SNIM® AI, the Social Network of Intelligent Machines, is the platform that ensures fleets of autonomous machines don’t go rogue.
Request a DemoWhen Physical AI is deployed across heterogeneous fleets of autonomous devices, with each variant tuned to a different skill, sensor stack, and environment, we observe the following:
The technical challenges are inevitable, so we built SNIM® AI.
SNIM® AI is the operational sustainment layer of embodied AI, defining a new category that continuously monitors, localizes failure, retrains on real field data, and redeploys models across the fleet so every edge device runs the best-available, production-ready AI.
The signals a Physical AI model encounters are highly variable and the labeled examples are scarce. Models degrade faster than centralized retraining can catch up. Often there is no big dataset to retrain on at all, and simulated data for many instances is not good enough.
SNIM® AI was built for this reality. Deployed machines learn from each other in the field, using whatever small slices of real operational data exist.
SNIM® AI uses an innovative, patented method for dynamic peer learning called 'Who's My Friend' (WMF™), enabling autonomous machines to learn from their environment and each other.
Explore WMFSNIM® AI manages models of all sizes, variants, and versions in one coherent repository. The platform tracks devices, skills, and missions to match each one with the best model.
Many real-time applications require ultra-low latency AI models that run on the edge, operating within strict SWaP (Size, Weight, and Power) constraints.
Edge AI models that fit within minimal memory and battery footprints are required, with the ability to update and maintain multiple permutations of these models per task/mission.
With SNIM® AI, every deployment makes the next one smarter, every field signal sharpens the next model, and every rollout compounds the value of your AI investment.
SNIM® AI closes the loop between production behavior and the next model version. Automated failure localization, targeted retraining datasets generated from real field data, and open integration with your existing MLOps stack.
SNIM® AI acts as the system of record for operational AI performance across the fleet. Centralized visibility, governance, and policy-driven control over how AI changes across deployed assets.