Making AI more accessible

Data tooling start-up Instill AI switches up access to AI as it raises $3.6m in a seed round, led by RTP Global.

The seed round will help the company accelerate its journey to help companies of all sizes extract untapped value from unstructured data.

While advancements in deep learning have helped us better understand unstructured data in recent years, data tooling hasn’t kept pace. The implementation and deployment of an effective AI solution in an organization’s data stack also remains extremely costly and complex. 

Why? Because building in-house AI solutions requires huge investment and relies on multifunctional teams.

An enterprise sized problem

As a result, only large enterprises with large amounts of resources can successfully build exclusive functionalities and components to process their unstructured data, enabling them to extract business insights or deliver AI applications.

The other problem is that while emerging MLOps tools and AI services make tapping the value of unstructured data possible, they provide different proprietary frameworks. This causes further difficulties for AI practitioners as they piece them together to build a custom end-to-end solution and integrate with the existing stack. The result? Team silos and inefficiencies. 

These are problems and pains that Instill AI’s co-founders Ping-Lin Chang and Xiaofei Du experienced first-hand in previous companies. And they’re on a mission to do something about it. 

“Unstructured data can be more analyzable, if AI is more accessible,” said Ping-Lin Chang, CEO and Co-founder of Instill AI. “We believe that machine learning and AI should be as easy to access as other off-the-shelf cloud services.” 

A low/no code approach

To achieve this, Instill AI has introduced its open-source project — Versatile Data Pipeline (VDP) – to seamlessly bring AI into the modern data stack. With a low/no code approach, modern data and AI teams can streamline the process of distilling the value of unstructured data, converting unstructured data into meaningful data representations. 

As well as impressing RTP partner Gareth Jefferies with the product, Instill AI has gained significant praise from the community too. VDP achieved 600 stars on GitHub in just five months.

The founders don’t plan to stop there. With the seed investment, Ping-Lin and Xiaofei plan to accelerate the development and strengthen the readiness of the VDP. This will bring them one step closer to making the solution to this “unstructured data problem” a reality.