Weavable

Getting an AI agent to work across HubSpot, Jira, and Slack usually means feeding it separate snapshots from each one.

Weavable is a persistent context layer for AI agents that connects those business tools into a single graph, so the agent can reason across them.

Standard Model Context Protocol (MCP) connections return point-in-time data.

Weavable instead keeps a continuous changelog and resolves the same entity across platforms, for example a customer who appears in a CRM, a ticket, and a chat thread.

Agents receive data that has already been processed, scoped, and ranked.

That means lower token usage and more deterministic outputs in real workflows.

Weavable is meant for developers building agents who find raw MCP access too shallow or too noisy.