As a business leader, you're likely under pressure to integrate AI and machine learning into your day-to-day operations. But where do these technologies create the most value, and how can they be applied in a meaningful way?
Listen to Gerhard Wieser, Chief Technology Officer at Polystar, as he discusses the industry's shift from admiring the potential of AI to focusing on a more important question: where is it most useful, and how can it deliver tangible value to customers and their businesses?
Watch the Customer Story Video“Machine learning allows us to shrink a highly complex problem into something manageable. It helps us isolate key parameters, refine predictions, and ensure our models truly reflect real-world processes.”
“Data, analytics, and artificial intelligence are central to our digital transformation. As we digitize and automate our operations, we extend our partnership with Polystar to run our IT and networks even more efficiently. We leverage real-time and vast amounts of data from all relevant sources to improve detection, resolution, and prevention of incidents, ultimately to further improve service quality for our customers.”
"Our direction is clear. By unifying key analytics systems onto a single platform, we are creating a strong foundation for insight-driven decision-making across both fixed and mobile networks. This approach allows us to support the specific needs of our operating companies while scaling advanced analytics and AI use cases in a structured and consistent way. Our collaboration with Polystar of Elisa Industriq reflects a shared focus on performance, operational excellence, and delivering better outcomes for our customers.”
Gridle's AI forecasts electricity prices, demand, and reserve market signals, then decides when each battery should charge, discharge, or bid. Built by energy market and critical infrastructure experts, it already optimizes more than 500 MWh of contracted capacity, including the world's largest sand battery in Pornainen, Finland.
CalcuQuote AI is designed specifically for EMS (electronics manufacturing services) and OEM (original equipment manufacturer) workflows: BOM (bill of materials) enrichment, sourcing, and procurement. It combines machine learning and optimization to solve real supply chain challenges with precision.
Boost your network performance with AI-driven anomaly detection. With this solution, telecom operations teams can automatically detect anomalies and accelerate root cause analysis (RCA) and issue resolution. With automated prioritization and clearer RCA paths, telco teams can focus on fixing issues, not finding them.
Built on Polystar's Kalix Analytics, these AI and ML models analyze historical and real-time data to forecast demand and capacity needs. You get proactive optimization, lower risk, and more efficient resource allocation across the network.
Use our ML-based geolocation to spot coverage issues. Our RAN (radio access network) monitoring solution visualizes radio performance data on Google Maps, offering a clear, geographic view. This enables users to analyze and resolve network coverage issues while pinpointing root causes.
AI and ML promise transformative benefits for telecom operators - from predictive maintenance to automated network optimization. But without data readiness, these initiatives stall. Fragmented data, inconsistent formats, and legacy systems create barriers to AI success.
What if your planners spent their day on decisions instead of chasing data? As an AI-powered virtual manager, LumiVM is designed to help manufacturers streamline operations, automate critical decisions, and improve efficiency throughout the supply chain.
Polystar applies artificial intelligence and machine learning to operational telco data, helping operators turn complexity into decisions they can act on.
Our AI-powered solutions enable faster decision-making, improved efficiency, and more proactive operations. From network capacity forecasting and anomaly detection to intelligent automation and advanced analytics, we help customers reduce costs, solve challenges faster, and unlock new opportunities for growth.
Purpose-built for EMS and OEM workflows, CalcuQuote AI helps manufacturers optimize sourcing, enrich BOM data, identify component alternatives, and reduce supply chain risk.
By combining machine learning with deep industry expertise, it enables faster, more informed decisions, lower costs, improved efficiency, and greater resilience in an increasingly complex supply chain environment.
Wind and solar make electricity cleaner and cheaper, but far less predictable. If you own a battery, that volatility is either a risk or an opportunity. Gridle helps you take the opportunity. Its AI forecasts spot prices, demand, and reserve market signals, then optimizes each asset individually across balancing and wholesale markets.
The results are practical. In Pornainen, Finland, Gridle optimizes the world's largest sand battery, which is expected to cut local heating emissions by about 70 percent while earning reserve market income. Utilities such as Vantaan Energia and developers such as AkkuX rely on the same approach for their grid-scale batteries.
High-tech manufacturers generate vast amounts of data across R&D, production, and quality processes. At camLine, we use AI and machine learning to transform this data into actionable insights, enabling teams to predict outcomes, identify root causes, and optimize performance faster.
From battery development and semiconductor manufacturing to complex production environments, AI-driven analytics support better decision-making, improve quality, and accelerate innovation throughout the product lifecycle.
Modern supply chain operations generate more data than teams can realistically process and act upon. At sedApta, we combine AI, machine learning, and natural language interaction to help organizations streamline operations, automate decision-making, and improve supply chain performance.
By transforming complex data into real-time insights and actionable recommendations, businesses can respond faster, optimize resources, and build more agile, resilient operations.
Learn more about how AI and ML create value across different industries.
Join leaders from Sanmina, Solutions Manufacturing, CalcuQuote and Banyan for a panel discussion on AI, supply chain risk and the future of EMS resilience.
Discover how Theion and camLine reduced battery R&D testing time from 42 days to 15 hours using AI-driven predictive models.
See how Gridle turns a 100 MWh thermal store into an active energy market participant, balancing heat demand, electricity costs, and reserve market income.
Explore how AI and automated root cause analysis boost yield, cut costs, and drive innovation in the evolving battery manufacturing industry.
Save up to 75% of time on compliance reporting. Watch the webinar with CalcuQuote and Banyan.eco to see how AI automates REACH, RoHS, and more in real time.
Watch the interview with our CPO, Thomas Nilsson, and discover how AI-driven network assurance enables proactive operations, automation, and better CX.
Discover why AI enhances, not replaces, developers, boosting productivity while relying on human creativity, direction, and technical expertise.