Engineering intelligence platform
Engineering intelligence that shows its work.
ShipReady Metrics reads the systems your engineering organization already runs and turns them into software engineering metrics you can defend: delivery, technical debt, security, lifecycle risk, modernization and cloud health. Every number traces to a connected source. Anything it cannot measure reads not measured.
The question engineering intelligence should answer
Most engineering dashboards answer how fast a team is moving this sprint. That matters to the people running the sprint. A board, an acquirer’s diligence team or an enterprise buyer asks something harder: how mature is this engineering organization, and can you prove it? They will pick a figure and ask where it came from. A number that was modeled, estimated or quietly defaulted to zero does not survive that question.
ShipReady is built for that second audience. It connects read-only to source control, pipelines, scanners and cloud accounts, scores each domain from the evidence it finds, and keeps the source attached to every result. The same connections feed an evidence trail an outsider can re-check, so the metric and its proof live in one place.
The software engineering metrics ShipReady measures
Six engineering scores make up the Engineering Excellence family. Each one names what it reads and what happens when the evidence is missing. The full signal list is on What we measure.
Three AI scores sit alongside them: AI Readiness, AI ROI and Agent Health. AI ROI reads not measured until adoption is metered, and Agent Health waits on agent telemetry. All nine domains roll into one ShipReady Score, translated into a dollar Value at Stake with measured cost and modeled risk kept apart and never added together.
Measured, modeled or not measured
The defining rule is simple. A figure appears only when it is measured from your systems. A domain with no connected source is left out of the composite instead of being guessed, and a scanner that is switched off is reported as a blind spot rather than a clean result. Confidence is tied to coverage: a score resting on a single source is capped at medium confidence, and thin data withholds the letter grade entirely.
Where ShipReady does model something, such as the risk side of Value at Stake, it shows the range and the assumptions you can see and change. The methodology documents every domain, its direction and its data source.
Where workflow tools lead, honestly
Engineering-intelligence and engineering-management tools are built to improve team workflow and plan engineering investment, and they lead on that job. ShipReady tracks the review and verification segment of pull-request cycle time, offers review analytics and a short AI-collaboration pulse. It does not send real-time review nudges, does not report engineering-time allocation or R&D capitalization, does not track OKRs, and does not rank individual developers. The comparisons say so row by row:
- Where ShipReady fits — category-level matrix versus engineering-intelligence and GRC-automation tools.
- Jellyfish alternatives and LinearB alternatives — evaluation checklists, not attack pages.
- ShipReady vs GitHub’s own security features — what GitHub already does, and what ShipReady reads from it.
Who it is for
CTOs and VPs of Engineering who report to a board, founders preparing for enterprise security reviews or diligence, and engineering leaders who need delivery, security and debt on one honest surface instead of three dashboards. If your only goal is tuning sprint flow, a workflow tool is the better fit. If someone outside engineering has to rely on the answer, start here.
Learn the metrics
Frequently asked questions
- What is an engineering intelligence platform?
- It is software that reads the systems your engineering organization already runs, such as source control, pipelines, scanners and cloud accounts, and turns that activity into metrics leaders can act on. Tools differ in who the metrics are for: some coach team workflow, others plan engineering investment, and ShipReady produces evidence a board, buyer or auditor can trace to its source.
- Which software engineering metrics does ShipReady measure?
- Six engineering scores: Delivery Health (including deployment frequency, lead time for changes and change failure rate), Technical Debt, Security Readiness, Lifecycle Risk, IT Modernization and Cloud Health. Alongside them sit three AI scores: AI Readiness, AI ROI and Agent Health. All nine roll into one ShipReady Score.
- What happens when a metric cannot be measured?
- It reads not measured and is left out of the composite. ShipReady never fills a gap with a benchmark, a model or a zero, and every score states how much of your estate it covers.
- Does ShipReady rank individual developers?
- No, by design. Its unit is the engineering estate and its repositories, not the person. There is no per-developer productivity ranking.
- Is ShipReady a replacement for workflow tools like pull-request coaching or allocation planning?
- No. It tracks the review and verification part of cycle time and review analytics, but it has no real-time review nudges and no engineering-time allocation or R&D capitalization reporting. If those are the job, use a tool built for them.