Predict Risk. Improve Flow. Deliver Value.
Turn Jira and Azure DevOps delivery data into predictive insights, early-warning signals, measurable Agile improvement, and leadership intelligence.
- Reporting effort
- Hours per week → minutes
- Risk detection
- Sprint end → day three
- Improvement
- Opinion → measured experiment
- Zero operational-data retention
- Row-level multi-tenant isolation
- Jira Cloud, Jira DC & Azure DevOps
- No per-person productivity scoring
Traditional dashboards answer one question. This platform answers seven.
- What is happening?
- Why is it happening?
- What is at risk?
- What is likely to happen next?
- What actions should the team take?
- Are our improvement actions working?
- What business impact has Agile improvement created?
Agile data is abundant. Delivery decisions are not.
Reporting consumes the week
Scrum Masters rebuild the same slides every sprint by hand, and the numbers are stale before the review starts.
Risks surface too late
Carryover, ageing work and unresolved dependencies are discovered at the sprint boundary instead of on day three.
Dependencies stay invisible
Cross-team commitments live in comments and chat threads, so nobody owns the escalation until a release slips.
Improvement is unmeasured
Retrospective actions are never baselined, so leadership cannot see whether the Agile investment changed anything.
From reactive reporting to predictive delivery
Select any stage to see exactly what happens to your data at that point.
Analyse. Deterministic analytics compute readiness, flow, blockers, dependencies and data quality before any AI narration happens.
- 01
Connect
Link Jira or Azure DevOps, or analyse an exported board file. Credentials stay server-side.
- 02
Normalize
Both platforms map into one canonical delivery model — states, sprints, estimates, priorities.
- 03
Analyse
Readiness, flow, blockers, dependencies, risk exposure and probabilistic forecasts are computed deterministically.
- 04
Act
Role-based dashboards, evidence-backed recommendations and improvement experiments that prove the outcome.
Turn Agile data into delivery decisions
AI delivery intelligence
Every finding carries observation, evidence, probable cause, recommended action and confidence. Nothing is invented.
Jira + Azure DevOps
Flexible field mapping with no hardcoded workflow assumptions, plus spreadsheet import for air-gapped teams.
Role-based dashboards
Distinct experiences for Scrum Masters, Product Owners, Engineering, Support and leadership.
Predictive delivery
Monte Carlo forecasting with P50–P95 ranges, sprint completion probability and goal confidence.
Flow intelligence
WIP, cycle and lead time percentiles, throughput, work-item age heatmaps and flow efficiency.
Continuous improvement
Turn retrospective actions into baselined experiments and measure whether they actually worked.
Leadership intelligence
Portfolio delivery confidence, release confidence, critical risk and value delivered — without the ticket noise.
Dependency intelligence
Cross-team dependency radar with owners, needed-by dates, risk level and sprint impact.
One data model. Six audiences.
Scrum Master / Delivery
Sprint Command Center, readiness, risk radar, blockers, flow, forecast, coach.
Product Owner
Backlog health, goal confidence, scope change, release readiness, value delivered.
Engineering Manager
Delivery health, defects, dependencies, quality trend, DORA where available.
Support Manager
Incidents, SLA compliance, ageing, resolution time, repeat issues, RCA trends.
Executive / Leadership
Portfolio confidence, sprint goal success, critical risks, business value, AI summary.
Platform / Org Admin
Tenants, users, teams, integrations, thresholds, privacy mode and audit history.
Enterprise-grade by construction
- Multi-tenant isolation enforced by row-level security on every table
- Secrets, tokens and PATs are held server-side and never reach the browser
- Operational work-item data is analysed in memory and never persisted
- Role-based access control with a full audit trail of privileged actions
- The delivery system is evaluated — never individual people
Responsible AI
No individual developer rankings, productivity scores or per-person velocity. Analysis targets flow, process, dependencies, quality and planning — never people.
Read the security modelThe questions procurement asks first
From Scrum ceremonies to measurable business impact
Start a pilot with your own board, or walk through the platform with a guided demo tenant. No operational data is retained either way.