QRAI
Project Risk, Controls & Forecasting Intelligence
Rigorous risk analysis, wired into the way you control your project.
The engine is the analysis you already know from other leading QRA software: Latin Hypercube Monte Carlo, joint cost and schedule confidence, correlations, cascading risks. Around that engine sits a complete project controls workflow: schedule and estimate quality checks, baseline governance, probabilistic forecasting, earned value tracked against the prediction, evidence-gated contingency drawdown, decision gates, portfolio roll-up, and closeout learning that calibrates your next project. An AI partner drafts the model, checks the schedule and tracks the actuals with you, so the loop costs far less time and effort than running it by hand.
Your Data's Safety and Integrity Are Paramount
QRAI is a closed, cloud-based system. The estimates, schedules, and risk models you entrust to us are encrypted, stored on secure servers in the United States, isolated to you alone, and fully auditable at every step.
A Closed System
Your data goes into QRAI and stays there. It is never shared, never sold, and never used to train public AI models. Access is by invitation only.
Cloud-Based, US-Hosted
All data is stored in the cloud on secure servers located in the United States, professionally managed and monitored around the clock.
Encrypted End to End
All project information is encrypted in transit and at rest. Sensitive cost, schedule, and risk data never leaves secure infrastructure unencrypted.
Backed Up and Securely Stored
Your data is hosted on hardened, professionally managed cloud infrastructure with continuous monitoring and automated backups.
Strictly Isolated
Every user's projects, estimates, and risk models are completely isolated. No one but you (and those you authorise) can ever see your data.
Fully Auditable
A complete, tamper-evident audit trail records every change, decision, and AI interaction, preserving the integrity of your analysis record.
A closed, secure home for AI. Pasting confidential estimates and schedules into open, public AI chat tools is not secure: your data can be exposed far beyond your control. Here, the AI works entirely inside your isolated workspace, with all the information specific to your project, covering costs, schedule, risk register, and simulation results, so it can correctly and specifically address your concerns without your data ever leaving secure infrastructure.
What Sets QRAI Apart
The same rigor, with less effort and cost
AI Builds the Model With You
Start with whatever you have: a guided conversation, a spreadsheet, a whiteboard photo, or a P6 / MS Project file. The AI drafts the full model (activities, costs, correlations, risks) and you review and refine it. It takes far less time than building the model by hand, and the AI never changes a number without your approval.
Practitioner-Built, Standards-Backed
QRAI picks the right AACE method for your analysis and warns you when something doesn’t add up. Rare but severe risks are routed to management reserve so they don’t distort your contingency.
Combined Methods, Directly Compared
Monte Carlo, parametric regression and expected value run side by side on the same project. See where the methods agree, understand the gaps, and fund a contingency that survives scrutiny.
Calibration & Bias Checks
The model learns from past project outcomes and benchmarks against reference-class data. Built-in bias checks catch overconfidence, anchoring and availability bias in your own estimates.
How QRAI Works
From conversation to controlled delivery in four steps
AI Interview
Describe your project in plain language, or upload whatever you have: a spreadsheet, a photo, or a P6 / MS Project file. The AI works alongside you to capture scope, costs, schedule, and risks.
Model Synthesis
QRAI drafts a fully probabilistic cost-schedule risk model with you, covering activities, distributions, correlations, and risk events. The heavy lifting is done for you, and every input stays yours to review and refine before it counts.
Monte Carlo Simulation
10,000+ Latin Hypercube iterations with integrated cost-schedule JCL, weather, resources, and cascading risks.
Decide & Track
S-curves, tornado diagrams, contingency recommendations, mitigation ROI, and closed-loop EVM tracking. AI-drafted reports are ready for your review, exported as print-ready PDF or editable Word.
Beyond the Simulation: A Project Controls Platform
QRA is the analytical core. Around it, QRAI carries the disciplines that turn analysis into control.
Project Controls
Schedule health diagnostics, estimate classification and basis-of-estimate documentation, baseline approval, and data-date re-forecasts. The quality checks that make analysis trustworthy.
Performance Measurement
Probabilistic EVM tracks actual cost and progress against prediction bands, flags trajectory drift early, and re-forecasts completion from the data date.
Forecasting & Decision Support
Confidence-level cost and completion forecasts, goal-seek scenarios, and structured decision gates with recommendations grounded in the simulation.
Reserve & Change Governance
Evidence-gated contingency drawdown, management reserve separation, change register control, and a full audit trail with electronic signatures.
How QRAI Compares
Other leading QRA software sets the bar for integrated cost–schedule risk analysis, but the analysis takes real time and effort to build. QRAI matches that core capability, cuts the modeling time and cost, then goes where desktop tools don't.
