Connect

Bring Your Engineering Stack Together
Bring together repositories, issue trackers, pipelines, and operational signals into a single engineering data model.
Engineering Intelligence Platform
Oobeya connects delivery, workflow, quality, and AI-assisted development signals into one operating layer that engineering leaders can actually use.
Unified view
See repositories, boards, pipelines, incidents, and AI usage in one platform surface.
Leadership signal
Turn operational noise into reliable metrics, symptoms, and action-ready insights.
AI chat
Ask Oobeya for engineering context, emerging risks, and leadership-ready summaries across your stack.
Deployment model
Run Oobeya as fully on-premise or SaaS, depending on your governance, security, and procurement needs.
How Oobeya Works
Oobeya connects the operational data behind software delivery, transforms it into measurable indicators, and highlights where leaders should focus next.
Connect

Bring together repositories, issue trackers, pipelines, and operational signals into a single engineering data model.
Measure

Calculate DORA, flow, productivity, and quality indicators with cross-tool context instead of isolated point metrics.
Act

Surface recurring bottlenecks, risky patterns, and leadership-ready signals so teams can act on what matters most.
What Leaders Get
Oobeya is built to reduce reporting overhead, increase signal quality, and give engineering leaders a more actionable view of how delivery is really working.
Outcome 1
Track DORA, flow, and deployment behavior without stitching together reports from multiple tools.
Outcome 2
See quality signals and workflow friction together so engineering issues are easier to prioritize correctly.
Outcome 3
Understand how coding assistants affect delivery speed, review shape, and engineering quality across teams.
Outcome 4
Give leaders a unified operating view instead of raw dashboards, disconnected exports, and ad hoc slide decks.
Core Capabilities
Oobeya combines engineering metrics, workflow analysis, and actionable signals so leaders can move from reporting to better decisions.

Capability 1
Identify recurring anti-patterns, workflow friction, and signals that affect delivery quality before they become leadership surprises.

Capability 2
Track engineering throughput, review behavior, and deployment performance with the context leaders need to improve execution.

Capability 3
Understand how planning, backlog flow, and execution patterns affect delivery consistency across teams and organizations.

Capability 4
Measure delivery performance across repositories, CI/CD, and operational signals to avoid misleading single-tool reporting.

Capability 5
Understand how AI coding assistants affect engineering speed, workflow shape, and quality outcomes with leadership-level visibility.
Ready to See It in Action?
Connect your existing toolchain, surface the metrics leaders actually trust, and give teams a faster path from data to improvement.