Self-Hosted LLM Serving

Deploy and operate large language models on your own infrastructure. We build production vLLM clusters on GKE and OpenShift with GPU autoscaling, model weight caching, and OpenAI-compatible API endpoints.

Keep your data private, control your costs, and eliminate vendor lock-in. Our deployments serve Llama, Mistral, Qwen, and other open-weight models with enterprise-grade reliability.

vLLM GKE OpenShift AI L4 / H100 Terraform Helm
  • GPU node pool provisioning with autoscaling (0 to N)
  • Model weight caching on GCS / S3 for fast cold starts
  • Prefix caching and continuous batching for throughput
  • HPA based on request queue depth
  • Prometheus metrics and Grafana dashboards
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Agentic RAG Systems

Build intelligent retrieval-augmented generation pipelines that go beyond simple search. Our agentic RAG systems use tool-calling agents, persistent memory, and multi-step reasoning to answer complex queries over your data.

From vector database selection and embedding strategy to agent loop design and tool integration, we architect the full pipeline.

LangChain PGVector CLIP FastAPI Redis
  • Vector database deployment (PGVector, Pinecone, Weaviate)
  • Multi-modal embedding (text, image, audio)
  • ReAct agent loop with native tool calling
  • Persistent conversation memory with fact extraction
  • Streaming responses via WebSocket / SSE

AI-Powered Security & Surveillance

Intelligent surveillance systems that combine computer vision, natural language processing, and real-time alerting. Query your security footage in plain English and get instant, context-aware answers.

Our CV pipelines process camera feeds through multi-model detection (YOLO, Mask R-CNN), generate embeddings (CLIP) and captions (BLIP), and store everything in a searchable vector database.

YOLO Mask R-CNN CLIP BLIP PGVector
  • Real-time object detection and classification
  • Friendly / unfriendly entity classification
  • Natural language querying over detection history
  • Automated alerting and threat escalation
  • GPU-accelerated batch processing on Kubernetes
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Kubernetes & Cloud Infrastructure

Production Kubernetes clusters designed for AI workloads. We handle the entire infrastructure lifecycle: VPC networking, GPU node pools, IAM, storage, CI/CD, and monitoring.

Everything is codified in Terraform and Helm, version-controlled in Git, and deployed through automated pipelines. No manual kubectl required.

Terraform GKE OpenShift Helm ArgoCD
  • GKE, EKS, and OpenShift cluster provisioning
  • GPU node pools with spot/preemptible instances
  • Workload Identity and least-privilege IAM
  • Istio service mesh and network policies
  • Cost optimization and right-sizing

How We Work

Flexible engagement models tailored to your needs.

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Project-Based

Fixed-scope engagements with clear deliverables. Ideal for migrations, new deployments, and architecture reviews.

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Retainer

Ongoing support for your AI infrastructure. Monitoring, scaling, upgrades, and on-call incident response.

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Advisory

Architecture reviews, technology selection, and strategic guidance for your AI and infrastructure roadmap.

Ready to Get Started?

Tell us about your project and we'll scope the right engagement for your needs.

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