Custom Private AI and Edge Solutions
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Private AI & Edge AI Solutions | GenAI Protos
Custom private AI deployment for regulated industries — sovereign AI, on-premise LLM, air-gapped environments, GDPR/HIPAA-compliant architecture, and edge AI inference. Full data sovereignty.
Custom Private AI & Edge Solutions
Design and deployment of private AI systems and edge AI solutions that run on-premise or on edge devices, keeping sensitive data within secure infrastructure boundaries while delivering real-time AI performance for regulated industries.
Private AI and Edge AI Deployment
Enterprises in Regulated Industries
Custom Private AI and Edge Solutions
Secure, on-device AI for maximum privacy and performance
Deploy powerful AI directly on devices. From TinyML sensors to NVIDIA Jetson supercomputers, we build Edge AI solutions optimized for speed, privacy, and offline capability.
Deploy at Edge
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Ultra Low Latency, 100% Offline Capability
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The Edge AI market is projected to reach $66.47 billion by 2030 (21.7% CAGR), driven by demand for real-time processing, enhanced privacy, and autonomous operation. Our Edge AI development services lead this innovation, deploying intelligence across the full hardware spectrum – from TinyML microcontrollers to NVIDIA DGX Spark desktop AI supercomputers.
We develop optimized AI models for on-device execution using advanced quantization, pruning, and knowledge distillation techniques, ensuring high performance on NVIDIA Jetson, Google Coral Edge TPU, Intel Movidius, AMD Kria, and Qualcomm platforms. Our IoT edge AI solutions deliver real-time AI inference with ultra-low latency – critical for autonomous systems, industrial automation, and 5G MEC applications.
Our expertise spans on-device LLMs (up to 200B parameters), generative AI at the edge, TinyML development, and Edge MLOps. We build embedded AI solutions, privacy-preserving AI with federated learning, and hybrid edge-cloud architectures that maximize data security and enable smart, resilient systems at the edge.
Why Move AI to the Edge?
Cloud dependency creates bottlenecks. We solve the critical challenges of modern deployment.
High Cloud Costs
Local processing significantly cutting bandwidth usage and cloud storage fees.
Latency Issues
On-device execution enables real-time responses by eliminating network transmission delays.
Privacy Concerns
Keeping sensitive data locally on-device minimizes exposure to external breaches.
Connectivity Gaps
Operations continue autonomously without relying on constant, stable internet access.
Hardware Constraints
Running complex LLMs on battery-powered devices requires extreme optimization.
Integration Complexity
Bridging the gap between AI models and embedded firmware.
Edge AI Development Services
Comprehensive solutions for deploying AI at the edge.
Strategic Edge AI Architecture & Use Case Design
Architecture
5G
ROI
Define high-impact edge AI applications, hybrid edge-cloud architectures, and 5G MEC deployment strategies for optimal ROI.
Edge AI Application Development (Remote & On-Site)
NVIDIA
IoT
Development
Custom industrial edge AI, autonomous systems, IoT edge AI development across NVIDIA DGX Spark, Jetson, Google Coral, and TinyML platforms.
Edge AI Setup & Research Support
Setup
POC
Research
Platform selection, proof-of-concept development, and feasibility assessment for NVIDIA, Google, Intel, AMD, and Qualcomm edge AI platforms.
Edge AI Testing & Validation
Testing
Validation
Hardware
Performance testing, accuracy validation, and hardware compatibility verification for real-time AI inference across edge devices.
Edge AI Integration Services
Integration
Hybrid
Cloud
Seamless integration with IoT infrastructure, industrial systems, 5G MEC networks, and hybrid edge-cloud architectures.
Edge AI Deployment & Maintenance
Deployment
MLOps
OTA
Production deployment using containerized edge AI, Edge MLOps automation, fleet management, and OTA model updates.
Edge AI Data Pipeline & Storage Engineering
Data Pipeline
Privacy
Storage
Efficient data pipelines for edge AI with real-time ingestion, preprocessing, edge caching, and privacy-preserving architectures.
Edge AI Training & Enablement
Training
TinyML
Optimization
Team training on edge AI development, on-device optimization, TinyML, Edge MLOps, and platform-specific SDKs.
Our Built Edge AI Applications
Real-world Edge AI solutions built for enterprise impact.
Inferencing 120B GPT OSS on NVIDIA DGX Spark.
JetsonLLM deploys containerized LLM inference on NVIDIA Jetson Orin Nano, enabling real-time text generation and analytics locally without cloud dependency, showcasing privacy-centric, ultra-efficient edge AI capabilities.
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View Solution
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LLM Inference
Edge AI
NVIDIA DGX Spark
Local Processing
Privacy-First
Containerized AI
Real-time Generation
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Fully Local Multilingual Voice Agent
Real-time voice AI deployed on NVIDIA DGX Spark with LiveKit orchestration, Whisper speech recognition, multilingual Riva text-to-speech, and local GPT-OSS 120B inference for enterprise speech automation.
