What is the Metafold API?

The Metafold API is a versatile collection of software components that can be combined in various ways to create a wide range of 3D functionalities. It is built on a high-performance, cloud native implicit geometry kernel and leverages our patented low-latency streaming technology. The Metafold API supports all types of devices, from performance workstations to mobile devices, while also handling user authentication, file storage, job scheduling and more. Additionally, the Metafold API offers SDKs for both Python and JavaScript for fast iteration as well as a client-side graphics engine, purpose built for high-performance volumetric rendering and interaction.

What problems does it solve?

• Example 1: You have developed a novel design for a prosthetic device. Although the design remains constant, there are various components that need to be sized on a per-patient basis. Your product is becoming popular and orders are piling up. What do you do?
• Current approach: The most common solution here is to simply hire more CAD specialists to make the necessary design changes as needed. This can work for a while but at some point it becomes expensive to keep hiring and training skilled individuals. Meanwhile the orders keep coming in and adding to the backlog. There is also evidence to suggest that skilled technicians are becoming harder to find (by about 10% per year).
• The alternative: transform your Grasshopper (or Solidworks or whatever) workflow into a robust web or mobile app. Expose only the parameters that users actually want to change in a clean modern user interface. Connect the output of the app with your order management systems or use the Metafold job system to do that for you.
• Expected outcomes:
• Up to 100x faster workflows per part.
• Ensure manufacturing compliance by only allowing viable designs to be output from the app or workflow.
• Increase engagement with your customer or organisation by simply sharing a website instead of an awkward desktop application (or worse, a GH definition).
• Example 2: You have been tasked with developing new midsole designs that exhibit high-performance mechanical properties (i.e. excellent energy return), while also being compatible with a certain manufacturing methodology (i.e injection molding). What do you do?
• Current approaches: There are many ways to approach this problem but the most common one that we have seen has two modes of failure. Firstly, like the first example, there is a strong tendency to stick with the tools that are already being used but just work harder (or longer). Often a single design iteration can take days or weeks, depending on how much simulation is involved, putting enormous pressure on the product release cycle.
• Secondly, in an attempt to create automated workflows, teams, especially engineering teams, will look to build a software solution in-house. The problem is that software development for 3D geometry is extremely difficult and time-consuming. The team now has two problems: creating the software and making it work AND getting the product out the door.
• The alternative: Our geometry kernel is industrial strength and battle-tested. We have python and javscript SDKs that you can pull into your existing toolchain (i.e. Grasshopper python components) and have those complex CSG chains simply work - no waiting, no crashes.

More details, please!

If you have read this far, you might be wondering how Metafold is different from other geometry libraries, or the various widely-used CAD systems, and at a high level, how it works. Head over to the Core Concepts section for further reading.