Company Website: https://www.seems.gr
Company Email: info@seems.gr
Employees: 12
Funding State: Bootstrapped
Industries
- Data Analytics - Big Data
Technology
- AI
- Cloud Computing
- Data Analytics - Big Data
- Diagnostic/Imaging
- Drones
- Hardware
- IoT
- Networks
- Sensors
- Software
- Web or Mobile Application
Business Model
- B2B
Revenue Model
- Licencing
- Other
- SaaS
Funding Sources
- Grant
- Loan
- Other
- Self
About
SEEMS P.C. is a high-tech startup company, focusing on the development of Digital Transformation solutions, employing the most advanced technologies. The company was established in February 2017 and has offices in Alexandroupolis and Thessaloniki. Investing to Knowledge and Innovation, through applied Research, SEEMS vision is to become the expert partner to support Industry in its effort to adopt and exploit the Digital Era means, within the spirit of Industry 4.0 revolution.
Solution & Product
SEEMS has developed aRTi-DTM, an integrated Industrial Internet of Things (IIoT) solution (HW & SW) supported by Artificial Intelligence and Edge computing technologies to monitor, control, predict and optimize productions’ performance in real-time. In more detail, aRTi-DTM collects real-time data from the production site, converts it into useful information, which results into trends, predictions, and recommendations. At the same time, with the use of AI, the root-cause of known and unknown problems is identified. At a final level, aRTi-DTM AI algorithms combine and analyse the already processed information more in depth to provide suggestions for improvement in real-time. In this way decisions are based on real-time qualitative data of the entire production and not on siloed data per machine.
Innovation & Scalability
The key benefit that differentiates aRTi-D TM is that it is a single and simple solution that enables manufacturers to use real-time AI recommendations to optimize their production performance with low investment, support and scalability cost. Unlike current solutions, aRTi-DTM can deliver any IIoT application due to its modular architecture, developed 100% in house, along with its ability to connect to existing systems that guarantees simplicity in use, flexibility in support and ease to expand. With real-time AI recommendations for improvement, aRTi-DTM can lead to reduced waste, machine downtime, energy consumption per product and consequently operating costs increasing thus productivity. In other words, with aRTi-DTM a manufacturing unit can produce more products with less costs.
Traction & achievements
aRTi-DTM clients come from the pharmaceutical, food and beverages, chemicals, pulp & paper, power generation and solar water heating industry. Based on its use case of "Automated recipe management and production analytics for the Production Line Digitization, Automation and Optimization using technologies of the Industrial Internet of Things and Artificial Intelligence", SEEMS received 3 awards (1 Gold in the Asset Management category, 1 Gold in the Production category and 1 silver in the Healthcare/Pharmaceutical category) at the IoT awards 2022.
Team & Why Us
The team is based on complementary skills in business, technical and administrative level but also in personal and scientific relations, which have developed between us in research and commercial projects the last 10 years, through which mutual trust and effective contact. All team members have distinct roles and clear goals, which they are committed to achieving by adopting a common and carefully design approach. All members have a high level of technical and scientific training and experience in: •IIoT applications development, •AI Software development, •Hardware design & prototyping, •Sensing Art and Data Science, •managing projects of high complexity and high budget, •the manufacturing industry and its needs.
Funding Needs
SEEMS is a bootstrapped company. The company did not seek to raise any capital from external investors so far.
Digital Transformation solutions in Industry powered by Artificial Intelligence & Internet of Things