Stradigi AI, a North American Artificial Intelligence software company, is pleased to announce that its cloud-based Kepler Platform is now offered on the Microsoft Azure Marketplace and optimised to run within Azure. Kepler utilises Microsoft compute, database, security, and Storage services. The ability to instantly activate Kepler through the Microsoft Azure Marketplace gives business users a way to automate AI across all functions and departments. AI projects can go into production in a matter of days and weeks vs. months to directly impact time to value and ROI. Stradigi AI also announced it has earned co-sell ready status through Microsoft One Commercial Partner program as a Microsoft Gold Partner with a competency in data analytics.

Stradigi AI, a North American Artificial Intelligence software company, unveiled the new self-service version of its Machine Learning (ML) cloud SaaS platform, Kepler. Stradigi AI is enabling users with no previous ML and Deep Learning experience to reap the benefits of business-driving AI in hundreds of real-world applications. The Kepler platform provides end-to-end automation of complex data science processes with its new Automated Data Science Workflows. The automation features allow businesses to get AI projects to market on their own quickly, solving the most pressing use cases in the market today, including customer segmentation, churn prediction, demand forecasting, predictive maintenance, sentiment analysis, attribution modeling, workforce planning, pricing optimization, and more, across all business verticals. "[The Kepler platform] has been designed to enable non-coders without data science experience to get up and running quickly to make ML-driven predictions," said Krishna Roy, Senior Analyst, Data Science and Analytics at 451 Research.

Stradigi AI, a Montréal-based AI solutions provider and research lab founded in 2014, today announced that it has raised $53 million CAD ($40.3 million) in a series A round led by Canadian institutional funds Investissement Québec and Fonds de solidarité FTQ, with participation from Holdun Family Office, Segovia Capital, Cossette, and company cofounders Basil Bouraropoulos and Curtis Gavura. CEO Bouraropoulos said the influx of capital will accelerate Stradigi's North American expansion, which will include new offices in the U.S., with 50 new positions in research, software, sales, and marketing. Additionally, he says it will bolster development of the firm's freshly unveiled AI platform, Kepler, on the heels of a recently announced partnership with professional services network KPMG. "Investissement Québec and the Fonds de solidarité FTQ, in addition to all the other amazing investors that contributed to this financing, are great partners for Stradigi AI," said Bouraropoulos. "As two of the most respected institutional funds in Canada, with diverse portfolios and deep experience with preparing companies for international growth, IQ and the Fonds will bring tremendous value as we execute our strategy to become one of the top three leading platforms in North America." It's built on an adaptable environment that leverages a software-meets-service model, where guidance from Stradigi's research scientists is provided in tandem with solutions deployed via a secure service.

In a recent Cray-sponsored survey, over 70% of respondents say Artificial Intelligence will be critical to their business by 2022, but cite a "lack of skilled resources" as a major challenge. In order to address those resource constraints, Cray, a Hewlett Packard Enterprise company has partnered with Stradigi AI, a leading Artificial Intelligence solution provider, to provide the skilled resources organizations need to be successful with AI. We'll have AI experts from Cray and Stradigi AI on hand to explain our proven methodology for guiding AI implementations from pilot to production.

The world of AI can be full of a lot of unknowns. That's why we're committed to bringing our #PeopleofAI to the forefront. We want to illuminate what they do, how they stay on top of ever-evolving trends and research, and why this matters for smart, human business. This week, our data annotator, Emily, demystifies what goes into the data annotation process -- an integral piece in creating effective machine learning. Data annotation is the foundation upon which machine learning models are built.

This story originally appeared in the October 2019 issue of strategy. In recent years, every sector, from finance to QSR, has amassed and aggregated data from various sources to uncover themes around unmet consumer needs, says Meghan Nameth, managing director for customer marketing and product analytics at PwC. But identifying patterns within defined sets of structured data is "actually the easy part of AI," notes Anne-Marie Castonguay, who heads up data and insights at Lg2. Now, the next big thing is deciphering unstructured data, such as documents, audio, video, social chatter and product reviews, which are usually qualitative in nature and far more difficult to parse. Machine learning algorithms typically use structured data – clearly defined data types that can be easily categorized, stored and searched in a database – to function.

Yanping grew up in China, and moved to Canada to complete her PhD at the University of Sherbrooke in Machine Learning and Data Mining. While completing her studies, she had strong a strong interest in further researching Machine Learning, which led her to pursue becoming a professor in Natural Language Understanding (NLU) at Xiamen University. In 2015, she decided to move to the AI hub, also known as Montreal, to dive into the industry dimension of her specialization. With NLU being one of the key technologies of our platform, Kepler, we got down to the nitty gritty with Yanping, who gave us a behind-the-scenes look at what her life as an NLU research scientist is actually like. NLU allows computers to understand the structure and meaning of human language.

When Basil Bouraropoulos hired Carolina Bessega for a three-month internship, he didn't know that the new intern, who had just graduated from a CEGEP computer-programming course, was a former physics professor who would change the focus of his company and become one of its top executives. Bessega started her career in Venezuela. There, she earned a PhD studying the birth of stars before teaching at a university and heading a research lab. But as the political and economic situation in her home country deteriorated, she decided to immigrate to Montreal. She had read that one of the best ways to enter the local job market was to go through a college program that included an internship, she said, so she enrolled in a computer programming analyst course.