A new chapter
in hardware engineering.

We’re building an AI-native hardware engineering stack for a future where intelligent agents participate directly in designing, verifying, debugging, and validating hardware.

Our work spans the full flow—from frontend compilation and semantic representations to execution, transformation, netlists, verification, evidence, and autonomous engineering workflows.

Connected layers of the Memdance stack: design capture, semantic IR, transformations, execution, netlists, evidence, and agent interfaces, sharing identity and semantics.

The goal is not simply to make existing hardware tools faster with AI.

It is to rethink how hardware is built when AI becomes a first-class engineer.

We’re an early-stage startup. Our products are in heavy development. Here, we share what we’re thinking, learning, and building.

FROM THE JOURNAL

Notes from the workbench.

  1. Our Ambition: Rethinking Hardware Engineering with AI

  2. Case Study: Tracing a Hardware Failure to Evidence

  3. CPU validation is a team sport

Read the journal