Project cockpit
One screen with budget, schedule, resource, procurement and risk health — plus a readiness check that tells you whether the project is ready for steering.
MVP in validation — demo environment available
Project control built on evidence, not hand-assembled reports.
ControlRoom connects budget, costs, earned value, risks and decisions in one operating cockpit. Every number traces back to its source; what is missing stays declared, not hidden. The guided demo tests fit against your real context.
Working modules
What ControlRoom does today.
Not a roadmap promise: these modules already work end-to-end in the demo environment, on a real backend with real data.
Budget and cost control
Budget lines, actual costs, commitments and forecasts in one economic panel, with total exposure and variance against Estimate at Completion.
Earned Value Management
BAC, PV, EV, AC, CPI, SPI, EAC and VAC computed deterministically from your data: same input, same result, always verifiable.
Risks, issues and decisions
A log with owners, impacts and rationale. Relevant signals — an open high risk, a stalled decision — surface directly in the cockpit.
Portfolio dashboard
Cross-project rollup with weighted CPI and SPI, a ranking of projects needing attention and explicit reporting of missing data.
Reports and snapshots
Immutable project and portfolio snapshots, PDF export, email delivery and side-by-side comparison of two reports to see how KPIs move.
From project to portfolio
The same discipline, across every project.
The portfolio view introduces no new numbers: it aggregates facts already verified in each project cockpit. If a project is missing procurement or progress data, the dashboard says so — instead of producing an average that looks complete but is not.
- Ranking of projects needing attention, with the reasons made explicit.
- CPI and SPI weighted by budget, not simple averages.
- An always-visible “data gaps” section: what is missing is part of the picture.
Governed AI
AI interprets the numbers. And shows its evidence.
ControlRoom’s AI reports start from immutable backend-calculated snapshots, not free text. Every statement must cite the evidence it derives from; strict validation rejects numbers that do not exist in the source data; every generation is audited. The default engine is deterministic, and the external LLM provider is an explicit choice, not a default.
It is the same principle I apply in my AI and governance consulting: a verifiable data foundation first, assisted interpretation second.
Product principles
A cockpit that is readable, verifiable and useful in decisions.
Connected sources
Every signal traces back to the record it comes from: a budget line, a cost entry, a risk, a decision.
Explicit limits
Missing data and uncertainty remain visible. Where there is no data, the cockpit says “unknown” instead of inventing an average.
Operating decisions
The view is organized around what needs attention, ownership or a decision — not around producing yet another report.
ControlRoom
Where we are: a working MVP, validation in progress.
The modules described on this page can already be demonstrated end-to-end. Integrations with existing tools, enterprise identity (SSO, MFA) and richer document workflows are still to be built. The public roadmap is honest about what is available, what is in validation and what comes next.
Read the roadmapControlRoom applies the AI Process Intelligence method to project governance. If you need a process assessment before any software, see how I work or get in touch.
Want to test the fit on your project?
Request a free demo prepared on your context: projects, data sources, reviews. No price and no outcome is promised before validation.
Request free demo access