Deploy AI at the Edge
We help companies leverage open-source models and edge computing to build faster, more cost-effective AI solutions. From model optimization to production deployment.
- Edge First
- 90%
- Reduction in latency
- Cost Efficient
- 70%
- Lower infrastructure costs
- Open Source
- 100%
- Based on proven frameworks
- Production Ready
- 24/7
- Monitoring & support
About us
Blue Keys Studio specializes in deploying AI at the edge using open-source models and cutting-edge MLOps practices. We help organizations leverage small-scale, efficient models that run on edge devices, reducing latency and enabling real-time decision-making.
Our approach combines DevOps excellence with edge computing expertise to create robust deployment pipelines. We focus on open-source frameworks like TensorFlow Lite, ONNX, and Hugging Face models, optimized for resource-constrained environments.
From model selection and optimization to deployment and monitoring, we provide end-to-end solutions that enable your AI to run where it matters most—at the edge. Based in Miami, Florida, we work with companies across industries to bring the power of edge AI to production.
- Edge-first architecture.
- Designed for performance on resource-constrained devices.
- Open source powered.
- Leveraging proven frameworks and community-driven innovation.
- Production ready.
- Built for scale with proper monitoring and deployment strategies.
Our services
We specialize in deploying AI at the edge using open-source models and production-grade MLOps pipelines.
- 01Edge AI Deployment
Deploy small-scale, efficient AI models at the edge using open-source frameworks. Optimize models for edge devices, reduce latency, and enable real-time inference close to data sources with our specialized MLOps pipelines.
- 02DevOps for Edge Computing
Build robust CI/CD pipelines for edge deployments. Infrastructure as code, automated testing, and orchestration solutions designed for distributed edge architectures. Seamlessly deploy and manage applications across edge nodes.
- 03Open Source Model Integration
Leverage open-source AI models optimized for edge computing. We help you select, fine-tune, and deploy models from Hugging Face, ONNX, and TensorFlow Lite, ensuring efficient performance on resource-constrained devices.
Open Source Tools We Use
Leveraging proven open-source frameworks and tools to deliver production-ready edge AI solutions.
TensorFlow Lite
Edge AI Framework
Optimized models for mobile and edge devices. Model quantization, delegate acceleration, and runtime optimization for resource-constrained environments.
ONNX
Model Interoperability
Open Neural Network Exchange for cross-framework model deployment. Convert and optimize models from PyTorch, TensorFlow, and other frameworks for edge inference.
Hugging Face
Open Source Models
Access to thousands of pre-trained models. Model fine-tuning, optimization, and deployment pipelines for NLP and vision tasks at the edge.
Edge Orchestration
Distributed DevOps
K3s, KubeEdge, and edge-native orchestration tools. Automated deployment, monitoring, and updates across distributed edge infrastructure.
Our work
We've helped organizations deploy AI at the edge, achieving dramatic improvements in latency, cost, and reliability.
Edge AI Deployment
Real-time inference requirements with limited connectivity
Optimized TensorFlow Lite models deployed across 500+ edge devices
90% reduction in latency
Open Source MLOps
Proprietary ML platforms too expensive at scale
Open-source MLOps stack with automated model deployment
80% cost reduction
Distributed Edge Pipeline
Managing updates across thousands of edge nodes
GitOps-based CI/CD with automated rollback capabilities
Zero downtime updates
Built for Edge. Powered by Open Source.
We combine deep expertise in edge computing, open-source AI frameworks, and production-grade MLOps to deliver solutions that perform where traditional cloud deployments can't.
Latest Insights
Stay updated with our latest thoughts on edge AI, open-source models, and MLOps best practices.
Coming Soon
We're working on exciting content about Kubernetes, DevOps, and MLOps. Check back soon for our latest insights!