January 25, 2021

Tech startup applies artificial intelligence to industry to improve efficiency and reduce environmental impact

The NTWIST team

Edmonton-based company NTWIST is applying artificial intelligence to help industrial companies reduce costs and environmental impact, and maximize profit.

The tech startup has developed a platform that harnesses the predictive power of machine learning, a form of artificial intelligence (AI). NTWIST says industrial plants can use the platform to optimize their processes. NTWIST’s software platform implements artificial intelligence algorithms in a user-friendly package that “communicates” with existing equipment in an industrial facility and existing control room software.

Achieving operational excellence in a processing facility is crucial as the world transitions to a high-production, low-waste environment, notes Chowdary Meenavilli, NTWIST co-founder. The AI platform uses existing sensor data to generate process recommendations and forecast production in real time, with less effort and better outcomes, Meenavilli says.

“Even with a conservative assumption that we can make a two per cent improvement in efficiency in our target industries, we can enable $1.75 billion a year savings in Alberta alone. Right now, this is money left on the table and the waste either ends up as tailings or energy waste,” Meenavilli says.

Alberta Innovates provided $200,000 through its Digital Innovation in Clean Energy (DICE) program to accelerate development of NTWIST’s artificial intelligence platform.

The DICE program provides funding to assist startups that align with Alberta Innovates’ strategy of supporting data-enabled innovation and using digital technologies for business transformation in Alberta’s traditional sectors. Ultimately, driving the use of an emerging technology like artificial intelligence helps to position Alberta as a global leader in applied AI and at the forefront of the AI transition.

The benefits of NTWIST’s solutions are twofold, says NTWIST research engineer Nirav Raiyani. On the economic side, “it provides businesses with a platform to make critical decisions by utilizing the existing operational data, ultimately reducing the costs and increasing profitability,” Raiyani says. On the environmental side, “the final outcome of our solution is to improve productivity with minimal resources, leading to the conservation of natural resources (i.e., energy, raw materials) and reduced environmental footprints.”

Industrial facilities ideal candidates for artificial intelligence

Industrial facilities are ideal candidates for AI integration, NTWIST says. These facilities already collect huge amounts of data; the systems they are trying to control have a level of complexity beyond what traditional technologies can handle; and there is a huge economic value in making operations more efficient. This combination of data, complexity and economic value is the sweet spot for artificial intelligence.

The project Alberta Innovates is helping to fund is one of NTWIST’s current core projects. The solution being implemented with the DICE program’s help will be NTWIST’s flagship product in the mining industry once the project is completed.

The product will enable customers to quickly identify the best ways to improve their energy efficiency. In most cases, this will result in greenhouse gas emission reductions that directly benefit the bottom line.

“The clean-tech side of our company is something the team is really passionate about. We have pulled almost everyone on the team onto this project in one way or another and it has been a real rallying point for everyone,” says Grayson Ingram, Product Manager, Industrial Automation, at NTWIST.

“Once we are successful in the mining space, this opens up the opportunity to implement the solution in other sectors – for example, oil and gas, pulp and paper,” Ingram says.

Since the approval of the DICE funding, NTWIST has expanded its team by four full-time and six part-time employees.

“A key aspect of our vision of the future is the collaboration between humans and AI. We take a human-centric approach to solving problems. We aren’t trying to make AI smarter than humans; we’re trying to use it to make humans smarter,” Ingram says.