Velaxe
AI Hub — Unified LLM Gateway, Chat, Embeddings & Jobs | Velaxe

AI Hub

AI Hub vs AWS Bedrock

Bedrock offers a managed multi-model service within AWS. AI Hub complements or substitutes with a vendor-neutral gateway, built-in chat memory, quotas, moderation policy, and events—ideal when workloads span clouds or include non-AWS providers.

Who this comparison is for

Teams multi-cloud or provider-agnostic by policy Products needing built-in chat history & search Ops demanding spend controls and audit exports

AI Hub highlights

  • Cross-cloud providers (OpenAI, Anthropic, Gemini, Mistral, HF)
  • Chat storage/search, ratings, snippets out-of-box
  • Monthly token quotas + usage dashboards

AWS Bedrock highlights

  • Deep AWS integration & IAM controls
  • Managed access to a set of foundation models

Capability matrix

8 rows
Capability AI Hub AWS Bedrock Notes
Provider neutrality (multi-cloud) Full Partial Bedrock models within AWS vs cross-ecosystem routing
Conversation memory & FTS search Full Manual DIY with DynamoDB/OpenSearch if on AWS
Moderation policy + CSV audits Full Partial Hub policy modes + export included
Usage quotas (hard) + dashboard Full Partial Hub enforces monthly token ceilings
Jobs queue + AI.job.* events Full Manual SQS/Lambda DIY on AWS
Admin key vault (workspace-scoped) Full Manual Hub ships vault; AWS Secrets Manager optional DIY
Redis memo-cache for deterministic calls Full Manual DIY ElastiCache or similar
Events bus for app integrations Full Manual SNS/SQS wiring otherwise
  • Choose based on cloud posture and governance needs; many teams run AI Hub alongside Bedrock.

Total cost of ownership

Within AWS-only stacks, Bedrock centralizes access. If you also need chat UIs, audits, quotas, and cross-provider fallback, AI Hub reduces the amount of glue code and ongoing ops.

Assumptions

  • Multi-product org shipping several AI features
  • Need for cross-cloud portability / second-source

Migration plan

From AWS Bedrock · Adopt AI Hub for chat/governance while keeping Bedrock as a provider

  1. 1

    Keep Bedrock as primary; add its creds to AI Hub KeyVault

  2. 2

    Point apps to AI Hub Query API; enable UsageDaily quotas

  3. 3

    Optionally add OpenAI/Anthropic/Gemini as fallback routes

  4. 4

    Use Hub Chat API for memory/search without custom storage

Security

  • AES-256-GCM at rest; TLS 1.2+ in transit; SAML-gated exports
  • RBAC-permission checks: ai.chat.use / ai.backend.call / ai.configure

Evidence & sources

Claim Value Source
Quotas & usage dashboard Last-30-day rollups + hard ceilings 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.

Run Bedrock via AI Hub with audits & quotas