Fiddler AI vs Vertex AI Vector Search

Fiddler AI provides observability and security for AI agents and predictive applications. It evaluates agents and models during development, then monitors them in production, with diagnostics spanning more than 100 built-in and custom metrics such as hallucination, toxicity, PII/PHI, drift, performance, and business KPIs. Real-time guardrails can detect risks and pause, reroute, or escalate agent actions. The platform records decisions, actions, evaluations, and policy outcomes to support audit evidence for requirements including GDPR, HIPAA, NAIC, and SR 11-7. It names LangGraph, Amazon Bedrock, and AWS Strands Agents as native framework support, and is built on OpenTelemetry standards. Deployment options include cloud SaaS, VPC, on-premises, and air-gapped environments. Fiddler says it is SOC 2 Type II certified, complies with HIPAA, and encrypts data in transit and at rest. Plans include Free at free, Developer at a price agreed with the maker billed per trace, and Enterprise with no listed price. The company was founded in 2018 and is headquartered in Palo Alto, California.

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.