Collaborative Data Ecosystems in Battery Manufacturing

zoom into some battery mechanics

Deliver new batteries and materials with collaborative artificial intelligence and data science to drive a sustainable future

Until today, materials and chemicals datasets tend to be small and sparse. Combined access to data in higher volumes and with high quality can quickly lead to more accurate results and higher ROI of AI projects.

Gain a competitive advantage
through innovation in AI

Companies that share complementary data with partners are better equipped to compete against disruptors

Accelerate time-to-market and streamline compliance processes

Start immediately to collaborate with partners of your value chain and deliver business outcomes

Find new and resource-efficient ways to recycle with partners

Create a circular supply chain to cover the demand for the incoming wave of electric vehicles

"Automotive OEMs are usually rather hesitant when it comes to sharing sensitive battery data. Understandably, because they rely on the trust of their customers with regard to the handling of data. Our partners also worried that they will lose their competitive advantage, but with Apheris, we were quickly able to convince them and are now collaborating on designing more efficient cell and battery materials."

Head of R&D, Battery Cell Manufacturer

E-BOOK Collaborate in
Battery Manufacturing

With an exponentially growing demand for rechargeable batteries, the development of new ultra-performant, fully scalable, and sustainable battery technologies and materials must be accelerated. Multiple partners of the battery value chain can now collaborate and develop powerful AI models for the discovery and development of next-generation batteries.

girl reading on a pile of large books

What this E-Book covers:

The data collaboration journey...

  • ...of a chemical R&D company who needs access to chemical compound data from an EV R&D department.
  • ...of a battery manufacturer that wants to leverage predictive AI models for material optimization and discovery.
  • ...of a cell manufacturer that reduced risk and protected his algorithmic IP while collaborating with his partners.