After five years as Synthetaic, we’re re-introducing ourselves as RAIC Labs. The new name reflects our commitment to building on the innovation of our RAIC platform, and celebrates the spirit of scientific discovery that’s always been part of the company DNA.
As we enter this new chapter, let’s look back at our origins as Synthetaic and the rise of RAIC.
Our Origins as Synthetaic
The spark of an idea that became Synthetaic came to CEO and Founder Corey Jaskolski during his time as an Explorer and Fellow at National Geographic — the rare job that’s as cool as it sounds. Corey develops custom imaging tools and other technologies suited to harsh environments and conservation use cases. Deploying them with National Geographic took him to remarkable places: the deck of the Titanic, a helicopter over Mt. Everest, and caves where the remains of Mayan human sacrifices are buried, to name just a few.
One such invention was a 3D scanner, built specifically to create a digital twin of one of the world’s last remaining Sumatran Rhinos. The resulting model struck Corey as incredibly lifelike, and got him thinking about what “real” data even is, particularly as it related to one of his interests: artificial intelligence.
Historically, building AI has relied on a wealth of training data — massive quantities of human-labeled examples to “teach” a machine learning model. But not every use case will have that wealth of examples. If a 3D rendering of a Sumatran Rhino could stand in for the real thing for researchers, could synthetic, AI-generated data similarly fill in the gaps for data-scarce use cases?
From that question came Synthetaic, founded as a leading provider of synthetic data for training AI models.
From the beginning, the synthetic data methods we developed showed strong results. In 2021, with the team at Michigan Medicine, we built a model that could increase accuracy of brain tumor diagnosis from 68% to 96%.
Since then, synthetic data has become an increasingly popular solution for a variety of use cases, and a variety of companies are developing solutions based on the creation of synthetic data.
As we explored applications of our generative technology, we remained vigilant about the potential shortcomings of synthetic data, including bias and model degradation. We began to explore the notion that technologies associated with generative AI, like transformers and GANs, could be used to eliminate the data bottleneck altogether.
The result of that exploration was RAIC, a revolutionary platform for analyzing your image, video, and geospatial data.
The creation of RAIC was a turning point for the company — away from synthetic data, and toward finding the answers locked inside your data.
The Rise of RAIC
RAIC is the ultimate no-code tool for exploring all types of image datasets. Its unsupervised AI makes your massive, unlabeled data sets instantly searchable. RAIC makes it possible for anyone to build detection AI from a single example in minutes, representing a total paradigm shift in speed-to-insight.
We knew that RAIC was unlike any other AI technology out there, and to demonstrate its value, we’d have to open people’s imaginations as to what was possible and break through their cynicism toward the AI hype.
The perfect opportunity to prove RAIC’s one-of-a-kind capabilities came in the form of a Chinese spy balloon. Using commercially-available satellite data, we traced the balloon’s path all the way back to its point of origin near Hainan — all starting from a single hand-drawn sketch of what the balloon might look like in the data.
By finding an unknown unknown in terabytes of data in just minutes, RAIC had more than proven itself. With more remarkable discoveries, RAIC's notoriety continued to grow.
Today, RAIC is making impossible data analysis possible across industries including security, conservation, defense, and agriculture. It’s also trusted by scientists, researchers, and investigative journalists to rapidly mine hard-to-reach insights from visual data.
Our new chapter as RAIC Labs is just getting started — stay tuned for more discoveries.