Task-Conditioned Scene Graph
Builds a Task-Conditioned Scene Graph (TC-SG) — picking or synthesizing the right spatial ontology before it maps. The map is a function of the task, not a fixed universal schema.
One intelligence layer, four working parts.
the Joints sits between perception and action — it decides what to understand, builds only that, verifies before it commits, and keeps the robot safe throughout.
Open-vocabulary perception
Detects and grounds objects it was never explicitly trained on, fusing detection, segmentation, and captioning into the live scene understanding.
Real-time adaptation
Change detection updates the world model as the environment shifts; the planner re-plans on the fly instead of acting on a stale snapshot.
Trust & anti-hallucination
Confidence gating, grounded retrieval, and visual verification mean the robot abstains and re-checks rather than acting on a confident guess.
A fast loop on the robotA deep loop in the cloud
A lightweight safety loop runs continuously on the edge — the robot stays safe and moving even if the cloud link drops. Heavy multimodal reasoning runs only when something new happens, which is what makes foundation-model intelligence affordable at fleet scale.
EDGEon the robot
Fast loop • Always onSensors + local SLAM
RGB-D • LiDAR • pose
Obstacle avoidance
Real-time adaptation
Safety governor
Allow-list • e-stop • waypoints
CLOUDGPU Cluster
Deep loop • Event-triggeredOpen-vocab perception
Detect · segment · caption
Build TC-SG
Task-Conditioned Scene Graph
Reasoning + planner
Subgoals · verify · abstain
ACROSS ROBOTS AND MISSIONS
One awareness engine. Re-shaped for every deployment.
The same intelligence layer adapts to each robot and each task through reusable schema templates — so every deployment gets focused, accurate navigation, not a bloated general-purpose map.
1/3
Autonomous security patrol
Routine patrols of warehouses, substations, and construction sites. The robot maps only persistent infrastructure, flags anomalies, and adapts to what's changed since the last sweep.
DEVELOP WITH SR AGENTIC
Built for robotics teams and hardware oems
Integrate the awareness layer and keep your own action policies closed. the Joints gives you deployable navigation intelligence without rebuilding spatial reasoning for every new environment.
Open-vocabulary perception
Detects and grounds objects it was never explicitly trained on, fusing detection, segmentation, and captioning into the live scene understanding.
Deploy across domains with reusable schema templates
Indoor service, factory patrol, search-and-rescue — a new client scenario is a new schema template, not a new mapping system to build from scratch.
Edge-to-cloud, deployable out of the box
Runs as a split edge/cloud stack: an always-on safety loop on Jetson-class hardware, event-triggered reasoning on an autoscaling GPU cluster.
Security and reliability planes around every action
Action allow-lists, a safety governor, sandboxed execution, and an immutable audit log bound what a robot can physically do in the field.
Give your robots real-world judgment with