Your Robots Forget.
CogmemAi Remembers.
Persistent memory for robot fleets, drones, and autonomous vehicles: mission knowledge, operator corrections, and site-specific learnings that survive reboots, follow units across deployments, and propagate fleet-wide.
The Amnesia Problem in Autonomy
Every reboot is a lobotomy. A robot that mapped a warehouse yesterday should not rediscover the loading dock today.
Knowledge Dies at Reboot
Session context, operator guidance, and learned quirks of a site evaporate when the process restarts. The unit starts every shift as a stranger to its own workplace.
Fleets That Cannot Share
Unit 7 learns that dock 3 has a low clearance. Units 1 through 6 hit the same beam, one after another, because nothing carries a lesson from one machine to the next.
Corrections That Do Not Stick
An operator corrects the same behavior every week. Without a memory layer that turns corrections into standing rules, the correction lasts exactly one session.
What CogmemAi Gives an Autonomous Fleet
Fleet Memory
What one unit learns, the fleet knows. Site maps, hazards, procedures, and fixes are saved once and recalled by every unit, with attribution of which machine learned it and when.
Corrections Become Rules
Operator corrections synthesize into mandatory behavioral rules through auto-skills. Correct a behavior once; the whole fleet obeys from then on, and the rule tracks its own confidence.
Built for Intermittent Connectivity
Cloud, local, and hybrid storage modes. Units cache memory locally, operate through dead zones, and reconcile when the link returns.
Air-Gapped Deployments
For defense platforms and sites where nothing may leave the perimeter, CogmemAi Edge puts the entire engine on your own hardware, under contract, with your keys.
MCP and REST, Your Choice
MCP tools for agentic stacks, a plain REST API for embedded controllers, a Python SDK (pip install cogmemai) for everything in between.
Encrypted Mission Data
Memory content is encrypted at rest with post-quantum cryptography. What your fleet knows is nobody else's business.
A Robot That Remembers, in Ten Lines
from cogmemai import CogmemAi
memory = CogmemAi(api_key="cm_your_key", project_id="warehouse-fleet")
# On boot: load everything this fleet knows about the site
context = memory.get_project_context(context="dock operations, unit 7")
# During operation: persist what the unit learns
memory.save_memory("Dock 3 clearance is 2.1m; route tall loads via dock 5")
# Operator correction becomes fleet knowledge
memory.save_correction(wrong="approached dock 3 with raised mast",
right="lower mast before entering dock 3")Robotics Questions, Answered
Does CogmemAi run on the robot itself?
The client runs wherever your control stack runs and can cache memory locally for offline operation. The Intelligence Engine runs in our cloud by default, or on your own hardware with CogmemAi Edge for air-gapped fleets.
What latency should we plan around?
Local and hybrid modes answer recalls from the on-device cache in milliseconds. Cloud recalls are a normal HTTPS round trip. Safety-critical control loops should never block on a memory call, and the SDK makes asynchronous use natural.
How does fleet-wide sharing stay consistent?
Memories carry attribution and timestamps, contradiction detection flags conflicting facts at recall time, and consolidation merges duplicates, so ten units reporting the same hazard produce one clean fact.
Can we keep everything inside our own network?
Yes. CogmemAi Edge deploys the complete engine inside your perimeter under an annual license, fully air-gapped, with keys you generate and hold.
Give Your Ai a Memory Today
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