Fable has established itself as the market's go-to startup for helping companies build accessible digital products. Based in Toronto, this startup is now broadening its support to communities and working towards more inclusion in AI training data with the new funding of $25 million.

Fable started two years ago as an easy way to get access to the expertise and people with disabilities, so any builder of a product could have the best advice on making it as accessible as possible. It has since its A round two years ago been building out a more robust product, with content, testing, and tools that integrate more directly into developers' workflows.

"It's changing it from being the accessibility specialists or product managers' issue alone. It's moving to everyone in the product development process: researchers, designers, product managers, engineers," said Alwar Pillai, co-founder and CEO, in an interview with TechCrunch. "It's historically another group that's been responsible for it and doing the work. Now they're taking that shared accountability and responsibility, and Fable is a platform that's allowing them to do it by themselves."

It appears that companies with large platforms have learned the secret that you can't sprinkle accessibility at the very end like Salt Bae. It has to be baked in from the start — and making the product better for people with disabilities usually makes it better for everyone else, too.

Fable initially supported vision and motor disabilities to get a warm start, Pillai explained:
We wanted to come up with a way just to get companies comfortable engaging with this population because, historically, it has been excluded. And these are communities organizations are a bit more familiar with. Over the course of time, we have observed a couple of trends within our customer base that made it like this is the right time for us to expand our community to represent people with cognitive disabilities and with hearing disabilities.

One in six people has some form of disability, she noted, though not all are visible or even something a person may mention. There are lots of assumptions built into user experiences, about what a user can see, hear, do, and understand. Finding and improving them is not always easy if you don't have, say, a deaf person or someone with dyslexia on your testing team.
"If you get the insights from these communities you are going to, at the end make products that work well for everyone. But it has been historically challenging for enterprises to engage with this community easily, and on demand. And that's when Fable jumps in," she said.

So, fable has developed assessment tools as well as advisory ones so that the product managers and engineers can monitor accessibility like any other standard function and quality milestone over time.

Another area of tech that deserves special attention and which Fable is hoping to improve is the data powering AI models. Bias in data translates to bias in models, and that's true for people with disabilities as much as it is for any other category.

For one, such AI models tend to aim at the most aggressively average answer or response—dead center on the bell curve. However, people with disabilities tend to fall outside that average need or experience.
"We are excited and cautious about the proliferation of AI; there is a huge opportunity to make experiences better for people with disabilities," said Pillai. "At the same time, however, it has the capability to also amplify the digital divide that already exists.". We see that AI is getting baked into so many things, but because people with disabilities have not been taken into account there, and the data that you probably collect is smaller, so they get excluded from the large models; we feel they have the ability to exclude the experiences of people with disabilities because it deviates from the 'normal'.

That can be mitigated with fine-tuning or prompt engineering, but only so much; a model necessarily pulls from the datasets it's trained on, so if disabilities are not adequately represented in there — and they aren't — the models simply are not equipped for accessibility. Fable has been working with the community, as well as researchers and governments, to create resources and best practices.

Our aim is that, very soon, we will be able to introduce these inclusive datasets and offer testing for accessibility in AI. Our customers are already coming to us for it," Pillai said.
She emphasized once again that it is about empowerment to include these methods within a company's own development processes — Fable doesn't do the work for them. 

Our platform has now become this dashboard where you can monitor all your digital properties and products against these accessibility metrics. We invested in integrations, because we wanted the insights and data to live in the products that product teams are using on a daily basis, said Pillai. "We went from just able to get one piece of insight to really being able to observe your performance across products, and when you think about an enterprise, they have, like, 500-plus digital products. The goal for them is, how do I know if I'm getting better or not? And finally, they have metrics to prove it."

The $25 million B round, led by Five Elms Capital, will go toward standing up the new teams and products around cognitive and hearing impairments, and of course AI expertise as well. Pillai said they were pretty pleasantly surprised while they were raising- the investment climate isn't quite as open as it was a few years ago.

It was so different from the last few times we raised," Pillai recalled. "I remember when we raised our seed and Series A, it was very much, you know, trying to convince investors about the opportunity around the accessibility space. But this time around, investors had a very strong understanding of the space, the growth opportunity.". It was more about, you know, how much value are you adding to customers, and how are you growing? I think that really stood out.