Technology

Open where it helps. Engineered for production.

We evaluate tools and models to suit your workload rather than requiring a single proprietary stack.

Technology

LayerCandidate toolsEXZAI service
Employee AI experienceOpen WebUI, purpose-built portalsAuthentication, UX, role-specific workflows
Local model runnerOllamaLocal development and prototyping
Production inferencevLLM, SGLang, NVIDIA NIM where licensedDeployment, benchmarking, batching and scaling
Model gatewayLiteLLM or equivalentRouting, usage controls, budgets and logging
Retrieval & searchQdrant, PostgreSQL + pgvector, rerankersIndexing, retrieval, permissions, evaluation
Workflow & applicationsn8n, Python, FastAPI, business APIsAgents, integrations, human-in-the-loop flows
Packaging & orchestrationDocker, Kubernetes, virtualizationReliable environments, rollouts, lifecycle
InfrastructureGPU systems, compute, network, storageArchitecture, procurement, installation
ObservabilityPrometheus, Grafana, OpenTelemetryMonitoring, diagnostics, capacity planning
Security & identityOIDC/SSO, access policies, secrets management, encryptionSecure architecture and operational controls

Technology names indicate tools that may be used in project architectures. They do not indicate commercial partnerships or endorsement.

Reference architecture

Reference architecture — Illustrative architecture Employees & applications → AI portal / business APIs → Identity, access & policies → Model gateway → Private model serving → GPU infrastructure / hosting; AI portal / business APIs → Knowledge retrieval (RAG) → Approved documents & systems; Model gateway → Approved external APIs (optional); → Monitoring, audit & operations Private trust boundary Employees & applicationsAI portal / business APIsIdentity, access &policiesKnowledge retrieval (RAG)Approved documents &systemsModel gatewayPrivate model servingGPU infrastructure /hostingMonitoring, audit & operationsApproved external APIs(optional)
Illustrative architecture

Engineering principles

  • Model and software licenses are reviewed for commercial use before deployment.
  • Model endpoints sit behind a reverse proxy, network controls, authentication and authorization.
  • Document handling, embeddings and telemetry destinations are confirmed before describing a system as fully local.
  • Citations help verification but do not ensure correctness; evaluation and human review apply where outcomes matter.
  • Agents do not take destructive or privileged production actions without human approval.

Ready to make AI work for your organization?

Tell us what you want to build. We will help define a practical technical and commercial path.