Tools that audit
Test whether the evidence behind a claim holds up.
92 of 388 tools.
Audit agentic action control integrity
Audit operational AI-agent actions from bounded least-privilege permission scope through independently tested authorization, approval, sandbox, monitoring, rollback or compensation, and kill-switch controls, counting unique value exposure once.
Audit aggregate metric reversal
Detect Simpson's-paradox-style sign reversals between an executive aggregate relationship and its weighted within-stratum fixed-effect relationship, with whole-stratum bootstrap uncertainty and practical-magnitude gates.
Audit AI capability fallback integrity
Prove that every aggregate capability required when AI is unavailable has a current approved runbook and a sufficiently large, timely, successful, independently observed exercise conducted with AI actually disabled.
Audit AI code change evidence integrity
Prove that aggregate AI-assisted coding evidence comes from prospectively registered, nonoverlapping treatment/control studies with immutable assignment, configuration, trace and mature-outcome denominators before anyone estimates an effect.
Audit AI configuration release integrity
Audit that the exact immutable AI configuration bundle evaluated and approved is the bundle exposed in every staged rollout, with consecutive parent lineage, complete blast-radius declaration, effective runtime controls, monotone traffic and a tested prior-version rollback path.
Audit AI data rights provenance integrity
Audit every AI training, fine-tuning, retrieval, evaluation, logging and persisted-output use against an immutable rights grant and the complete derivative lineage, including time, revocation, deletion, purpose, jurisdiction, consent, derivative and evidence gates.
Audit AI evaluation contamination integrity
Audit frozen AI evaluation suites for temporal or answer leakage, model-version mismatch, incomplete pre-label predictions, weak label provenance, missing subgroup support, cross-suite case reuse and near-duplicate content components before evaluation scores are trusted.
Audit AI inference cost allocation integrity
Reconcile provider AI invoices bottom-up to workload and route usage, price terms, cached requests, retries, fixed charges and credits without combining currencies or silently allocating unexplained spend.
Audit AI knowledge grounding integrity
Audit the complete AI knowledge supply chain from immutable source versions through indexed chunks and effective access policy to retrieved evidence, claim-level citations and honestly mature grounding outcomes, without treating unresolved answers as failures.
Audit AI model routing evidence integrity
Audit every live AI-model route against current version-matched local evaluation, uncontaminated temporal holdout, pricing freshness, residency, retention, reliability and genuinely independent provider fallback evidence, counting each workload's value at risk once.
Audit AI output IP provenance integrity
Audit aggregate AI outputs against the exact model and provider terms effective at generation, pre-commercialization similarity evidence, counsel-owned ownership/use rules, human review and any claimed indemnity coverage.
Audit AI privacy budget integrity
Recompute each aggregate AI privacy account from its immutable release ledger using additive Rényi differential-privacy composition and target-delta conversion, while auditing order grids, sequence, hashes, accounting periods, purpose, review approval, evidence and claimed-versus-actual budget spend.
Audit AI regulatory obligation evidence integrity
Audit point-in-time AI-system classification, counsel-supplied obligation applicability, control evidence and incident-reporting clocks without pretending to infer law.
Audit AI routing experiment integrity
Audit prospectively registered AI-route experiments at the randomization-unit/period/route grain, reconciling logged propensities, allocation fidelity, pre-assignment balance, crossover, outcome maturity, simultaneous-experiment overlap and unique value at risk before any causal effect is reported.
Audit AI workflow trace value integrity
Audit every AI workflow execution from root trace through model, tool, cache, review and control steps to one mature business outcome, reconciling parent lineage, retries, wall-clock latency, direct cost and uniquely attributed net value while retaining unfinished work.
Audit analytical specification multiverse
Audit whether an analytical conclusion survives a prespecified multiverse of admissible windows, cohorts, metrics, and models using aligned bootstrap draws, a weighted specification curve, practical-effect support gates, and descriptive choice-influence diagnostics.
