AACE 132R-23 Level 4 · CPM · TOC · Monte Carlo

Real schedule-risk math. Modern UX. An AI copilot that reasons over your actual schedule.

Legacy risk tools cost $10K+/seat and look like 2005. Modern PM tools are beautiful but can’t compute a P80 date. CritPath AI is the only platform that does both — built for the uncertainty of R&D programs.

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Built for Biotech program leaders · Deep-tech founders / CTOs · Federally-funded PIs · Grant program managers

The gap no one else fills

Risk-math depth →Modern, self-serve UX →
The empty quadrant

Legacy risk tools

Primavera · Deltek · Pertmaster — ~$10K+/seat, Windows desktop

Spreadsheets & trackers

manual Gantts — no probabilistic math

Generic PM

Monday · Asana · Smartsheet · Linear — $7–25/mo

CritPath AI

Real risk math + modern UX + a schedule-aware copilot

$10/user/mo · all features

Schedule-risk tools have the math but not the UX. Generic PM tools have the UX but not the math. CritPath AI is the only one in both.

How we compare

CapabilityCritPath AIGeneric PMLegacy risk tools
Monte Carlo + CCPM risk math✓—✓
Risk analysis & monitoring✓—✓
Decision gates + retroactive reschedule✓——
Project analysis & reporting (EVM)✓partialpartial
Schedule-aware AI copilot✓partial—
AI employees (configurable agents)✓——
Modern web UX, self-serve✓✓—
R&D-native (biotech / deep-tech / federal)✓——
AI project charter → drives the schedule + copilot✓——
Speed-vs-cost tradeoff analysis✓—partial
AI-employee workspace (watch agents work)✓——
Integrations (GitHub; Slack / Notion / Discord soon)✓✓—
Entry price / user / mo$10$7–$25~$10K+/seat

The AI-employee workspace and GitHub integration activate at general availability; Slack, Notion, and Discord integrations are on the near-term roadmap — in active development.

The engine R&D actually needs

Built from the first line for the uncertainty and decision density of research programs — not retrofitted from construction or IT delivery.

Critical Path Method

Full CPM engine — four dependency types, lag, float, near-critical detection, forward/backward pass across your entire dependency graph.

Theory of Constraints

Find the drum, size CCPM project & feeding buffers, track consumption on a fever chart, and visualize Drum-Buffer-Rope live.

Monte Carlo Simulation

PERT-Beta sampling, risk-event injection, criticality index, and tornado-chart sensitivity across 10,000+ vectorized iterations.

Decision Gates

Go / No-Go / Pivot / Defer as first-class schedule objects, with retroactive rescheduling that propagates a gate decision through the whole plan.

AI Copilot

A Claude + Gemini copilot that reasons over your actual CPM/TOC/Monte Carlo graph — it tells you which task drives your P80 slip, not generic advice.

AACE 132R-23 Level 4

Regulatory-grade risk-driven scheduling with audit trails — built for pharma IND programs and federally-funded R&D, with 21 CFR Part 11 on the Enterprise roadmap.

Rigor where it matters. AI where it helps.

CritPath AI implements the full AACE International RP 132R-23 Level 4 risk-driven scheduling model, with a Claude + Gemini copilot that reasons over your schedule — not a generic chatbot pinned on top.

  • ✓Decision gates with retroactive rescheduling propagation — no PMO tool ships this
  • ✓CPM + TOC/DBR + Monte Carlo in one product — incumbents have at most one
  • ✓AI copilot grounded in the real dependency graph, not a chatbot pinned on top
  • ✓WSJF + Cost of Delay integrated with Monte Carlo and CPM
  • ✓TOC Thinking Tools — Goal Trees, Problem Trees, Conflict Clouds — from the schedule
  • ✓Claude + Gemini, no OpenAI lock-in

Pricing

One simple seat — $10/user/month, every feature. Less than a fraction of a single legacy schedule-risk license.

Pro

Most teams

$10 /user/mo

Everything: CPM, TOC/DBR, Monte Carlo, decision gates, WSJF, portfolio dashboard, 2FA/MFA, audit log, API. Unlimited projects.

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Enterprise

Custom

On-prem, SOC 2, SAML, HIPAA BAA, dedicated CSM; 21 CFR Part 11 on the roadmap.

Talk to us

Build your own organization of AI employees — configurable agents with custom skill sets that work alongside your team to boost productivity. They’re billed separately, by usage — your actual LLM token cost plus a platform margin, metered by the hour. You only pay for the AI work you run.

Model your next milestone.

Spin up a project, import your task list, and run a Monte Carlo simulation in under five minutes.

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