We don’t build the robot. We build its experience.
Embodied intelligence is bottlenecked not by models, but by experience — the scarce, physically‑grounded record of how the real world is actually handled.
ΦMnesis Labs
01 — The problem
Embodied AI is starved of real‑world data.
Models have scaled. The data that grounds them in physics has not.
Internet video has no body
No force, no depth, no first‑person dexterity.
Simulation lacks reality
The sim‑to‑real gap remains the wall.
Real data is locked away
Trapped in factories, fragmented, non‑portable.
02 — What we do
From real‑world capture to physically‑aligned experience.
Step 01
Capture
Dual‑modal acquisition — Teleport teleoperation and EgoWear first‑person wearables. Two hands, real tasks.
Step 02
Reconstruct
4DGS physical reconstruction — a metric, time‑aligned twin of the scene, grounded in real geometry and force.
Step 03
Train & evaluate
Closed‑loop policy training and benchmarking, returning signal that targets the next capture.
ΦMnesis Labs
03 — The flywheel
The loop that compounds.
Each turn makes the next cheaper and the data more valuable. The flywheel, not any single model, is the durable advantage.
Capture · Reconstruct · Train · Repeat.
Capture
Reconstruct
Train
Evaluate
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04 — Why us · the moat
A position no robot maker can hold.
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Neutral third party
We don’t compete with our customers’ robots, so they trust us with the data. Compliance‑ready, data stays in‑region.
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4DGS physical grounding
Metric, physically‑aligned reconstruction — not loose video. The texture of reality, made trainable.
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Open schema
The USB‑C for embodied data — one standard every rig and model plugs into. We own the interface.
05 — Beachhead
The automotive Tier‑1 factory floor.
Vision‑led, two‑handed assembly — the dexterous tasks robots can’t yet do and where real experience is most scarce. A controlled environment, a measurable outcome, a repeat customer.
Engagement loop
01Deploy capture on the customer’s line
02Reconstruct & train on their tasks
03Return a usable policy — data stays in‑region
04Expand to the next task, next line
What anchors us
i.
Memory & space
Mnesis — from the Greek for memory. A 4DGS physical twin that remembers the world in metric measure.
ii.
Real‑world data
Factories, two hands, first‑person. The scarce, physically‑grounded experience models can’t scrape.
iii.
Closed‑loop flywheel
Capture, reconstruct, train, evaluate, recapture — a compounding advantage that out‑runs any one model.
ΦMnesis Labs
06 — Team
Deep‑tech, hardware, and infrastructure — under one roof.
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Mnesis LabsΦ
Memory for machines.
The spatial‑memory data engine for embodied AI. Let’s build its experience together.