DecisionLedger AI

    Decision Management

    Run decisions as a managed, measurable process

    Treat decisions as a managed asset, not one-off events. Standardize how choices get framed, modeled, and reviewed, then track outcomes to close the loop and improve decision quality over time.

    Structured

    Decision Process

    0

    Decision Methods

    Closed-Loop

    Outcome Tracking

    Challenges We Solve

    Common pain points that structured decision models eliminate.

    Every Decision Is Ad Hoc

    The same kinds of decisions get made differently every time, depending on who's in the room. Standardize decision framing and method so quality doesn't depend on the individual.

    No Memory of Past Decisions

    Organizations repeat the same debates because nothing is captured. Build a decision portfolio that records context, options, and rationale you can learn from.

    Assumptions Go Unchallenged

    Decisions rest on assumptions no one stress-tests. Run sensitivity and scenario analysis to see which assumptions actually move the outcome.

    Outcomes Are Never Reviewed

    Decisions get made and forgotten, with no comparison of predictions to reality. Track outcomes against forecasts to learn what actually works.

    Use Cases

    How leaders use DecisionLedger to make better decisions.

    Chief of Staff

    Uses the decision readiness assessment and trade-off analysis to standardize how the leadership team frames and compares major choices before they reach the table.

    Cut decision cycle time while improving the quality of options considered

    Strategy Lead

    Runs scenario planning and assumption sensitivity models to identify which assumptions actually drive a strategic bet, focusing debate where it matters.

    Re-prioritized analysis onto the few assumptions that moved the outcome

    Operations Director

    Maintains a decision portfolio with traceable rationale, then reviews outcomes against forecasts to learn which decision patterns consistently pay off.

    Built an institutional memory that reduced repeated debates

    Measurable Impact

    Based on platform benchmarks across early adopters.

    Decision Consistency

    Ad hoc per personStandardized process
    Repeatable quality

    Assumption Testing

    Rarely challengedSensitivity-tested
    Focus on key drivers

    Institutional Memory

    Lost after the meetingDecision portfolio
    Learn from the past

    Outcome Review

    Never measuredTracked vs forecast
    Closed-loop learning
    Platform Features

    A System of Record for Decisions

    Standardize framing, apply rigorous methods, and learn from every outcome.

    Decision Framing

    Structure options, criteria, and constraints consistently so every decision starts from a clear, shared definition.

    Method Library

    Apply the right decision science method to each choice, from weighted scoring and trade-off analysis to scenario and sensitivity modeling.

    Outcome Feedback Loop

    Track realized outcomes against predictions to measure and improve decision quality over time.

    Connects With

    Part of 150+ native integrations across CRM, marketing, finance, HR, ecommerce, and analytics

    Salesforce logoSalesforce
    HubSpot logoHubSpot
    Stripe logoStripe
    Shopify logoShopify
    Google Analytics 4 logoGoogle Analytics 4
    Workday logoWorkday
    QuickBooks logoQuickBooks
    Snowflake logoSnowflake
    Slack logoSlack
    Zendesk logoZendesk
    GitHub logoGitHub
    Meta Ads logoMeta Ads
    Mailchimp logoMailchimp
    NetSuite logoNetSuite
    Jira logoJira
    Power BI logoPower BI
    Salesforce logoSalesforce
    HubSpot logoHubSpot
    Stripe logoStripe
    Shopify logoShopify
    Google Analytics 4 logoGoogle Analytics 4
    Workday logoWorkday
    QuickBooks logoQuickBooks
    Snowflake logoSnowflake
    Slack logoSlack
    Zendesk logoZendesk
    GitHub logoGitHub
    Meta Ads logoMeta Ads
    Mailchimp logoMailchimp
    NetSuite logoNetSuite
    Jira logoJira
    Power BI logoPower BI

    Featured Models

    Pre-built decision models ready to run with your data.

    Assumption Sensitivity Model

    Identifies which assumptions most influence the outcome and how changes to them could materially alter the decision.

    oat_sensitivity_tornado

    Decision Portfolio Balance Model

    Detects over-concentration of risk across decisions. Analyzes the aggregate portfolio of active decisions to identify clustering, correlation, and concentration risks that could amplify failures. Computes Herfindahl-Hirschman Index, category and risk-level concentration, timeline clustering, risk factor correlation, and portfolio balance scoring with rebalancing recommendations.

    Risk Matrix

    Decision Readiness Assessment

    Determines whether a decision is truly ready to be made by evaluating data completeness, risk exposure, and unresolved dependencies.

    weighted_mcda_readiness

    Decision Traceability

    Decision Traceability Model - Links inputs, assumptions, approvals, overrides, and outcomes into a directed traceability graph. Scores completeness of each link, detects broken chains, identifies orphaned decisions, flags stale assumptions, and computes override-to-decision ratios for governance and audit compliance.

    graph_traceability_analysis

    Scenario Planning & Stress Testing

    Model multiple future scenarios and stress test decisions against adverse conditions. Quantifies upside, downside, and base-case outcomes with probability-weighted expected values. Computes Value at Risk (VaR), Monte Carlo confidence intervals, scenario comparison matrices, sensitivity analysis, and risk-adjusted recommendations.

    Scenario Modeling

    Strategic Option Viability Model

    Compares strategic paths with quantified upside, downside, and execution risk. Evaluates multiple strategic options through financial, operational, and risk lenses to identify the most viable path forward. Computes expected monetary value, risk-adjusted EMV, asymmetry ratios, real options value, viability composite scores, dominance analysis, breakeven probabilities, and Monte Carlo confidence intervals.

    Scenario Modeling

    Trade-off Analysis Model

    Explicitly surfaces opportunity cost between competing options. Quantifies what you gain and what you give up for each alternative using multi-criteria comparison with explicit cost-of-not-choosing analysis.

    Weighted Sum (MCDA)

    Causal Decision Intelligence

    Builds causal graphs from organizational data to distinguish correlation from causation in business metrics. Identifies true drivers of outcomes, estimates intervention effects, and prevents costly decisions based on spurious correlations.

    Bayesian Inference

    How It Works

    Three steps to structured, auditable decisions.

    1

    Frame the Decision

    Structure the choice: options, criteria, constraints, and stakeholders. Assess decision readiness before investing in analysis.

    2

    Model & Compare

    Apply the right decision method, run scenarios, and stress-test assumptions. Compare options side by side with quantified trade-offs and uncertainty.

    3

    Decide & Learn

    Record the decision and its rationale in the portfolio, then track the outcome against the forecast to improve the next decision.

    Replace Your Stack

    Could your organization explain how it makes its most important decisions, or does decision quality depend entirely on who happens to be in the room?

    ×

    Decision-by-meeting

    Outcomes that depend on who attends and who speaks loudest

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    One-off spreadsheets

    Bespoke analysis with no shared method or memory

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    Gut-feel calls

    Important decisions made without structured options or stress-tested assumptions

    ×

    Forgotten decisions

    No record of why a choice was made and no review of how it turned out

    All in one governed platform

    Start with Decision Management today

    See how DecisionLedger AI transforms your decision-making.