Tiger Eon
Complete organizational AI that automatically integrates agents with your data from Slack, GitHub, and Linear. Process data in real-time with time-series partitioning and deploy quickly with Docker.
Tiger Agents for Work
Enterprise-grade Slack-native AI agents with durable event handling, horizontal scalability, and flexible model choices. Get complete observability and integrate with specialized data sources.
MCP Server
Integrate Tiger Data directly with AI assistants like Claude Code, Cursor, and VS Code. Manage services and optimize queries through natural language with secure authentication.
pgai
Automate AI workflows in your database with embeddings, vector search, and LLM integrations. Use the vectorizer to automatically generate and sync embeddings from your data.
pgvectorscale
High-performance vector search with StreamingDiskANN indexing. Extend pgvector with optimized algorithms for billion-scale vector workloads and faster similarity search.
Vector database concepts
Understand embeddings, similarity search, and vector indexing. Learn about ANN algorithms, distance metrics, and best practices for building vector-powered applications.
LangChain integration
Build LangChain applications with Tiger Data as your vector store. Use document loaders, retrievers, and chains with pgvector and pgvectorscale for RAG applications.
LlamaIndex integration
Integrate Tiger Data with LlamaIndex for advanced data indexing and retrieval. Build context-aware AI applications with vector storage and semantic search.
Python interface
Work with vectors and embeddings using Python. Use the Timescale Vector Python library for seamless vector operations and similarity search in your Python applications.
SQL interface
Manage vectors directly with SQL. Create vector columns, perform similarity searches, and build indexes using familiar PostgreSQL syntax with pgvector extensions.