Who this comparison is for
AI Hub highlights
- Plug-in any of OpenAI/Anthropic/Gemini/Mistral/HF via one API
- Searchable conversation history with ratings & snippets
- SAML-gated audit CSV + monthly quotas
Google Vertex AI highlights
- Deep GCP integration & ecosystem tooling
- Managed endpoints for Google and partner models
Capability matrix
| Capability | AI Hub | Google Vertex AI | Notes |
|---|---|---|---|
| Cross-provider abstraction | Full | Partial | Vertex within GCP vs Hub across vendors |
| Turnkey chat memory & FTS search | Full | Manual | DIY with Datastore/Elastic/BigQuery |
| Policy moderation (block/warn/allow) | Full | Partial | Hub adds policy layer + auditing |
| Usage quotas & spend dashboard | Full | Partial | Hub enforces token ceilings globally |
| Job queue + progress/done events | Full | Manual | DIY with Pub/Sub + Cloud Tasks |
| Redis memo-cache | Full | Manual | Add Memorystore or similar on GCP |
| Web UI (Chat/Playground/Keys/Audits) | Full | Partial | Hub includes single-instance UI |
- Many customers run AI Hub as a thin control plane over Vertex AI models to unify policies across stacks.
Total cost of ownership
Vertex AI is ideal for GCP-native ML. AI Hub reduces control-plane buildout when you want multi-provider prompts, shared chat memory, audits, quotas, and fallbacks without bespoke services.
Assumptions
- 2+ providers required over time
- Compliance needs audit exports regularly
Migration plan
From Vertex AI · Keep Vertex models; adopt AI Hub for governance & chat
-
1
Add Vertex credentials to KeyVault (or route via Gemini adapter)
-
2
Switch app calls to AI Hub Query API; validate outputs
-
3
Enable quotas, moderation policy, and audit export
-
4
Adopt Hub Chat API to avoid custom conversation storage
Security
- Encryption at rest & in transit; workspace isolation
- Permission checks for admin/config/usage endpoints
Evidence & sources
| Claim | Value | Source |
|---|---|---|
| Chat system & audits | Conversations/FTS + AiAudit CSV | product_docs |
About AI Hub
AI Hub centralizes generative AI for your workspace with a single, policy-aware gateway to multiple providers. Teams get a streamlined chat experience with searchable history and feedback, a minimal Query API for quick prompts, and embeddings for retrieval workflows. Operators gain visibility with usage & cost tracking, quotas, and exportable audit logs.
Choose the best model for each task, fail over between providers, and moderate inputs/outputs with block/warn/allow policies. Keys are encrypted at rest and scoped per workspace. Long-running tasks run on a background worker and broadcast events so other apps can react in real time.
Designed for safety and speed: opinionated defaults, least-privilege access, and drop-in APIs that make it easy to bring AI to every surface of Velaxe.