Audit analytics challenger independence
Audit whether an analytical challenger supplies genuinely independent error information: use paired temporal moving-block bootstrap bounds on error correlation, incumbent-failure catch rate and common-mode joint failure, with simultaneous Bonferroni control across every screened challenger and explicit evidence gates.
Audit analytics function calibration readiness
Gate analytical functions on paired out-of-time decision loss against a frozen baseline using temporal moving-block bootstrap, autocorrelation- and weight-adjusted effective sample size, evidence coverage, lower confidence bounds, improvement probability and recent degradation rather than declaring a model calibrated from training fit.
Audit analytics transportability
Audit whether locally calibrated analytical functions retain decision-loss improvement across target-similar operating environments using similarity-weighted random-effects meta-analysis, between-environment variance, I-squared, sign consistency and a conservative target prediction interval.
Audit attention fragmentation evidence integrity
Audit consented point-in-time contributor identity, availability, privacy-safe calendar metadata and work-session lineage before reporting aggregate meeting load, protected focus blocks or cross-project switching.
Audit attrition risk prediction integrity
Audit an attrition model's complete eligible cohort, point-in-time features, supportive-use governance, intervention-contaminated labels, competing outcomes, calibration, false positives and authorized subgroup error before any person-level use.
Audit benefit double counting
Reconcile business-case benefit claims to unique economic source pools and allocation fractions, exposing overallocated sources and claim-level mismatches before portfolio value is aggregated.
Audit budget constraint binding
Audit whether a claimed budget constraint genuinely blocks value after dependency-feasible portfolio reallocation, separating current-plan inefficiency from scarcity with scenario CVaR and a discrete budget shadow price.
Audit cash flow timing consistency
Audit whether economic-event and cash-settlement timing obey governed lag rules across coherent scenarios, quantify the resulting NPV distortion, reconstruct scenario liquidity paths, and separate timing exceptions from liquidity-tail exposure without treating exceptions as wrongdoing.
Audit causal claim negative controls
Gate a causal effect claim using prespecified negative outcome/exposure controls, Benjamini-Hochberg multiplicity control, and an omnibus chi-square falsification test.
Audit CI pipeline evidence integrity
Audit the complete point-in-time change-to-pipeline-to-job-to-rerun cohort, exposing missing CI, orphan records, future leakage, inconsistent required-job outcomes, incomplete provider evidence and same-configuration fail-then-pass flake proxies without scoring people.
Audit cluster randomization integrity
Audit cluster-randomized experiments for practical baseline imbalance and differential outcome observation, with cluster-size-weighted standardized differences and assignment permutation diagnostics.
Audit code knowledge concentration integrity
Audit file, module, service, or repository knowledge concentration from point-in-time substantive changes, reviews, incident response and documentation using identity-confidence filtering, recency decay, Bayesian ownership uncertainty, entropy-effective owners, HHI and leave-top-owner-out resilience—without turning contribution evidence into a person-performance score.
Audit commercial resilience claim integrity
Audit resilience ROI claims against a unique commercial-source to technical-component graph: recompute each action's avoided loss under joint failure scenarios, cap support at graph-derived value, detect duplicate effects, probability drift and weak evidence, and prevent overlapping component benefits from being sold twice.
Audit commercial technical commitment integrity
Audit signed commercial promises against explicitly allocated technical scope, dependency order, funded capacity, acceptance criteria and evidence; expose orphan scope, double allocation, cycles, late plans and maximum contractual penalty without interpreting legal rights from engineering activity.
Audit cost allocation consistency
Audit whether shared engineering, platform, cloud, vendor, or operating cost pools reconcile to source totals and follow their declared pro-rata allocation bases at every target.
Audit cost capitalization sensitivity
Audit whether permitted software-cost capitalization choices change reported project ROI and priority even though scenario cash NPV, downside, and economic rank are unchanged.
