Deploy production-ready computer vision in 14 days.
99% accuracy with 90% less training data.
Advanced vision-language models designed for manufacturing excellence.
Sub-pixel accuracy for defects invisible to traditional inspection methods.
Real-time inference on production lines with no cloud dependency.
Achieve production accuracy with 50 images instead of 50,000.
Enterprise-grade vision AI built on proven deep learning foundations.
Built on state-of-the-art neural architectures optimized for manufacturing environments.
Open-source foundations with enterprise extensions.
# Dynamic Routing Capsules for defect localization
model = CapsuleNetwork(
input_channels=3,
primary_capsules=32,
digit_capsules=num_defect_types,
routing_iterations=3
)Capsule networks preserve spatial relationships, critical for precise defect localization in manufacturing contexts.
# Optimized for NVIDIA Jetson
import tensorrt as trt
engine = optimize_for_edge(
model,
precision='FP16',
max_batch_size=4
)Hardware-specific optimization achieves real-time performance on edge devices without cloud dependency.
# Federated learning across facilities
update = federated_average(
local_gradients,
aggregation='secure',
differential_privacy=True
)Privacy-preserving federated learning enables model improvement without exposing sensitive production data.
Building on community innovations, contributing back improvements.
Core deep learning framework
Cross-platform model deployment
NVIDIA GPU optimization
Computer vision preprocessing
Model versioning & tracking
Container orchestration
Measurable results from day one.
See Gramm AI in action at your facility.