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Voice AI
Multilingual
Speech-to-Text
Enterprise Automation
NVIDIA Riva
Local Inference
LiveKit
Spark Vault
Spark Vault is a secure, on-premises enterprise search solution for medical documents on NVIDIA DGX Spark, combining containerized AI models and vector databases for rapid, private searches without cloud dependency.
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Enterprise Search
Medical AI
Vector Database
On-Premises
Document Search
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Why GenAI Protos for Edge AI Solutions
Unmatched Hardware Platform Expertise
Deep expertise across NVIDIA DGX Spark, Jetson Orin, Google Coral Edge TPU, Intel Movidius, AMD Kria, Qualcomm, Hailo, and ARM platforms.
Leadership in Emerging Edge Technologies
Pioneers in on-device LLMs (up to 200B parameters), generative AI at the edge, 5G MEC, TinyML, and agentic edge AI.
Mission-Critical Reliability & Field-Tested Performance
Production-grade edge AI with 99.9% uptime across industrial automation, autonomous vehicles, healthcare, and smart cities.
Complete Edge AI Lifecycle Management
Full-stack ownership including Edge MLOps, hybrid architectures, federated learning, OTA updates, and fleet management.
Advanced Edge AI Optimization & Performance Engineering
Achieve 3–10x performance improvements via quantization (FP4, INT8), pruning, distillation, and hardware-aware optimization.
We Build On The World's Best Platforms
Our expertise spans the full spectrum of edge AI hardware.
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FAQs
What is Edge AI Development with GenAI Protos?
GenAI Protos creates AI applications that process data locally on devices like IoT sensors and NVIDIA chips, eliminating cloud dependency.
Which hardware platforms do you support?
We optimize AI for NVIDIA Jetson, Google Coral, Intel Movidius, AMD Kria, NVIDIA DGX Spark, Qualcomm, and TinyML microcontrollers.
Do you support offline AI inference?
Yes, our edge architectures run autonomously with real-time intelligence even in remote locations without internet.
What industries use your Edge AI services?
Industrial automation, healthcare devices, autonomous vehicles, smart cities, and 5G edge computing environments.
Ready to Go Offline?
Unlock the power of AI at the edge. Faster, safer, and cost-effective.
Latency
50ms
Cost Cut
60%
100%
Start Your Project
GenAI Protos
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Schedule a Call
Custom Private AI and Edge Solutions
Deploy powerful AI directly on devices. From TinyML sensors to NVIDIA Jetson supercomputers, we build Edge AI solutions optimized for speed, privacy, and offline capability.
Custom Private AI and Edge Solutions
The Edge AI market is projected to reach $66.47 billion by 2030 (21.7% CAGR), driven by demand for real-time processing, enhanced privacy, and autonomous operation. Our Edge AI development services lead this innovation, deploying intelligence across the full hardware spectrum – from TinyML microcontrollers to NVIDIA DGX Spark desktop AI supercomputers.
We develop optimized AI models for on-device execution using advanced quantization, pruning, and knowledge distillation techniques, ensuring high performance on NVIDIA Jetson, Google Coral Edge TPU, Intel Movidius, AMD Kria, and Qualcomm platforms. Our IoT edge AI solutions deliver real-time AI inference with ultra-low latency – critical for autonomous systems, industrial automation, and 5G MEC applications.
Our expertise spans on-device LLMs (up to 200B parameters), generative AI at the edge, TinyML development, and Edge MLOps. We build embedded AI solutions, privacy-preserving AI with federated learning, and hybrid edge-cloud architectures that maximize data security and enable smart, resilient systems at the edge.
Why Move AI to the Edge?
Cloud dependency creates bottlenecks. We solve the critical challenges of modern deployment.
Edge AI Development Services
Comprehensive solutions for deploying AI at the edge.
We Build On The World's Best Platforms
Our expertise spans the full spectrum of edge AI hardware.
Our Built Edge AI Applications
Real-world Edge AI solutions built for enterprise impact.
Inferencing 120B GPT OSS on NVIDIA DGX Spark.
JetsonLLM deploys containerized LLM inference on NVIDIA Jetson Orin Nano, enabling real-time text generation and analytics locally without cloud dependency, showcasing privacy-centric, ultra-efficient edge AI capabilities.
Fully Local Multilingual Voice Agent
Real-time voice AI deployed on NVIDIA DGX Spark with LiveKit orchestration, Whisper speech recognition, multilingual Riva text-to-speech, and local GPT-OSS 120B inference for enterprise speech automation.
Spark Vault
Spark Vault is a secure, on-premises enterprise search solution for medical documents on NVIDIA DGX Spark, combining containerized AI models and vector databases for rapid, private searches without cloud dependency.
