Training responsible : Mikael Syväjärvi

In this training we learn about research to deeptech. Contact us to have this for your organization or project.

– Deep tech startups face unique challenges and require founders and investors to be prepared for a complex journey.

– AI and ML are crucial in deep tech companies for data analysis and advanced solutions.

– Deep tech startups work on scientifically complex technologies requiring specialized expertise.

– Development cycles can be long, leading to delayed market entry and financial challenges.

– Deep tech startups face higher risk of failure, making funding acquisition more difficult.

– Deep tech startups often operate in regulated industries, requiring compliance with complex regulations.

– Protecting valuable IP through patents is critical but challenging and expensive.

– Marketing approaches in deep tech differ, with a focus on research and development before product promotion.

– Balancing excitement and accurate communication is a challenge in deep tech startups.

– Deep tech startups involve extensive research, high risk, and uncertainty in the initial stages.

– Unlike typical tech startups, deep tech focuses on scientific feasibility rather than just business execution.

– Deep tech startups face a high risk of scientific failure.

– Funding after validation requires proving market fit, scalability, and potential returns on investment.

– Staying updated on advancements and emerging opportunities is crucial in the evolving deep tech field.