Spatial-memory data engine

We don’t build the robot.
We build its experience.

Mnesis Labs captures scarce, physically-grounded experience from the real world, reconstructs it as a metric 4DGS twin, and closes the loop with training and evaluation. The picks-and-shovels layer for embodied AI.

How it works

From real-world capture to physically-aligned experience.

Capture · Reconstruct · Train · Repeat. Each turn makes the next cheaper and the data more valuable.

2.4M
Frames captured
11
Tier-1 lines
01

Capture

Dual-modal acquisition — Teleport teleoperation and EgoWear first-person wearables. Two hands, real tasks.

02

Reconstruct

4DGS physical reconstruction — a metric, time-aligned twin of the scene, grounded in real geometry and force.

03

Train & evaluate

Closed-loop policy training and benchmarking, returning signal that targets the next capture.

The moat

A position no robot maker can hold.

Three things compound at once — trust, physical grounding, and the interface everyone else has to plug into.

Φ

Neutral third party

We don’t compete with our customers’ robots, so they trust us with the data. Compliance-ready, data stays in-region.

Φ

4DGS physical grounding

Metric, physically-aligned reconstruction — not loose video. The texture of reality, made trainable.

Φ

Open schema

The USB-C for embodied data — one standard every rig and model plugs into. We own the interface.

Memory for machines.

Building robots that work in the physical world? Let’s build their experience together.

info@mnesislabs.ai