ORIGIN AI®
LIVE NEURAL NETWORKWe design, train, and deploy custom neural network architectures — CNNs, Transformers, RNNs, and diffusion models — that solve problems no classical algorithm can touch.
CNNs are the gold standard for image and video understanding. Their convolutional layers learn hierarchical features — from edges to complex shapes — making them ideal for object detection, medical imaging, quality inspection, and satellite analysis.
Transformers revolutionised both NLP and computer vision through self-attention mechanisms. Vision Transformers (ViT) treat images as sequences of patches, capturing global dependencies that CNNs miss — outperforming on complex reasoning and long-range pattern tasks.
RNNs and LSTMs excel at sequential data — time series forecasting, sensor streams, speech recognition, and natural language tasks where order matters. Their gated memory cells learn long-term dependencies that feedforward networks cannot.
Diffusion models are the state of the art for generative tasks — producing photorealistic images, 3D assets, audio, and video from text prompts. We build custom diffusion pipelines fine-tuned on your specific visual domain.
GANs pit a generator against a discriminator in a zero-sum game — producing synthetic data, augmented training sets, super-resolution images, and domain transfer outputs. Used extensively for data augmentation in low-data regimes.
Why train from scratch when you can stand on the shoulders of giants? We take foundation models pretrained on billions of samples and fine-tune them on your domain-specific data — achieving SotA results with a fraction of the compute.
Every model we deliver ships with reproducible training pipelines, evaluation benchmarks, TensorRT optimisation, and deployment-ready inference code. No black boxes.
Healthcare
U-Net based segmentation model trained on 12,000 MRI scans to detect and precisely delineate glioblastoma, meningioma, and pituitary tumours. Integrated with DICOM viewers for seamless radiologist workflow. Achieved sensitivity above 96% on held-out test set.
Fine-tuned multilingual BERT on 2 million customer feedback records across 18 languages. Classifies sentiment, intent, and urgency in real-time — routing tickets automatically and flagging escalations before SLA breach.
Customer Intelligence
Manufacturing
Custom EfficientNet-B5 model detecting micro-cracks, scratches, and surface defects on PCBs at 120 frames/second on an NVIDIA Jetson edge device. Reduced scrap rate by 78% and manual inspection cost by $2M annually.
Stacked Bi-LSTM model trained on 5 years of smart meter data to forecast electricity demand at 15-minute intervals. Enables dynamic pricing and load balancing — reducing peak overload events by 61%.
Energy / Smart Grid
Tell us your dataset, your domain, and the outcome you need. We'll design a neural architecture that actually ships.