A modern Barbecana Full Monte alternative

Full Monte earns its reputation. Its Monte Carlo engine is mature and well-respected among project-controls professionals, with proper merge-bias treatment (so parallel paths converging on a milestone are not under-risked), criticality and sensitivity outputs, and methods aligned to AACE Recommended Practice 57R-09. At roughly $1,195 per seat perpetual plus about $299 a year, it is dramatically cheaper than legacy desktop incumbents like Primavera Risk Analysis or quote-only tools such as Deltek Acumen and Safran Risk.

If your world is already MS Project or P6, and you have an analyst whose job is to run risk simulations, Full Monte is a sensible, low-cost choice. We are not going to pretend otherwise — these are real strengths, and its core simulation depth is battle-tested.

Full Monte is an add-in, not a platform. It runs inside Microsoft Project or P6, so you need the host application license underneath it — the per-seat cost of Full Monte is on top of the cost of MS Project or P6. It is also Monte-Carlo-only: there is no Critical Chain / Theory of Constraints scheduling, no Drum-Buffer-Rope or fever chart, no decision gates with retroactive rescheduling, and no WSJF or Cost of Delay economic prioritization.

It also has no AI. There is no copilot to explain which task is driving your P80 slip, what a go/no-go gate decision does downstream, or how a CMC vendor delay re-cascades the plan. And like most project-controls tools, it is built to be driven by one analyst — the simulation lives on a desktop, not in a shared workspace the whole program team can read.

CritPath AI delivers the Monte Carlo analysis Full Monte is known for — PERT-Beta sampling, explicit risk-event injection, criticality index, tornado sensitivity, P50/P80/P90 dates, and optional duration correlation — but as one capability inside a complete method stack. The same model also runs CPM with four dependency types, lag, float and near-critical analysis; Critical Chain and Theory of Constraints with Drum-Buffer-Rope buffers and a live fever chart; decision gates (Go / No-Go / Pivot / Defer) that retroactively reschedule the plan; WSJF and Cost of Delay; EVM; and AACE RP 132R-23 Level 4 risk-driven scheduling with audit trails.

On top of that engine sits a Claude + Gemini AI copilot grounded in your actual dependency graph — not a chatbot pinned over a work list. It reasons over the real CPM/TOC/Monte Carlo network to explain why a date moved and what a schedule change does downstream. Because it is a multi-tenant web app, the whole R&D program team works in it, rather than waiting on one analyst's desktop simulation.

Per seat, Full Monte's amortized cost (~$33/mo) can look cheaper than CritPath's $10/user/month — until you account for the rest of the picture. Full Monte's price assumes you already own an MS Project or P6 license per analyst, and that you have an analyst to operate it; CritPath needs neither. CritPath's $10/user/month includes every standard feature and unlimited projects, with AI employee usage billed separately by metered consumption (actual LLM token cost plus a platform margin), so you only pay for the AI you run.

Net: Full Monte is a low-cost way to add Monte Carlo to an existing desktop scheduling stack for one specialist. CritPath is a low-cost way to give an entire R&D program team Monte Carlo plus CCPM, TOC, gates, WSJF and an AI copilot — without a host license. Enterprise terms (SSO, on-prem, SOC 2, HIPAA BAA) are on the roadmap as a custom tier — not yet shipped today.