Delivery intelligence · Jira

ClearView

Jira contains plenty of evidence about how work is moving. ClearView turns it into decisions: what is drifting, what is blocked and whether the plan still deserves confidence.

Product directionDelivery modelInformation designAI-assisted build

ClearView landing screen showing delivery intelligence dashboards

The problem

The evidence was there. The clarity was not.

Delivery reporting had become a small industry. Data was gathered by hand, different views produced different stories and the most useful signals were buried in Jira.

ClearView starts with the decisions people need to make, then works backwards to the evidence. It brings commitment, scope change, ageing work and delivery history into one view without asking every leader to become a Jira analyst.

I conceived and built the application using user-centred design and AI-assisted development. It made overcommitment and weak planning assumptions visible early enough to discuss, contributing to a wider change in planning and delivery practice.

50% → 80%+Delivery against commitment, alongside wider changes to planning and team practice

One viewThe same evidence for team and leadership conversations

Decisions firstUseful questions before impressive-looking metrics

Product views

Three views. One argument.

The product is deliberately not a wall of metrics. Each view answers a question: what did we expect, what is moving now and what does the recent history suggest? The detail is there, but the first job is orientation.

ClearView product overview — Entry point: begin with the delivery question, not the dashboard.

ClearView Scrum delivery flow dashboard — Delivery flow: see the shape and movement of current work.

ClearView Kanban delivery history dashboard — Delivery history: put the current picture in context.

Next case study: Alignment Lab