THE OPERATING SYSTEM
FOR INTELLIGENCE.
// Ragable is more than a vector database. It is a complete runtime environment for AI agents, handling memory, state, and retrieval in a single unified layer.
Unified Memory
Forget managing embeddings and chunks manually. Ragable treats memory as a first-class primitive, automatically syncing with your data sources.
Type-Safe SDK
End-to-end type safety from your data source to your LLM context window. Catch retrieval errors at compile time, not runtime.
Global Edge
Your agents should live where your users are. Ragable replicates your index to 35+ edge regions for sub-50ms latency worldwide.
REAL-TIME DATA SYNCHRONIZATION
Traditional RAG pipelines are stale the moment they're indexed. Ragable uses a webhook-driven architecture to listen for changes in your data sources (Notion, Google Drive, Slack, GitHub) and updates your agent's memory in milliseconds.
- Incremental Sync (Only process diffs)
- Automatic Conflict Resolution
- 50+ Native Connectors
- Custom Webhook Ingestion
[10:42:01] EVENT_RX: webhook.notion.page_updated
[10:42:01] PAYLOAD: { page_id: "88a...", diff_size: "2kb" }
[10:42:01] ACTION: Computing vector diff...
[10:42:02] EMBED: Generating 4 new chunks (text-embedding-3-small)
[10:42:02] UPSERT: Writing to Shard_04 (us-east-1)
[10:42:02] REPLICATE: Propagating to Edge (eu-west, ap-northeast)
[10:42:03] SUCCESS: Memory updated in 1.4sLATENCY IS THE ENEMY OF INTELLIGENCE
Agents that feel "slow" break the illusion of intelligence. Ragable deploys your vector index to the edge, ensuring that retrieval happens as close to your user (and your inference provider) as possible.