Arthur vs Vertex AI Vector Search

Arthur helps enterprises find AI agents across their environments and provides tools to observe and govern them. Discovery sensors monitor OpenTelemetry streams, MCP servers, network traffic, cloud APIs, and employee endpoints. The platform traces agent steps, tool calls, retrieved context, costs, latency, and behavior over time. Its governance features apply machine-checkable policies and provide real-time guardrail verdicts for prompt injection, PII exposure, restricted models, and off-policy tool use. Deployment options include hosted SaaS, on-premises, and hybrid; for hybrid setups, the evals engine runs beside customer workloads so sensitive data stays in the environment. Arthur lists RBAC, SSO, and deployed engineering support with every deployment option. Documented integrations include OpenAI, Anthropic, LangChain, LiteLLM, CrewAI, LlamaIndex, OpenAI Agents, Google ADK, AWS Bedrock, and Mastra. The Free plan is free, with up to four use cases, two projects, and seven-day data retention. Premium is $60 a month; Enterprise pricing is custom.

Vertex AI Vector Search is a cloud vector search engine for semantic search, recommendations, and generative AI applications. It uses Google Research’s ScaNN algorithm and supports dense embeddings, sparse embeddings, and hybrid search combining semantic and keyword methods. Numeric and text attribute filters can restrict results. Indexes can be deployed to public or private endpoints, including Private Service Connect, which provides private access from multiple user VPC networks. Documented integrations include RAG Engine, Cloud Storage, Cloud Run, TensorFlow Recommenders, and LlamaIndex. Google documents Python and Java clients, a Python SDK, and REST workflows. Security controls include VPC Service Controls and customer-managed encryption keys. Listed uses include retrieval-augmented generation, chatbots, recommendations, and multimodal search. Pricing is usage based: serving uses node-hour charges, with separate build, update, and streaming charges. Build and update data costs $3.00/GiB; streaming inserts cost $0.45/GiB.