A live, continuously updated map of your entire cloud estate. Resources, dependencies, ownership, cost, and the decision traces behind every change. No tagging required.
A Context Graph is a continuously updated, versioned representation of operational reality, with provenance and change lineage that explains how it got there. It turns fragmented cloud data into a queryable picture of what is running, what changed, who owns it, and why.
Your tools have the data. But it is fragmented across systems, stored in incompatible formats, missing the relationships that make it meaningful. When something goes wrong, the work is not fixing the problem. The work is reconstructing the context to understand it.
No single system knows what is actually running. IaC captures intent, not reality. Runtime drift, manual changes, and partial rollbacks leave your view perpetually stale.
You know what is running but not why it is there, what changed it last, or who approved the change. When incidents happen, you reconstruct the timeline manually under pressure.
Resources are provisioned by service accounts and CI pipelines. Ownership becomes implicit and contested. When something needs a decision, nobody is clearly accountable.
The Context Graph is not another inventory tool or CMDB. It is a shared representation layer that correlates signals from the systems your teams already use and produces a unified, queryable model of your cloud.
It does not replace your existing tooling. It connects what those tools know and adds what they cannot capture on their own: relationships, change lineage, and durable ownership.
Core Primitives
Oscar, our AI co-pilot, is uniquely designed to construct and interrogate the Context Graph on behalf of individuals, teams, and entire organizations. Every scan Oscar runs adds to the graph. Every question Oscar answers draws from it.
Oscar maps your cloud including resources, dependencies, and vulnerabilities by reading real signals. It builds the graph from what is actually running, not what someone labeled correctly years ago.
When an incident, resource question, or review arises, Oscar reconstructs full context on the fly. What is it, who owns it, what changed recently, what depends on it. Answers in seconds, not hours.
Every platform workflow starts with discovery. Oscar uses the Context Graph to perform that discovery automatically, so assessments, migrations, and governance workflows begin with verified facts.
Decision Trace — infrastructure-change
Most operations tools record what happened. The Context Graph also records why: who proposed a change, what evidence they had, who approved it, and what the system knew at the time of the decision.
These decision traces are not notes in a ticket. They are first-class data, linked to the resources they affected, queryable by anyone who needs to understand the current state of your systems.
Decision traces solve the institutional knowledge problem. When the engineer who made a choice leaves the team, the reasoning does not leave with them. The Context Graph preserves it, makes it searchable, and builds on it over time.
Unlike static inventories or one-time assessments, the Context Graph accumulates intelligence over time. Every workflow that runs, every decision that is made, and every incident that is resolved contributes to a richer model of your cloud.
Over months and years, the graph accumulates a rich history of how your cloud evolved: what was built, what was changed, what was decommissioned, and why. That history makes future decisions faster and safer.
With enough decision traces, the graph can surface patterns: recurring cost spikes tied to deployment cycles, dependency chains that consistently cause blast radius expansion, ownership gaps that slow incident response.
AI agents grounded in the Context Graph produce consistent, accurate outputs because they share the same model of reality. No conflicting answers, no rediscovery, no hallucinated dependencies. The graph eliminates the slop.
The Context Graph ingests signals from any system your teams use. No new tooling required. No integration project. No mandatory tagging. Oscar slots in alongside existing workflows and starts building the graph from day one.
When operational reality and change lineage are queryable in a unified model, a different class of capabilities opens up across safety, cost, governance, and AI.
Surface downstream dependencies and blast radius before a change ships. Know which services share the infrastructure you are about to touch. Promote and roll back environments as coherent versioned units, not isolated artifacts.
Connect symptoms to dependencies, ownership, and recent changes before the on-call engineer even opens their laptop. Context that previously took hours to reconstruct is available in seconds. Shorter incidents. Less middle-of-the-night heroics.
What was running in this environment at this point in time, who changed it, who approved it, and why. These questions answer themselves from the graph. Evidence collection becomes a query, not a multi-week investigation.
Multiple agents running in parallel need shared context or they produce inconsistent answers and unsafe actions. The Context Graph is the substrate that makes parallel agentic operations safe, accurate, and governed.
OpsCanvas built the Cloud Intelligence Graph as our purpose-built version of a context graph, designed specifically for the challenges of multi-cloud operations. Our co-founder Jason Turim wrote the technical paper explaining the architecture, the primitives, and why cloud environments make context graphs uniquely hard to build and uniquely valuable to operate.