Context Graph

A live graph of your services, teams, concepts, and dependencies. Highly available, permissioned, and agent-ready.

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CONTEXT INFRASTRUCTURE

From raw data to agent-ready context

Agents need structured, authoritative context to perform complex actions. Roadie builds and maintains that context so your agents can focus on shipping code.

Integration-powered data store

We pull data from your production systems like GitHub, PagerDuty, Datadog, Kubernetes, and dozens more. The graph is built automatically from the tools your teams already use.

Schema and schemaless relationships

Define structured schemas for known entity types, or let schemaless connections emerge organically. Both coexist in the same graph.

Dynamic updates

The graph evolves continuously. Updates come from user input, integration syncs, and background agents that discover and maintain relationships.

Human-crafted context bundles

Package exactly the information an agent needs for a particular task into a reusable bundle. Everything from ownership and dependencies, to runbooks and API specs.

Agent-requested context

Agents request context on-demand; Roadie assembles it. Context can be ephemeral or permanent. Agents get structured data, not raw firehose.

Agent-suggested updates

When an agent discovers new information like a missing dependency, an outdated owner or an incorrect query format, it can suggest changes for human review or automatic merge.
HOW IT WORKS

The context lifecycle

From integration to agent consumption, context flows through a continuous loop of collection, relationship building, and refinement.

01

Integrations pull data

Connect your tools. We sync repos, services, incidents, deployments, ownership, and documentation into the data store. Everything is indexed and queryable.

02

Graph builds relationships

We link services to teams, APIs to consumers, runbooks to incidents. Schema-defined and schemaless connections coexist. Background agents continuously refine the graph.

03

Context bundles are assembled

When an agent needs context, we assemble the relevant slice of the graph. Humans can pre-define bundles or agents can request exactly what they need.

04

Agents consume and contribute

Your agents query the context store via MCP. As they work, they can suggest updates. Anything from new relationships, corrected metadata, to discovered dependencies. The store gets smarter over time.