5 universities, 11 ambitious science-based university teams, 7 VC firms, numerous experts, entrepreneurs and angel investors, 22h of mentoring and 3 workshops – the first Science Base Camp proved to be an incredible ecosystem effort across Nordics and Baltics.
Superangel joined forces with Aalto Startup Centre, University of Tartu, TalTech, Riga Technical University and University of Latvia to build a bridge between investors and future technologies, and help accelerate the commercialisation of science-based products. This is the first event of many, and we are looking to include more universities and VC partners to the initiative.
Here are the 11 forward-looking and innovative deeptech university teams from Science Base Camp you need to keep an eye on.
AIFORE – Aalto University & University of Helsinki, Team lead: Philipp Back
AIFORE is developing a scalable AI optimization tool for more sustainable and profitable forest management.
Currently, forest management is largely based on old and inflexible best-practice guidelines. Preliminary results show that AI optimization can increase the net present value (NPV) of forest assets by up to 20%, and the mean annual revenues by up to 14%. For large B2B clients, this translates into €5 – €15 million in additional timber sales revenues – per year. AIFORE also incorporates risk factors (e.g. forest forest, storms, insect, price fluctuations) to reduce the risk of forest investments by up to 20%. Lastly, AIFORE combats climate change by helping forest owners to find the best strategies for reducing CO2 emissions and preserving biodiversity.
The team has just received over 700k€ to explore the commercialization potential of their forestry research.
Cellboxlabs – University of Latvia, Team lead: Gatis Mozolevskis
Cellboxlabs is developing miniature human organ replicas called organs on chips to help pharmaceutical companies perform preclinical tests in human-like organs.
Drug development is expensive (1.54 bn) and currently ineffective (~10%). The key issue for gut related drugs is that there are no representative human microbiome research and test models at the preclinical research stage, which then leads to expensive failures in clinical trials. Organs on chip are microfluidic devices that in essence allow human cell culturing in small channels similar to human organ channel systems, therefore creating a more accurate test model of different organs for pharmaceutical companies and academic institutions alike.
They are preparing to raise a pre-seed round in 2021. They are aiming for 700k€ funding that would help drive early sales to research institutes and validate the product for entering the pharmaceutical market.
Drug Hunter Analyzer – TalTech, Team lead: Jekaterina Mazina-Šinkar
Drug Hunter Analyzer is a portable drug analyzer for onsite drug abuse determination in oral fluid.
Drug Hunter combines two powerful techniques in one box, namely capillary electrophoresis (CE) and deep UV fluorescence detection for illegal drug abuse determination in oral fluid. The only available roadside saliva drug tests based on immunoassay have high error rates and identify only illegal drug class, not drug itself or its quantity. Drug Hunter identifies and quantifies each illegal drug separately even in the multidrug abuse cases, providing reliable and accurate determination of recent drug use in minutes for onsite non-expert use.
They are looking to include funding in cooperation with larger public funds for commercialisation and large scale development projects.
EyeVi Technologies – TalTech, Team lead: Gaspar Anton
Enabling digitization data streams through the AI powered platform
3D data is becoming the next foundation layer in all geospatial content required applications. With their unique approach they are able to train their AI faster than any other competitor. EyeVi mission is to control daily updated 3D geospatial data streams for infrastructure digitization, automotive and digital twin sectors.To achieve that they’re offering a software and hardware solution for B2B clients that enables data capture and data production with their machine learning algorithms at market disrupting ROI and OPEX. Machine learning algorithms trained to generate specific features of road infrastructure using any input data (UAV, MMS, other sensors).
In 8 months, they have expanded to 5 markets. Now they’re raising a 1.2M€ pre-A round that adds to numerous public grants they have received so far.
HYMET – Team lead: Nikolas Trutiak
HyMet designs advanced thermal interface materials which are also powerful heat spreaders. This new class of material will make the next generation of electronics smaller, less power hungry, longer lasting and higher performing. HyMet materials have been benchmarked to reduce power consumption of electronics by more than 30% compared to stock materials and has been conducting 3rd party testing since Q3 2020.
