Mentat Desk structures every decision as a ledger of evidence, competing simulations, and a reasoning trace you can audit. The AI Mentat surfaces hidden assumptions, generates adversarial scenarios, and retrieves patterns from every past decision your team has made.
Free plan available · No credit card required
Live from this instance
Active projects
3 workspaces
Strategic directions
7 arcs
Open decisions
12 questions
Data source
LIVE
AI features
4 active
Simulation modes
4 types
Active projects
3 workspaces
Strategic directions
7 arcs
Open decisions
12 questions
Data source
LIVE
AI features
4 active
Simulation modes
4 types
Why Mentat Desk
From noise to evidence
Every metric, research finding, constraint, and assumption gets classified and linked. Before you model anything, your Intel ledger tells you exactly what you know and what you're betting on.
Scenarios with explicit confidence
Competing hypotheses become concrete forward projections with confidence-adjusted expected values. The AI Mentat computes the gap — you make the call.
Decisions that survive scrutiny
Publish a signed brief with full reasoning trace. Board members, investors, and team leads can follow the logic — not just read the conclusion.
Step 1 — Capture and classify evidence
Paste in data points, research notes, customer calls, and constraints. Ask Mentat drafts signal templates tuned to the current key choice — every template is editable before you save.
Mid-market NRR: 110% vs Enterprise NRR: 95%
FactLost $150K ACV deal — competitor had enterprise integrations
RiskGartner: 75% of enterprise buyers require SOC2
Constraint3 AEs (mid-market trained), 1 SE (entry-level)
ConstraintBurn rate: 14 months runway at current pace
FactEnterprise-first
$2.5M
$1.1M EV
Hybrid motion
Recommended$2.2M
$1.54M EV
Mid-market only
$2.1M
$1.79M EV
Mentat insight: Hybrid motion has 25pp higher confidence; expected value $1.54M vs $1.13M. Recommend Hybrid.
Step 2 — Model simulations
Baseline + unlimited what-if branches. Each simulation carries a hypothesis statement, confidence level, and a chain of reasoning you can challenge step by step.
Step 3 — Audit reasoning traces
Instead of taking a recommendation on faith, step through the exact inference chain. Each step is tagged as fact, assumption, calculation, or model-derived — so you can challenge the logic before you commit.
Hiring model
2 AEs × 4 deals/qtr × $40K ACV = +$1.28M ARR
Retention model
Enterprise NRR 95% + feature investment → 105%
Concentration model
Enterprise 60% of customers → 75% of ARR; concentration → 35%
Confidence synthesis
Hiring 50% risky + feature 30% + market 20% → 45%
Conclusion: ARR $2.5M at 45% confidence
Decision Question
Recommended: Hybrid Motion
Hybrid motion balances enterprise growth with mid-market retention. Expected value outperforms enterprise-first by $440K.
Key assumptions
4 tracked
Identified risks
3 flagged
Contingency plan
Defined
Probability statement
72% · 5 fields
Step 4 — Publish and share
Package your key choice into a polished brief with a signed, expiring share link. Board members can explore the full reasoning trace without logging in.
AI Mentat — four modes
The AI Mentat engages at four distinct points in your decision process — each mode produces structured output that directly affects your Verdict.
Phase 1
Probability Statement
Reads the scenario's reasoning trace and linked assumptions to generate a structured 3-part summary: a one-sentence conclusion, a confidence derivation, and the single reversal assumption that would flip the outcome.
70%
confidence
The hybrid motion will grow ARR to $2.2M within 18 months with mid-market NRR sustained above 108%.
Derived from 4 high-confidence evidence signals; enterprise ramp assumption remains the primary risk ceiling.
Reversal Assumption
If the enterprise AE fails to ramp within 120 days, ARR drops $300K and the Hybrid scenario collapses to Mid-market parity.
Mentat advises: Watch AE ramp velocity as your primary leading indicator. If the AE closes one deal in 90 days, upgrade to Enterprise-first Simulation.
