We began our careers as academics and researchers, focusing for over two decades on unstructured data, text mining, natural language processing, and machine learning. At the University of Toronto, we had the opportunity to contribute to advancements in the field through publications and patents.

We founded Sysomos in 2008 as a spin-off from a university research project, leveraging state-of-the-art natural language processing and machine learning technology. We raised venture capital and grew the company 32x over the next five years. Sysomos powered social media analytics for numerous Fortune 500 customers, including McDonald's, Coca-Cola, Google, Nike, Apple, and Intel.

After Sysomos was acquired, we set out to bring behavioral intelligence to the built world by founding Aislelabs. There, we engineered machine learning algorithms to process billions of new data points daily, serving clients such as Simon Properties, Cadillac Fairview, The Dubai Mall, London Gatwick Airport, the Dallas Mavericks, and IKEA.

Over time, machine learning has continued to evolve, and today, Artificial Intelligence (AI) and Large Language Models (LLMs) are more powerful than ever. These advancements can serve as the foundation for technologies that drive productivity across various industries. However, true gains won’t come merely from adopting tools like ChatGPT or Copilot. Instead, specialized platforms are needed—platforms designed to harness corporate data and enable complex workflow automation with a high degree of accuracy.

The trillion-dollar AEC industry sits on vast amounts of underutilized data. This data is often messy, unorganized, and inconsistent—a goldmine waiting to be unlocked. But to operationalize this data, it must first be made AI-ready, and this transformation should be driven by AI itself, not manual human effort.

The AEC industry has unique yet well-defined workflows. These workflows are intricate and require AI algorithms that generic, off-the-shelf models cannot provide. For example, beyond being 100% accurate and relevant, the AI must not overlook any detail; it must be exhaustive.

With the research and development efforts underway at Workorb, we believe it’s the right time to tackle the AEC industry's challenges. Historically, this sector has been slow to adopt digital technology, mainly due to the lack of solutions that can handle its complex workflows with minimal tolerance for error or omission. Workorb is directly addressing this with a platform that cleans the data and prepares it for AI-powered solutions.

At the heart of Workorb is a team of passionate experts with deep roots in academic research, applied machine learning, and decades of experience building scalable systems and successful companies. We’ve dedicated our careers to solving real-world problems, and now we’re united around a shared vision: unlocking the full potential of corporate data to drive efficiency, growth, and innovation.

This summer’s venture funding is a key milestone that accelerates our mission - bringing total capital to $2.6M.  Our partners—Metavallon VC and Freedom of Innovation Ventures (by Sang Kyun Cha, founder of SAP Hana), contribute both funding and expertise, helping fuel our growth story.

We’re incredibly excited about the road ahead. We want to take this opportunity to thank the firms that have trusted us, collaborated with us, and shared invaluable insights into their industries. Together, we’re building software that makes a real impact.

The coming year will be pivotal for Workorb. Our focus will be on expanding business development efforts, educating the market about AI's transformative potential, and continuing to refine our product to meet the evolving needs of the AEC industry.

This is just the beginning, and we can’t wait to see what we’ll achieve together. Thank you for being part of our journey.

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Nick & Nilesh,
Co-founders, Workorb