Their materials have reached TRL5 and they are still accepting requests for proof of concept/pilot studies beginning in Q2 2021. With these results and market proven, HyMet anticipates being open for Seed Round investment in Q4 2021. To participate in a study or to request samples, visit their homepage.
HOKEMA – Aalto University, Team lead: Anna Smolander
A novel speech recognition that is able to give personal feedback for the speaker.
Hokema’s speech recognition is the first in the market using a solution that is able to recognise the exact mistakes speakers make in pronunciation. Therefore their speech recognition is more detailed and accurate than any else. While other speech recognizers quess what was said, Hokema’s solution knows it – at a very detailed level. And top of that it is able to give feedback for the speaker.
In addition to significant grants and Business Finland support, they’re looking to raise 200k€.
“Science Base Camp is the best start up event for University spin-off companies to attend: the organisers have an excellent understanding of tech commercialization and open innovation concept.” – Hokema
LASO-LIBS – Aalto University, Team lead: Antti Kotanen
Augmenting geologists with a superpower: Laser vision
LASO-LIBS stands for Large Area Scanning Operation Laser-Induced Breakdown Spectroscopy. It’s like traditional scanning LIBS but 1000 times faster. Analysis is based on machine learning models and neural networks. By scanning drill cores it can classify, identify and quantify elemental and mineral composition. This can result in 9% cost savings in an ore exploration project.
They’re looking to raise up to 320k€ to add to the grant funding they have already received.
NYMO – University of Tartu & TalTech, Team lead: Heigo Põld
An autonomous robot ship
The multi-purpose autonomous robotic vessel is able to perceive the surrounding environment and navigate the given mission points without external interference. The robot ship recognizes various objects at sea and is able to make the necessary decisions. This developed robotic ship is both an innovative product and a service delivery platform that can perform different tasks as well parcel and cargo transportation services.
They’re looking to raise 3,5M€ in addition to the grant funding received so far.
Parkzia – Aalto University, Team lead: Prasad Jayathurathnage
Disruptive solution for trouble-free contactless charging for autonomous E-vehicles and robots.
The team has created a unique technology to enable very high-efficient wireless charging solution with full positioning freedom. The patent pending technology has been proven using a proof-of-concept prototype. Machine learning assisted algorithms are implemented to control the charging and enabling safety.
They’re looking to raise around 1M€ in addition to significant grant funding.
“We really got important feedback how to improve our investor readiness. Now we have a clear plan for next 8 weeks.” – Parkzia
PlantInvent – University of Tartu, Team lead: Hannes Kollist
Providing whole plant gas exchange analysis
Today, most gas-exchange measurements are carried out in single leaves and guard cell signaling is often measured in epidermal peels. PlantInvent aims to bridge the gap to a more comprehensive understanding of plant physiology by providing whole plant gas exchange analysis. They do so by using their custom-built gas exchange devices for Arabidopsis thaliana as well as for other species.
They are looking for funding worth 300k€.
TWinTech – TalTech, Team lead: Vladimir Kuts, Ph.D.
Universal SaaS software for simulation, programming, and real-time control of manufacturing units and robotic systems.
Their solution is able to control and simulate any aspect of the production line without limitation by brand or type of the machine, as well as being managed and self-learning independently by the exploitation of Machine Learning algorithms. The toolkit is being developed by using a game engine (Unity3D) enabled with machine learning, virtual/augmented reality, and various telemetry/interface technological solutions (ROS, MQTT).
They’re looking to raise 220k€.
Curious to know what was discussed at the event? You can find out – the workshops of Science Base Camp can be rewatched.
What are investors expecting from science-based teams
How to build a list of 100 key people
Action plan on increasing investment readiness
Interviews with VCs at the event
That was a blast! See you at the next Science Base Camp!
