billion

Overview of OpenAI:

Since its inception in 2015, OpenAI has emerged as a dominant force in the artificial intelligence landscape. Initially founded as a non-profit AI research lab by industry leaders like Elon Musk and Sam Altman, OpenAI now focuses on developing safe artificial general intelligence (AGI) to advance human progress.

Key Developments of OpenAI:

  • Microsoft holds a 49% stake, strengthening OpenAI’s influence in the AI market.

  • Launched GPT-4 in March 2023, a breakthrough in deep learning models.

  • In February 2024, OpenAI reached a revenue milestone of US$2 billion, with a valuation exceeding US$80 billion.

2. Canva: Democratizing Design for Everyone

Founders of Canva:

Melanie Perkins, Cameron Adams, Cliff Obrecht

Total Funding of Canva:

$589M

Overview of Canva:

Canva, a graphic design platform, has revolutionized visual content creation by offering user-friendly design tools. Since its launch in Australia in 2013, Canva has made professional-quality design accessible to individuals and businesses alike.

Key Developments of Canva:

  • Provides tools for creating social media graphics, presentations, promotional merchandise, and websites.

  • Offers an extensive library of templates, attracting millions of users.

  • More than 15 billion designs have been created, with over 200 new designs generated every second.

3. Anthropic: Redefining Ethical AI

Founders of Anthropic:

Dario Amodei and Daniela Amodei

Total Funding of Anthropic:

$450 million

Overview of Anthropic:

Anthropic was founded by former OpenAI employees and is committed to advancing AI responsibly. The company has gained significant backing from Amazon, Google, Salesforce, and Zoom.

Key Developments of Anthropic:

  • Developed Claude, a direct competitor to OpenAI’s ChatGPT.

  • Released Claude 3, an AI chatbot designed to handle complex queries with enhanced ethical safeguards.

4. Celonis: Transforming Business Efficiency with AI

Founders of Celonis:

Alex Rinke, Bastian Nominacher, Martin Klenk

Total Funding of Celonis:

US$1.77 billion

Overview of Celonis:

Celonis is a German-based AI company specializing in process mining technology. It helps businesses optimize workflows, reduce waste, and improve customer experiences.

Key Developments of Celonis:

  • Its Process Intelligence platform creates digital twins for businesses, enhancing efficiency and sustainability.

  • Expanded its partnership with BMW to improve operational efficiency and environmental sustainability.

5. Mistral AI: Europe’s Rising AI Powerhouse

Founders of Mistral AI:

Arthur Mensch, Guillaume Lample, Timothée Lacroix

Total Funding of Mistral AI:

$1.05B

Overview of Mistral AI:

Mistral AI, a French AI firm founded in 2023, focuses on generative AI solutions. The company quickly gained global attention by securing substantial investments from leading venture capital firms.

Key Developments of Mistral AI:

  • Formed a strategic partnership with Snowflake in March 2024 to expand AI accessibility.

  • Launched Mistral Large, an advanced AI model available through Snowflake Data Cloud for enterprise applications.

6. Perplexity AI: Revolutionizing Conversational Search

Founders of Perplexity AI:

Aravind Srinivas, Johnny Ho, Denis Yarats, Andy Konwinski

Total Funding of Perplexity AI:

$915M

Overview of Perplexity AI:

Perplexity AI, founded in August 2022, is transforming AI-powered search engines by providing detailed, source-cited responses.

Key Developments of Perplexity AI:

  • Publicly launched its ‘first fully functional conversational answer engine’ in 2023.

  • Achieved 10 million monthly active users within two years.

7. DataRobot: Bridging AI and Enterprise Solutions

Founders of DataRobot:

Jeremy Achin & Tom de Godoy

Total Funding of DataRobot:

$1 billion

Overview of DataRobot:

DataRobot is a leader in automated machine learning, making AI accessible to businesses through its unique collaborative approach.

Key Developments of DataRobot:

  • Provides training through DataRobot University, enabling organizations to implement AI-driven solutions.

  • Helps enterprises build, monitor, and deploy AI safely at scale.

8. Inflection AI: Advancing Conversational AI

Founders of Inflection AI:

Mustafa Suleyman & Reid Hoffman

Total Funding of Inflection AI:

$1.525 billion

Overview of Inflection AI:

Founded in 2022, Inflection AI specializes in AI-driven hardware and applications, focusing on empathetic conversational AI models.

Key Developments of Inflection AI:

  • Developed Pi, an AI chatbot designed for emotional intelligence and conversational depth.

  • The company’s AI studio integrates top-tier developers and designers to create innovative AI experiences.

9. Scale AI: Accelerating AI Development with High-Quality Data

Founders of Scale AI:

Alexandr Wang & Lucy Guo

Total Funding of Scale AI:

$1 billion

Overview of Scale AI:

Scale AI enhances machine learning models by providing high-quality labeled data. The company focuses on data labeling, dataset management, and AI-driven solutions.

Key Developments of Scale AI:

  • Secured US$1 billion in funding in May 2024 at a US$14 billion valuation.

  • Offers an end-to-end solution for managing machine learning lifecycles.

10. Wayve: Pioneering Autonomous Mobility with AI

Founders of Wayve:

Alex Kendall

Total Funding of Wayve:

$1.26bn

Overview of Wayve:

Wayve is revolutionizing self-driving technology through embodied intelligence. The company is committed to making autonomous vehicles more adaptable and intelligent.

Key Developments:

  • Among the first to deploy autonomous vehicles using end-to-end deep learning.

  • Continues to test its technology in London, UK, and California, US.

Conclusion

Deep tech is revolutionizing industries by transforming scientific breakthroughs into real-world applications. However, its success hinges on strong collaboration between corporates and startups. While deep tech startups bring disruptive innovation, corporates provide critical resources such as funding, market access, and regulatory expertise. By fostering long-term partnerships, sharing infrastructure, and aligning strategic goals, both entities can bridge the gap between research and commercialization.

As investment and government support for deep tech continue to grow, businesses must embrace innovative collaboration models to drive meaningful progress. By building innovation-friendly ecosystems and overcoming commercialization challenges, corporates and startups can unlock deep tech’s full potential, shaping the future of technology and addressing some of the world's most pressing challenges.

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