Great question - TVM / OctoML are a great option if you have an off-the-shelf ML model and off-the-shelf hardware. Tensil is different in that you can actually customize the accelerator hardware itself, allowing you to get the best trade-off of performance / accuracy / power usage / cost given your particular ML workload. This is especially useful if you want to avoid degrading the accuracy of your models (e.g. through quantization) to achieve performance targets.

That makes sense. So is this only for edge compute use cases, or can I use tensil on an FPGA I have running in my data centre?

You absolutely can use it in a data centre. You can even tape out an ASIC using these designs! Currently we've done most of our prototyping with edge FPGA platforms but if you want to try other platforms we'd love to help you get started. You can email me at tom@tensil.ai or use the contact methods on the website.