Now in Private Beta

One skill.
One model.
Total mastery.

CosmicBrain AI builds skill-specific Vision-Language-Action models that give robots precise, reliable capabilities — not a single monolithic model that does everything poorly, but focused experts that each do one thing extraordinarily well.

97.3% Pick & Place Accuracy
12 Skill Models Shipped
<50ms Inference Latency

General-purpose VLAs fail at the edge cases that matter

Monolithic VLA models promise everything and deliver mediocrity. They can sort of grasp, kind of pour, and almost fold. "Almost" doesn't work on a factory floor.

Generalist VLA

  • One model for hundreds of tasks
  • ~70% success on common tasks
  • Catastrophic forgetting between skills
  • Massive compute requirements
  • Unpredictable failure modes
  • Months of fine-tuning per deployment

CosmicBrain Skill Models

  • One model per skill, composed together
  • 97%+ success on target skill
  • No interference between capabilities
  • Runs on edge hardware
  • Predictable, testable behavior
  • Deploy in hours, not months

Modular skills. Mix and match.

Each skill model is a self-contained VLA expert. Compose them into task pipelines or deploy individually. New skills ship monthly.

🤲

Precision Grasp

6-DOF grasping across object geometries. Handles transparent, reflective, and deformable objects.

98.1% accuracy Available
📦

Pick & Place

Object rearrangement with language-conditioned target placement. Millimeter-level precision.

97.3% accuracy Available
🔧

Tool Use

Screwdriver, wrench, and hand-tool manipulation with force-feedback awareness.

94.7% accuracy Available
🚶

Bipedal Walk

Stable bipedal locomotion on uneven terrain with dynamic obstacle avoidance.

96.2% accuracy Available
👁

Scene Understanding

Real-time 3D scene parsing with semantic segmentation and spatial reasoning.

95.8% accuracy Available
🫗

Pour & Dispense

Liquid and granular material transfer with volume estimation and spill prevention.

93.5% accuracy Beta
🧵

Fabric Handling

Cloth folding, spreading, and manipulation for textile and garment applications.

91.2% accuracy Beta
🗺

Semantic Navigation

Language-guided navigation through indoor environments. "Go to the kitchen counter."

96.0% accuracy Available
+

Custom Skills

Need a skill we don't have yet? We train custom VLA skill models on your task data.

Talk to us →

How skill-specific VLA works

Each skill model is a compact Vision-Language-Action transformer trained on curated demonstrations for a single capability.

01

Vision Encoder

Multi-camera RGB-D input processed through a lightweight vision transformer. Extracts task-relevant features — not everything in the scene, just what matters for this skill.

Input: RGB-D (640×480) × N cameras → Skill-specific feature tokens
02

Language Conditioning

Natural language instructions set the task parameters within the skill's domain. "Pick up the red mug" activates the grasp model with object-specific attention.

Input: Text instruction → Skill-conditioned action prior
03

Action Decoder

Diffusion-based action head generates smooth, collision-aware trajectories. Each skill model outputs actions in its own optimized action space.

Output: 6-DOF end-effector trajectory @ 10Hz, confidence scores
04

Skill Router

A lightweight orchestrator selects and sequences skill models based on high-level goals. Handles transitions, pre-conditions, and fallbacks.

Router: "Make coffee" → [Navigate → Grasp(mug) → Place(machine) → Press(button)]

Purpose-built for the edge

Three model tiers to match your hardware and latency requirements.

Nano

CB-Nano

Ultra-lightweight for embedded systems. Single-skill deployment on resource-constrained hardware.

  • Parameters45M
  • Latency12ms
  • HardwareJetson Orin Nano
  • Skills per device1-3
Learn More
Ultra

CB-Ultra

Maximum capability for complex manipulation. Research-grade performance with production reliability.

  • Parameters1.2B
  • Latency48ms
  • HardwareA100 / H100
  • Skills per deviceUnlimited
Learn More

Deploy in minutes, not months

Python SDK with ROS2 integration. Load a skill, run inference, get actions.

deploy_skill.py
from cosmicbrain import SkillModel, SkillRouter

# Load skill-specific models
grasp = SkillModel.load("cosmicbrain/precision-grasp-v3")
place = SkillModel.load("cosmicbrain/pick-place-v2")
navigate = SkillModel.load("cosmicbrain/semantic-nav-v1")

# Compose into a task pipeline
router = SkillRouter(skills=[grasp, place, navigate])

# Run with natural language
actions = router.execute(
    instruction="Pick up the screwdriver and bring it to the workbench",
    obs=camera.get_observation()
)

# Each action comes with confidence + skill attribution
for action in actions:
    print(f"Skill: {action.skill} | Confidence: {action.confidence:.2f}")
    robot.execute(action)

Building the skill layer for physical intelligence

We believe robots don't need bigger brains — they need better skills. CosmicBrain AI is a robotics AI company building the world's largest library of skill-specific VLA models.

Our team comes from leading robotics labs and AI companies. We've shipped manipulation systems in warehouses, kitchens, and factories. We know what breaks in production, and we build models that don't.

We're backed by top-tier investors and are building from San Francisco.

Compatible with
ROS2 NVIDIA Isaac MuJoCo PyBullet

Our Thesis

Skill decomposition is the path to reliable robot intelligence. Instead of training one model to do everything, we train many models to each do one thing perfectly — then compose them.

Ready to give your robots
real skills?

Join the private beta. Tell us what you're building and we'll set you up with the right skill models.