Agentic AI

Agentic AI is a platform for building and deploying AI agents that run directly in your Postgres database. It provides an agent UI, model serving, and managed orchestration for teams that want to build RAG applications without managing AI infrastructure separately.

It enables you to store, index, and search complex data like text or images by transforming them into mathematical coordinates, powering Retrieval-Augmented Generation (RAG) and semantic search applications directly inside your Postgres database.

AIDB

AIDB acts as the orchestrator of your AI workflows. It automates the complex backend tasks required to make your data AI-ready:

• In-Database LLM integration: Connect directly to OpenAI, Azure, Google Cloud Storage, AWS S3, or local models using SQL.

• AI data preparation: Automatically transform table data into vector embeddings.

• Semantic management: No more glue code, you can manage your RAG workflows with standard SQL commands.

For more information, see AIDB docs.

Vector Plus

EDB Vector Plus is a Postgres extension that adds the ivfplus vector index type for faster, lower-footprint vector search at scale. It works alongside pgvector, using the same vector type.

Key capabilities:

• Hierarchical IVF clustering: Search large vector datasets with higher query throughput and lower latency than pgvector's ivfflat index.
• RaBitQ quantization: Reduce the CPU and memory footprint of vector search.
• Compatibility with pgvector: Build ivfplus indexes on existing vector columns. Requires pgvector 0.7.0 or later.

For more information, see Vector Plus docs.

pgvector

pgvector is an open-source Postgres extension for storing and querying vector embeddings directly in your database using standard SQL.

Key capabilities:

• Vector storage: Store embeddings alongside your existing data as a native Postgres column type.
• Similarity search: Query by cosine similarity, L2 distance, or inner product.
• HNSW and IVFFlat indexes: Scale approximate nearest-neighbor search to large datasets.

EDB Agent Governance

EDB Agent Governance is a standalone application that audits and governs how AI agents interact with your Postgres data. It connects to your HM-managed clusters or standalone Loki instances to reconstruct agent sessions from Postgres query logs.

Key capabilities:

• Reconstructing agent sessions: Inspect every SQL statement an AI agent executed, with full execution metadata.
• Auditing across multiple data sources: Connect to several HM or Loki sources at once and audit clusters across all of them from one place.
• Incremental sync: Session data is cached and synced incrementally, so audit views load quickly without re-querying the full log history on every visit.

Agent Skills

Agent Skills give AI coding agents like Claude Code built-in, validated knowledge of how AIDB, PGAA, and PGFS work, instead of the agent having to discover that information on its own.

Key capabilities:

• Local, validated knowledge: Skills are markdown files the agent reads directly, maintained by EDB alongside each product.
• Install per product or all at once: Point your agent at the edb-agent-skills repository and it installs the skill for you.