Always-Current System Context
Dependencies, ownership, runtime signals, and change history stay connected in a live graph that updates as the system changes.
AI moves faster with trusted system context.
Copilots struggle when context is fragmented or stale. DevGrid gives engineering, security, and platform teams one live context graph so automation stays grounded in reality.
Single
context graph across humans and agents
Zero
manual context stitching for AI workflows
24/7
context refreshed from live engineering signals
AI can move quickly. It can also move on the wrong context.
Architecture knowledge lives in one tool. Ownership data in another. Dependency and risk signals in several more. Copilots infer across fragments and deliver confident answers that can miss critical system context. Without one live context graph, automation moves fast on bad data instead of reducing toil.
Here's how DevGrid fixes that
Task-Scoped Context Delivery
Deliver only the context each workflow needs, from incident triage to migration planning, so agents act with precision.
Unified Context Aggregation
Aggregate context from your engineering tools into one live graph so teams wire their AI stack once instead of plumbing each tool individually.
Works with Your AI Stack
Copilots, bots, and internal automations all draw from the same trusted context via APIs and Model Context Protocol.
Four roles. One context truth.
Each role works from the same live context graph and sees exactly what they need to make safe, fast decisions.
Technology Executive
Sees: AI adoption coverage, automation outcomes, and context quality trends across the portfolio.
Decides: Where to expand automation investment and where governance needs to tighten.
Technology Manager
Sees: Workflow bottlenecks, ownership gaps, and dependency hotspots affecting AI-assisted delivery.
Decides: Which teams and workflows are ready for broader automation.
Risk Manager
Sees: Policy boundaries, access scope, and exception patterns across agent-assisted workflows.
Decides: Where to add guardrails and how to reduce operational and compliance risk.
Engineer
Sees: Service dependencies, ownership, recent changes, and policy context in the flow of work.
Decides: What action to take next with clear blast-radius awareness.