AI/ML Model Deployment

Deploy production-ready AI models at scale. From LLMs to custom ML models, we build infrastructure that's 40-60% cheaper than industry standard while maintaining performance.

Why Choose Us for AI Deployment?

Most AI deployments fail to go beyond the prototype stage or cost 2-3x more than necessary. We specialize in taking AI models from research to production, optimizing both performance and cost. Our expertise has powered AI systems serving 21M+ users with 100+ concurrent GPU services.

💰 40-60% Cost Reduction

Optimize GPU utilization, implement model batching, and use spot instances strategically. We reduce AI infrastructure costs without sacrificing performance.

⚡ Sub-Second Response Times

Model optimization, caching strategies, and efficient serving infrastructure. Our LLM deployments respond in under 1 second even at peak load.

📈 Scale to Millions

Auto-scaling GPU clusters, load balancing, and fault tolerance. We've built AI systems serving 21M+ users with 99.9% uptime.

AI/ML Models We Deploy

🤖

Large Language Models (LLMs)

Deploy GPT, Claude, Llama, Mistral, and custom fine-tuned models. Optimized inference with vLLM, TensorRT-LLM, and custom serving solutions.

Capabilities:
  • Model quantization (4-bit, 8-bit) for cost efficiency
  • Batching and request queuing
  • Multi-model serving on shared infrastructure
  • Automatic failover and GPU health monitoring
👁️

Computer Vision Models

Object detection, image classification, segmentation, and OCR. Deploy YOLO, ResNet, Vision Transformers, and custom CNN architectures.

Use Cases:
  • Real-time video processing pipelines
  • Batch image processing at scale
  • Edge deployment for low-latency inference
  • Multi-model ensembles for accuracy
📝

NLP & Transformers

BERT, RoBERTa, T5, and custom transformers for classification, NER, sentiment analysis, and text generation.

Applications:
  • Document classification and routing
  • Entity extraction and knowledge graphs
  • Semantic search and embeddings
  • Real-time translation systems
🔬

Custom ML Models

Recommendation engines, time series forecasting, anomaly detection, and custom neural networks built with TensorFlow, PyTorch, or Scikit-learn.

Solutions:
  • Personalized recommendation systems
  • Fraud detection and risk scoring
  • Predictive maintenance
  • Demand forecasting

Our AI Deployment Stack

Model Serving

FastAPI + Uvicorn Custom serving
TorchServe PyTorch models
TensorRT NVIDIA optimization
vLLM LLM serving

Infrastructure

AWS / GCP Cloud GPU instances
Kubernetes Orchestration
Docker Containerization
Spot Instances Cost optimization

Monitoring & Optimization

Prometheus + Grafana Metrics
MLflow Experiment tracking
Weights & Biases Model versioning
Custom Dashboards Business KPIs

Case Study: Undetectable AI

🤖 100+ GPU Services Serving 21M+ Users

Built a production AI infrastructure managing 100+ concurrent GPU services for AI text transformation models. The system processes millions of requests daily with sub-200ms response times while maintaining 99.9% uptime.

Technical Implementation:
  • FastAPI microservices with async GPU request handling
  • Dynamic model loading and unloading for GPU efficiency
  • Redis-based request queuing and caching
  • Kubernetes auto-scaling based on GPU utilization
  • Multi-region deployment for low latency
21M+
Active Users
100+
GPU Services
<200ms
Response Time
99.9%
Uptime

How We Reduce AI Costs by 40-60%

🎯 GPU Utilization Optimization

Model batching, dynamic model loading, and multi-tenancy on shared GPUs. We achieve 80-90% GPU utilization vs industry average of 30-40%.

⚙️ Model Quantization

4-bit and 8-bit quantization reduces memory footprint by 50-75%, allowing smaller (cheaper) GPU instances without sacrificing accuracy.

💡 Smart Caching

Cache frequent requests and intermediate results. Reduce GPU calls by 30-50% for typical workloads.

☁️ Spot Instance Strategy

Use spot instances for batch workloads (60-70% cheaper) with automatic failover to on-demand for critical requests.

Ready to Deploy AI at Scale?

Let's discuss your AI project. Get a free consultation to explore deployment strategies and cost optimization.

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