Robotic Memory as a Service
Engram
A persistent, queryable memory layer for autonomous robots.
Autonomous robots see the world as an endless stream of camera frames, depth scans, and motion. Engram turns that stream into a durable memory — one a robot can search in plain language to recall what it saw, where it saw it, and when.
The problem
Robots perceive constantly.
They rarely remember.
A robot on a multi-hour shift produces hundreds of thousands of observations; over several days, tens of millions. Without somewhere to keep them, each experience is gone the moment it scrolls off the sensor buffer — so the robot can't answer the simplest question about its own past.
Long-horizon autonomy needs a memory that outlives the moment and can be questioned on demand. That memory layer is what Engram provides.
What Engram is
One memory, three dimensions.
Every observation a robot makes is anchored in three places at once — somewhere in 3D space, at a moment in time, and at a point in meaning. Engram holds all three together in a single memory, so a question can constrain any one of them, or all of them.
Persistent
Experience is written to a memory that lasts the whole deployment and keeps growing — from an eight-hour shift to a multi-day mission — and stays fast as it scales.
Unified
Space, time, and meaning live in one memory rather than three disconnected stores, so a layered question is resolved together instead of being stitched back by hand.
Queryable
Ask in plain language and get back the handful of observations that actually answer the question — with a confidence score, so the robot knows when it has seen enough.
How a memory is formed
From sensor stream to searchable memory.
Engram sits downstream of a robot's sensors and perception. Raw streams flow in continuously; structured, searchable memories come out the other side.
sense → understand → remember · a continuous loop while the robot is awake
What you can ask
Questions that cross space, time, and meaning.
Because the three dimensions are remembered together, Engram answers questions that combine them — and ignores everything irrelevant on the way to the answer. A question can pin one dimension tightly and leave the others open.
Find a thing by what it is
Where is the coffee machine?
Recall what was near a spot
What did you see near the kitchenette?
Look back to a moment
What was here an hour ago?
Pin every dimension together
The yellow pole near the intersection, the last time you saw it.
Tie one object to another
A pen next to a monitor.
Search inside a described place
An object in a wide, sunny room.
Track how the world changed
Where did the blue toolbox go?
Memory, delivered as a service
You bring the robot. Engram is the memory behind it.
Engram is a managed memory layer that ingests live perception and returns a world model you can query through a simple interface. No index to build, no storage to operate, no retrieval stack to tune — the memory scales with the mission and stays fast as it grows.