Phase 2
Adversarial Simulation
The Devil's Advocate mode identifies the 2–3 highest-volatility assumptions in any scenario and simultaneously inverts them to their worst-case values. The gap between source and adversarial is your true downside exposure.
Inverted Assumptions
AE ramp: 90 days → 180 days (historical enterprise failure rate: 60%)
Mid-market NRR: 110% → 98% (attentional dilution from enterprise pivot)
Enterprise NRR: 95% → 88% (premature entry without SOC2)
Adversarial ARR forecast
$1.4M at 22% conf
Mentat advises: The $800K gap is your true downside exposure. Add a contingency gate: "If AE has no closed deal by day 90, revert to mid-market focus."
Phase 3
Blank Slate Simulation
Reads only the decision title and objective — deliberately ignoring all Intel. Generates 3 first-principles hypotheses an outside advisor would consider, then scores each for novelty against your existing scenarios.
Generated without reading your Intel. The Mentat reasoned from title and objective only — no assumptions inherited.
Partnership-led growth
Novel · 94%White-label partnerships with two system integrators generates $800K ARR without direct AE hires.
PLG enterprise trial
Novel · 71%Product-led growth with a 30-day enterprise trial converts 18% of trials to $35K ACV deals.
Vertical specialisation
Partial · 38%Healthcare vertical with HIPAA compliance unlocks a 2x ACV premium in a segment competitors ignore.
Phase 4
The Vault
Searches all completed, outcome-indexed decisions across every project using semantic similarity. Synthesises them into calibration warnings — which assumptions your organisation historically over-estimates, and by how much.
In 3 of 4 similar enterprise hiring decisions, teams over-estimated AE ramp speed by 35% on average. Two of those decisions ended with ARR missing by 20%+.
Assumption Warnings
AE ramp timeline
over-estimated ~35% (3 decisions)Use 120-day ramp default, not 90-day
Enterprise NRR uplift
over-estimated ~12% (2 decisions)Reduce NRR uplift assumption by 8pp
Suggested confidence adjustment
−15pp
Vault advises: Reduce Hybrid scenario confidence from 70% to 55% before publishing a Verdict. Historical pattern is consistently over-optimistic on ramp speed.
The full journey
Capture Intel
Classify every signal as fact, assumption, or constraint.
Form hypotheses
Competing explanations with hidden assumption extraction.
Build simulations
Baseline + what-ifs with confidence-adjusted expected value.
Run AI Mentat
Probability Statement, Devil's Advocate, Blank Slate, Vault.
Publish Verdict
Signed brief. Frozen assumption ledger. Board-ready.
Record outcome
Forecast variance fed into Memory for next decision.
Full documentation
User Guide & Workflows
Step-by-step walkthroughs from first Question to published Verdict, with real-world examples for every workflow.
In Frank Herbert's Dune, Mentats are the ultimate decision-makers — humans trained in structured reasoning, computation, and strategic foresight. They don't guess. They think.
Mentat Desk brings that discipline to your organisation. Every decision you capture becomes part of an evolving library that makes your team smarter, faster, and more decisive with every choice.
Think clearly
Signal classification and assumption tracking eliminate hidden bets and confirmation bias.
Reason systematically
Auditable step-by-step traces let you challenge logic before committing, not after.
Learn perpetually
Outcome reviews feed The Vault, improving calibration guidance for every future decision.
Step 6 — Learn and improve
After execution, run an outcome review. Mentat computes forecast accuracy, surfaces which assumptions were wrong, and stores the lessons in your decision memory. The Vault uses these outcomes to calibrate guidance for similar future decisions.
Outcome Review — Enterprise GTM Pivot
Vault update: AE ramp assumption updated to 120-day default. Will surface on next enterprise hiring decision.
Pricing
Start free. Scale when you need. No lock-in.
Estimated monthly
$0
$0 / year
Best for teams proving strategic rigour.
Free plan. No credit card. One decision is all it takes to see the difference structured reasoning makes.