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Version: 2.0

Private Deployment Overview

A Vectara private deployment provides the same platform capabilities within your infrastructure, designed for organizations with specific data residency or security requirements.

Why private deployment?

  • Data stays put: Processing takes place where your information resides. No outside API calls (unless you want them), no uploads.
  • Compliance-ready: For secret contexts, you create air-gapped systems. HIPAA, SOC 2, and FedRAMP controls are all handled by your own methods.

Agentic AI platform capabilities​

  • Multilingual semantic search capabilities
  • Advanced RAG with accuracy controls
  • AI Agents framework with tool integration
  • Enterprise-grade performance

Deploy anywhere​

  • On-premises: Traditional data center deployments
  • Cloud VPC: Major cloud providers supported
  • Air-gapped: Isolated network environments
  • Kubernetes: Container-based deployment

Technical deployment​

Infrastructure as code deployment:

  1. Terraform/Helm packages - Deploy like any other K8s app
  2. Your models or ours - Connect OpenAI, Anthropic, Google, or use included models
  3. Standard integrations - OIDC auth, Prometheus metrics, S3 storage

Why engineers choose private deployment​

  • Control the stack: Your K8s, your monitoring, your backups
  • Model flexibility: Use GPT-4 for chat, Llama for summaries, whatever works
  • No black boxes: See the metrics, logs, and traces
  • Updates when ready: Deploy updates on your schedule