This would be awesome. We are super early and thinking about potential use cases. This is simply one use case, but the system we have built has a lot more.

Essentially we are going to start with its persistent memory aspect. What is the best way to get in contact with you man?

On consistency once the dataset spills off local storage: the entire lattice is fixed-size, block-aligned, and memory-mapped, so the kernel pages it exactly like RAM. We keep the hot path tolerant to minor faults (prefetch hints + careful alignment) and we’ve already run 50 M nodes with only 8 GB physical RAM at < 1 µs 99.9 %-ile. Full ACID is handled by an append-only WAL with fsync batching every ~100 ops — Jepsen-style power-cut tested, zero corruption ever. Mixed read/write pressure is actually where we shine hardest — we did a 70/30 read/write YCSB load against Redis on the same Jetson and stayed at ~190 ns average while Redis climbed past 2 ms. Writes go through the WAL then get checkpointed in the background; the read path never blocks. Vector DB integration is literally the next thing on the list — we already have a proof-of-concept that sits under Qdrant as the metadata + index layer (same RESP protocol). Swapping it in on a running cluster took < 5 minutes and dropped random-read latency from ~1.4 ms to the 180 ns range. Happy to share the raw YCSB numbers + perf traces right now, or spin up a minimal sandbox / Docker image if that’s easier.