| Capability | Other Leading QRA Software | QRAIthis platform |
|---|---|---|
| Integrated cost–schedule Monte Carlo with JCL | Latin Hypercube, Spearman correlation, cascading risks, resources, weather | |
| Schedule quality diagnostics | Pre-run quality checks | Pass / Warning / Fail checks with repair guidance, built in |
| Probabilistic model construction | Manual — every activity, cost line and risk mapped by hand | AI interview or P6 / MS Project import — the AI drafts the model with you, ready for your review |
| Multi-method contingency (RP 117R-21) | Monte Carlo only | MCS, parametric (RP 42R-08) and expected-value methods run side by side and reconciled |
| Methodology governance (AACE PGD-02) | Not enforced | Context-driven method selection with consistency enforcement (RP 40R-08) |
| Calibration against real outcomes | Not available | Bayesian calibration, reference-class benchmarks (IPA / Flyvbjerg), optimism-bias uplift |
| Human-factor safeguards | Not available | Kahneman-derived cognitive-bias diagnostics on elicitation, ranking and overconfidence |
| AI / ML analytics | Not available | Live what-if surrogate, adversarial model review, run-to-run anomaly detection and causal discovery |
| Risk library & knowledge base | Standard register — bring your own risks | Curated library seeded from AACE / IPA / DOE / Flyvbjerg sources, with Delphi workshop capture |
| Reporting output | Charts & S-curves | AI-drafted narrative report you review and finalise, plus auto-generated Risk Management Plan, Procedure & QRA Methodology Guide |
| After the simulation | Stops at the run | Closed-loop probabilistic EVM with risk-based contingency drawdown governance |
| Portfolio risk | Limited portfolio features | Portfolio VaR / CVaR with cross-project contagion and optimized contingency allocation |
| Financial & lifecycle modeling | Not available | Probabilistic NPV / IRR with commodity cycles, FX and escalation, showing probability of positive NPV for FID |
| Keeping the model current | Manual re-runs | Continuous QSRA — auto re-simulates whenever the schedule changes |
| Deployment | Windows desktop | Cloud — any device, per-user data isolation, full audit trail |
Comparison based on the publicly documented capabilities of other leading QRA software as of September 2026. Those tools remain respected, mature choices for classical integrated QRA. QRAI is built for teams that want the same analytical core with less modeling time and effort: an AI partner across the workflow, enforced methodology, and calibration depth on top.
QRA Maturity Self-Assessment
AACE RP 122R-22 / PGD-02 (QRAMM)Where does your organization sit on the quantitative risk analysis maturity ladder? Per PGD-02, higher maturity means contingency is set by calibrated, empirical, hybrid methods rather than judgment alone.
Select your current level above to see how QRAI supports it and what the next step is.
How we verify
Don't take the claims above on faith — go check the machinery
Nine out of ten megaprojects overrun their budget (Flyvbjerg). A planning tool that cannot show its own verification is part of that problem. Every card below links to a live capability, not a screenshot.
The engine checks itself
Every simulation runs statistical self-tests — distribution shape, convergence, percentile math — and publishes the results beside the numbers. Failures are surfaced, not hidden.
Models are cross-validated
Surrogate what-if surfaces report leave-one-out accuracy for every predicted percentile, so you can see how much to trust a fast prediction before you use it.
The human stays in the loop — provably
Six gates between an AI suggestion and your approved model
AI drafts
Proposes distributions, checks and edits — applies nothing.
2You approve
Every input is reviewed and owned by a person before it counts.
3Debate on record
An adversarial proponent/skeptic review produces a signed verdict.
4Independent sign-off
Estimate reviews with electronic signatures (31R-03).
5Decision gate
Tolerance checks against your risk appetite (47R-11).
6Audit trail
Every change, who made it and why — exportable, signed.
What QRAI will not do
The limits, stated up front — because that is how you should judge a risk tool
Garbage in, garbage out. No tool rescues an incomplete schedule or a Class 5 estimate presented as a Class 2. QRAI audits model quality and tells you when it is poor — it cannot conjure quality that is not there.
The AI never invents project facts. If a quantity, price or probability is missing, it asks you rather than filling the gap with a plausible number.
Calibration claims require closeout data. Until your own projects have been back-tested, accuracy comparisons use published reference classes — clearly labelled as such, never passed off as your track record.
A percentile is not a promise. Contingency at P80 means an 80% confidence of funding within that envelope under the model as built. If the model omits a risk, the simulation will not know it exists.
Monte Carlo samples your inputs. The output is only as honest as the distributions, correlations and mapping you approve — which is why every input stays yours to review.
And one more: roughly one in a thousand megaprojects lands on budget, on schedule and on benefits simultaneously (Flyvbjerg). QRAI improves the odds on cost and schedule; it cannot fix a project whose business case was wrong to begin with.
Built on Industry Standards
QRAI aligns with the frameworks your stakeholders and auditors expect
One Platform, the Full Risk Lifecycle
The headline features get the attention, but every stage of the QRA workflow is built out to practitioner depth, not just the simulation.
Schedule & Estimate QC
Traffic-light diagnostics (in the style of other leading QRA software) on logic, float, density and range quality; AACE estimate classification; native P6 (.xer), MSPDI and Excel import/export.
Integrated Cost–Schedule (P+ICSRA)
NSRF correction reconciling parametric and Monte Carlo P80, PM/UC contingency governance with drawdown triggers, treatment optimization by EMV/ROI, and a qual–quant consistency gate.
AI/ML Intelligence Layer
Live what-if scenarios on a machine-learned surrogate, adversarial model review, anomaly detection on run-to-run deltas, causal discovery and ML-driven duration priors.
Risk Register & Library
Curated risk library seeded from AACE, IPA, DOE and Flyvbjerg sources, Delphi workshop capture, breakdown structures, cross-project contagion and multi-vector impacts.
Ready to put your project decisions on a probabilistic footing?
Start with the AI interview, import your existing schedule and estimate, or work through the Getting Started guide.