AEGIS selects expert.ai to boost its data strategy
AEGIS has chosen the expert.ai natural language platform to implement a risk engineering solution that will extract and analyse critical information from risk engineering reports during the property underwriting process.
By applying the power of AI to this information-intensive process, AEGIS engineering teams will collect data more efficiently and comprehensively, enabling them to provide deeper insights to both underwriters and policyholders regarding key risk exposures and mitigation strategies.
“Artificial intelligence will continue to play a crucial role within AEGIS’s digital transformation program which aims to maximize our efficiency and increase our data analytics capabilities,” said Scott Schenker, SVP and Chief Information Officer at AEGIS.
“We’ve selected expert.ai for its ability toread, organise and extract relevant data so our team can be more efficient both in terms of managing repetitive tasks as well as better serving our policyholders.”
Tim Heinze, SVP and Chief Loss Control Officer at AEGIS, said in the course of evaluating and selecting an AI platform, expert.ai outperformed all of its evaluation criteria in terms of ensuring speed and efficiency.
It also delivered high-quality information needed to properly assess the risks of its policyholders and provide domain expertise based on the data collected.
By automating the reading and extraction of relevant data from natural language texts, expert.ai offers a range of AI services to reduce risk, improve risk selection and pricing, and augment capacity for insurance carriers and brokers.
"We help insurers understand and extract the data they need from loss control and property reports, policies, renewals and submissions, at scale and more than four times faster than their standard," said Michael Watt, Vice President of Insurance at expert.ai.
"All of this is performed with maximum accuracy, ensured by expert.ai’s unique approach to mixing language understanding, a robust knowledge graph and machine learning."
Accelerating solar transition with robotics and automation
Professor Tadhg O’Donovan, Head of the School of Engineering and Physical Sciences at Heriot-Watt University Dubai, shares his views on how robotics and automation can deliver a real impact in leading the Middle East’s transition to solar energy and in advancing the overall sustainability agenda
As the world grapples with diminishing supplies of oil and the need to reduce carbon emissions, the adoption of disruptive technologies such as robotics and automation can be an important catalyst for the proliferation of renewable energy. Current applications and research show that robotics and automation help simplify the processes involved in support of renewable energy generation, especially for solar energy sources, which results in increased productivity, and cost savings.
Solar panel placement
Robots and automation can help unload and place solar panels onto racks at huge utility-scale sites. Thanks to outdoor, autonomous robotic technology, the process for solar field assembly can be made more efficient. Moreover, due to the fragile nature of solar cells and wafers, high-speed impact robots are more suitable and gentler than manual handling which helps ensure higher throughputs with better yield. Robots support solar construction crews, not replace them which means utility-scale contractors are able to reduce large amounts of repetitive tasks and improve productivity, bolster worker safety, and produce more MegaWatt-hours, faster.
Solar panel cleaning and maintenance
Crucial tasks such as removing dust from solar cells can be automated with the help of self-cleaning robots which is otherwise risky for people. Dust removal is critical in high dust-density regions such as the Middle East to maximise the irradiance incident on the panel and to ensure the solar panels provide maximum power output and energy yield. Water-free autonomous cleaning system can save billions of litres of water over the lifetime of a plant situated in arid regions.
Manufacturing of solar power systems
Robots in the PV manufacturing process make a significant contribution due to their ability to reduce costs considerably and enhancing precision and accuracy when compared with human intervention. Manufacturers can deploy robots and automation to make smarter and swifter production decisions, which ultimately increase precision, reduces the cost of production, and improves productivity. Silicon ingot, silicon modules, solar cells, and silicon wafers are some examples of delicate components that can be produced with high precision through robotic automation.
Integrating robotics into the renewable energy industry comes with a few of challenges too. One of the largest challenges being the power grid itself which is primarily designed to transport energy from large, centralized power plants fuelled by non-renewable sources such as natural gas and oil. Hence, the current power grid requires an overhaul before solar and other forms of distributed renewable energy can be truly integrated as a viable source of power.
Fresh power grid designs
Propelling the energy industry into the future requires fresh approaches to the power grid design. The answer lies with smart power grids that can integrate various renewable energy sources and help utility companies achieve greater efficiency and sustainability.
An increase in the integration of robotics and automation in the renewable energy industry could lead to an eventual total shift from other sources of energies such as oil to greener alternatives such as solar. Finally, this will spur the creation of “jobs of the future” – especially in high-growth data, digital and robotics engineering.