Cognoa has gained regulatory recognition for its machine learning software as a class II diagnostic medical device for autism — meaning the digital health startup is now positioned to submit an application for full FDA clearance.

It’s a first but important regulatory step for a business that was founded back in 2014, and plays in a still nascent digital health space where untested ‘wellness’ apps are far more plentiful than medical technologies with robust data to prove out the efficacy of their interventions.

Discussions with the FDA started in early 2017, says Cognoa CEO Brent Vaughan, adding that it’s hoping to gain full FDA clearance this year.

He says the ultimate goal for the US startup is to become a standard part of domestic health insurance-covered medical provision — and for that FDA clearance is essential to opening the doors.

We first covered the Cognoa at launch in 2014 and the following year when it was still being careful to describe its technology as a screening rather than a diagnostic system.

It’s since gathered enough data to be confident in using the ‘D’ word — having run a pilot with 250,000 parents, offering free screening for their children so it could gather more data to refine its machine learning models.

“We were lucky that we had investors,” says Vaughan. “There’s not a huge business model in providing free screening services to kids, right, because we were certainly never going to sell ads. That wasn’t the goal.

“It took a little patience but in the process of providing free screening and at least showing parents how to navigate their way to the front of a line as more of an information service we were able to build the data models to support a development of a diagnostic device actually a couple of years sooner than we originally thought we would. So it ultimately paid off for us.”

Cognoa has raised $20.4M to date. Its main investor is the Chinese private investment group Morningside. Vaughan tells TechCrunch it’ll likely be looking to raise another round by the end of this year.

It has also conducted multiple studies over the last 2.5 years across the US, including blinded control trials and side-by-side comparisons of its different versions — working with children’s hospitals and secondary care centers. It now bills its technology as a “pediatric behavioral health diagnostics and digital therapeutics platform”.

The initial machine learning model, which was targeted at screening for autism, was based on the work of Stanford pediatrics and psychiatry professor Dennis Wall. The model itself was built by combining and structuring existing datasets of behavioral observations on about 10,000 children.

Though, as noted above, Cognoa has continued to refine its autism model with structured contributions from parents participating in the pilot and inputting data via its app. (Aka: If an AI service is free, you’re the training data.