Discover 5 Top Machine Learning Startups

Staying ahead of the technology curve means strengthening your competitive advantage. That is why we give you data-driven innovation insights into artificial intelligence. This time, you get to discover 5 hand-picked machine learning startups.

Out of 8 000+, the Global Startup Heat Map highlights 5 Top Machine Learning Startups

The insights of this data-driven analysis are derived from the Big Data & Artificial Intelligence (AI)-powered StartUs Insights Discovery Platform, covering 2 093 000+ startups & scaleups globally. The platform gives you an exhaustive overview of emerging technologies & relevant startups within a specific field in just a few clicks.

The Global Startup Heat Map below reveals the distribution of the 8 797 exemplary startups & scaleups we analyzed for this research. Further, it highlights 5 AI startups that we hand-picked based on criteria such as founding year, location, funding raised, and more. You get to explore the solutions of these 5 startups & scaleups in this report. For insights on the other 8 792 machine learning startups, get in touch.

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Savia facilitates Rehospitalization Minimization

Founding Year: 2018
Location: Palo Alto, US
Funding: USD 500 000
Industry: Healthcare
Partner for: Managing High-Risk Patients

US-based startup Savia provides a machine learning-based platform to minimize rehospitalizations. The startup’s predictive model analyzes patient-specific data points through patients’ electronic health records (EHR) to predict and prevent Skilled Nursing Facility (SNF) rehospitalizations. The system uses predictive analytics and risk modeling to manage high-risk patients. The mySAIVA dashboard aids medical professionals to prioritize activities and take timely interventions for patients at risk. The system increases efficiency and quality of care by providing clinicians with constantly updated patient charts to reduce rehospitalization-related costs.

Circly enables Operations Optimization

Founding Year: 2020
Location: St. Polten, Austria
Funding: USD 352 000
Industries: Retail, Manufacturing
Partner for: Self-Optimizing Manufacturing Solution

Austrian startup Circly provides AI-powered planning tools for the manufacturing and retail sectors. The solution uses machine learning to automate routine tasks from forecasting to planning. The startup offers an interactive tool to constantly provide feedback and upgrades, including different data sets for the user to select and rank individual dependencies, as well as independent cross-platform dashboards. The system optimizes order pooling, automates inventory balancing and availability, as well as increases delivery efficiency and inventory reliability with forecasting.

Synauta enabled ML-based Water Desalination

Founding Year: 2018
Location: Calgary, Canada
Funding: USD 1,06 M
Industry: Wastewater Management
Partner for: Improving Water Treatment & Management

Canadian startup Synauta optimizes water desalination for industries. The startup uses machine learning algorithms to provide operators with setpoints and optimal cleaning times. Synauta’s system also improves energy saving by integrating reverse osmosis set points in supervisory control and data acquisition (SCADA) systems. The startup’s solution optimizes the usage of chemicals in the desalination process by applying plant data. It recommends the most suitable date for cleaning membranes. This predictive maintenance mechanism reduces costs for chemical extraction. The system helps plant managers at industries treat the water used in the manufacturing process efficiently.

Glint Solar improves Solar Greenfield Selection

Founding Year:2020
Location: Oslo, Norway
Industry: Energy
Partner for: Floating Solar

Norwegian startup Glint Solar identifies and analyzes the best greenfield sites for floating solar fields. The startup’s Regional Scan solution uses satellite data and machine learning to monitor sites. The platform scans through large regions to identify water bodies. The Nearshore scan system allows planners to filter and select sites based on numerous layers such as water-body size, distance to the grid, installed capacity, and land use. The startup’s Site system further analyzes the parameters such as irradiation, wind, waves, temperature, water level fluctuations, water presence, far shading, precipitation, and high-level bathymetry. The startup meets the increasing demand for renewable solar energy plants by enabling optimal selection of the field location.

yieldsApp identifies Crop Infestation

Founding Year: 2019
Location: Hod HaSharon, Israel
Industry: Agriculture
Partner for: Real-time Pest Management

Israeli startup yieldsApp uses machine learning to identify pests and diseases in plants. The startup integrates real-time data with agronomy intelligence to provide farmers with concise, simple, and accurate recommendations. yieldsApp collects real-time data from satellite imagery, weather conditions, and sensors. The collected data is analyzed to predict pest occurrence and provide recommendations for use of pesticides. The application’s self-learning algorithm helps farmers identify pests and diseases and take corrective actions at the right time.

Discover more AI Startups

Startups such as the examples highlighted in this report focus on optimizing & improving various industries through machine learning algorithms. While all of these technologies play a major role in advancing Industry 4.0, they only represent the tip of the iceberg. To explore more AI-based technologies, simply get in touch to let us look into your areas of interest. For a more general overview, you can download one of our free Industry Innovation Reports to save your time and improve strategic decision-making.