About – Numeno

Personalization should be effortless, transparent, and rooted in human-centered design.

We are committed to making technology feel familiar and intuitive, ensuring that every digital experience resonates with the unique preferences and subjective needs of each user.

From Waverly to Numeno

Our journey started in 2020 with Waverly, the first AI-native social platform built around algorithmic transparency and control. Waverly.social lets users curate content, craft great posts, maintain control over their feed, and foster thriving communities.

Along the way, we built some deep AI tech that we’re now sharing with the world as Numeno. Our simple, transparent APIs help transform natural-language data into dynamic, tailored interactions that feel intuitive and human.

Our Team

We are venture scientists and creators. We have founded companies, led teams, and shipped many things that folks love, both in the enterprise space and at startup scale. We are bringing our passion and energy to the hybrid space of AI-backed, human-centered-software.

Philippe Beaudoin
LinkedIn »

Dave Burke
LinkedIn »

Press

Waverly is looking to combat challenges like distraction, misinformation, and disinformation by betting on its users. The company is attempting to do this in a number of ways: by offering content curated and driven by user intent; using NLU to understand user intent rather than tracking their every click and move; and ensuring that while people can choose to follow whatever content they want, they can’t flood other users’ Waves with that content.

Canada has long been the domain of business-to-business, software-as-a-service firms. But the world’s biggest tech companies make things for people, so the country needs more founders and funders pursuing consumer AI applications, says Beaudoin. In June 2020, he launched Waverly to build a social platform using “human-first” algorithms.

The good news, in any case, is that this technology aims to eliminate silly keyword interactions between human and machine. And, conversely, it promises that the machine will respond in a richer way than by picking and choosing content offered here and there.