Artificial intelligence and sensor-tech firm founded in 2019, based in Switzerland.
Backed by NobleProg Group.
aikemy enables you to see what’s in your food, medicines, and cosmetics with intelligent sensing tech.
Our app for consumers:
- instantly detects food and medicine safety hazards
- assists you in the selection of best quality products
- tracks individual nutrition
aikemy platform for business:
- saves up to 99% of the time spent on lab testing and saves costs
- introduces continuous quality control with flexible integration into your manufacturing steams
- enables instant decision making, tracking, monitoring and optimizing efficiency exactly where you need it
Your Pocket Lab: Revolutionary, AI-enabled Technology at a Low Cost
aikemy introduces the pocket lab – AI-enabled consumer sensor technology that brings full-scale laboratories into your pocket. A simple scan using the device supplied by AMS and the pocket lab can tell what it is, the composition, detect potential safety hazards, or confirm authenticity. The answer to your question pops up on your mobile phone.
- Consumer type, extremely affordable
- AI in place to achieve maximum accuracy
- Non-destructive & real-time measurements
- Pocket-size: 4 x 4 cm
CEO & Founder
Agata is an engineer and entrepreneur. She has expertise in business innovation, R&D to quality areas gained by working for the top medical technology players, incl. Danaher Co. and Siemens Healthineers. Agata holds degrees in both Biomedical Engineering and Materials Science as well as education in business from the University of St. Gallen. She is based in Zurich, Switzerland.
Business Development in China
Bernard has expertise in worldwide business development as a Founder and CEO. He is also a CTO adept at cloud computing, big data to artificial intelligence, specialized in the service sector, including IT projects for Big Pharma. Bernard is based in London, UK and Zhuhai, Guangdong, China.
Founder & CTO
Zofia holds a Ph.D. in Computer Science and M.Sc. in Mathematics. She was a researcher at leading Universities incl. Geneva and Zurich, as well as NGOs, incl. The World Bank, with expertise in statistics, artificial intelligence, and big data. Zofia led preventive medicine projects. She is based in Zurich, Switzerland.
Build Trust. Fight the Fakes.
aikemy provides patients with a convenient way of ensuring their medicines are genuine.
According to WHO, even 1 in 10 medicines is falsified. Counterfeit products often look identical to their authentic versions, but contain too little or too much of the active ingredient, or are made with toxic substances. Patients who receive the falsified medicines believe that they on therapy, but this is not true. Even worse, they are at risk of severe illness or death. Counterfeiting is illegal, but difficult to recognize, particularly for patients. The spread of the problem is the largest in online pharmacies.
We have been successfully able to detect falsified drugs by testing medicines using the pocket lab. Learn more about the significant results of our True Blue project.
True Blue Project Success
Learn more about our experience of detecting falsified medicines using the pocket lab with a backed-by-data 100% success rate of correct answers in a peer-reviewed publication.
The miniaturized Near-Infrared Spectroscopy (NIRS) enables convenient, non-destructive, and real-time testing of medicines circulating on the field or throughout the supply chain. We have successfully been able to detect falsified Viagra using a new low-cost, consumer-type NIRS. In like manner, we have distinguished the original Viagra from its generic versions with the same dose. This innovation is a promising way of ensuring medicines authenticity by looking at their chemical ‘fingerprints’. Portable screening technologies for medicine quality assurance on the field or throughout the supply chain are currently growing and complementing the current approach for combating the falsified products, i.e., safety features on the packaging and laboratory analysis of suspect samples. In total, 78 spectra of Sildenafil-based tablets were recorded and classified using the K-Nearest Neighbors algorithm that relies on the Euclidean distances between measured values. The accuracy of our model was assessed using cross-validation and bootstrapping techniques. As a result, the miniaturized NIRS correctly ordered all tablets according to their manufacturer and indicated the falsified tablets. The spectra differed in shape from the authentic versions and show the high spread in chemo-physical characteristics, which suggest poor manufacturing practices of the falsified products.