From data engineering to production deployment — we build the complete AI stack, not just models.
We design and train models purpose-built for your problem. No off-the-shelf shortcuts — every architecture choice is driven by your data, your constraints, and your success metrics.
From classification and regression to generative models and reinforcement learning — we pick the right approach for your problem, not the trendiest one.
Object detection, image classification, semantic segmentation, OCR, and video analysis. Deployed on cloud GPUs, edge devices, and embedded systems.
Our vision systems run at 4ms inference time on $200 edge hardware — because production constraints shape architecture decisions.
Text classification, named entity recognition, sentiment analysis, document summarization, and conversational AI. Fine-tuned on your domain vocabulary and validated against your actual use cases.
We build language systems that understand your business — not just general English.
Model versioning, experiment tracking, CI/CD pipelines, A/B testing, monitoring dashboards, and drift detection. Production-grade infrastructure from day one — not an afterthought.
We build the systems that keep your models running, improving, and serving reliably at scale.
Pipeline design, feature stores, data quality frameworks, real-time streaming, and data versioning. Your data, structured, reliable, and ready for model training.
Garbage in, garbage out — we make sure your data is clean, consistent, and properly featureized before a model ever sees it.
Model optimization for on-device inference — quantization, pruning, knowledge distillation, and ONNX conversion. Intelligence without cloud latency.
We deploy models on Raspberry Pis, Jetsons, custom embedded boards, and mobile devices — wherever your data lives.
4ms inference on device
No cloud dependency
Real-time processing
Free consultation — we'll assess your data, your problem, and your success criteria.