Audit cyber control evidence integrity
Audit whether claimed defense in depth is supported by current independent control tests mapped to declared attack-path steps, while preserving duplicate mappings and counting each exposed business asset only once.
Audit data sovereignty residency evidence integrity
Audit every governed data asset's point-in-time storage, processing, replica, backup, log/cache and key locations plus cross-region transfers against an effective counsel-supplied residency policy, independent evidence, encryption controls and retention limits.
Audit decision execution fidelity
Audit whether approved decisions actually became verified implementation at the promised aggregate-unit and component grain, with whole-unit bootstrap uncertainty and simultaneous gates for fidelity, overdue scope, unverifiable evidence, exceptions and critical gaps.
Audit decision flow integrity
Audit management decision histories for unresolved work, state cycles, unowned dwell and excessive lead-time tails using immutable event sequences, whole-decision bootstrap uncertainty, simultaneous flow-level gates and state bottleneck diagnostics.
Audit decision rank robustness smaa
Measure rank acceptability, regret, pairwise dominance, and central winning weights under uncertain criterion scores and bounded stakeholder weights.
Audit delivery to cash chain integrity
Reconcile each governed milestone from delivery-ready evidence through customer acceptance, billing eligibility, net invoicing and collected cash; enforce temporal ordering, eligible-unbilled and outstanding-receivable identities, evidence separation and bounded diagnostics without treating Git activity as an accounting fact.
Audit executive technology reporting integrity
Audit a frozen executive technology pack for complete metric/risk scope, point-in-time source and definition lineage, numerical reconciliation, supported narrative direction, independent review and evidence coverage.
Audit extreme metric tail dependence
Detect extreme metric co-exceedances beyond independence with empirical tail coefficients, permutation inference, practical magnitude gates, and FDR control.
Audit financing term sheet integrity
Audit startup financing terms as exact share, price, proceeds and ownership identities: include pre-money option-pool increases and converting instruments in the pricing denominator, keep secondary purchases out of company cash and post-money share creation, reconcile primary issuance, post-money equity value and reported investor ownership, and retain evidence failures and impossible fees or secondary sales.
Audit forecast ensemble lineage integrity
Audit whether a claimed forecast ensemble is a complete, independently sealed and point-in-time evidence set rather than duplicated consensus, then score only mature uncontaminated outcomes.
Audit fundraising pipeline integrity
Audit a fundraising pipeline as point-in-time evidence rather than CRM theater: reconstruct monotone stage events, terminal status and primary proceeds, retain open opportunities as censored, reject forecasts made after resolution, detect duplicate active investor accounts, and gate the portfolio on mature-forecast support, Brier loss and calibration gap.
Audit growth incrementality experiment integrity
Audit aggregate randomized growth experiments before anyone trusts channel incrementality: enforce unique experimental units, nondegenerate logged propensities, both arms, control-spend discipline, baseline balance, spillover and evidence gates; then estimate propensity-weighted baseline-adjusted contribution, cluster-unit bootstrap uncertainty and incremental return on spend.
Audit human AI decision complementarity
Audit whether a governed human-AI decision process reduces prospective loss below the better standalone human or AI policy using paired shadow decisions, cluster bootstrap uncertainty, disagreement support and simultaneous gates across all screened systems.
Audit incident learning evidence integrity
Audit the complete point-in-time incident-to-postmortem-to-corrective-action lineage, separating missing or contradictory evidence from genuine overdue learning debt without attributing individual fault.
Audit informative metric missingness
Audit whether aggregate metric availability is associated with a governed outcome using permutation inference, bootstrap intervals, practical effect gates, and false-discovery control.
Audit joint metric dependency drift
Detect changes in cross-metric dependence with empirical-copula ranks, random-feature permutation inference, sliced Wasserstein magnitude, and FDR-controlled pair diagnostics.
Audit joint outcome network integrity
Audit whether a company-specific Bayesian joint-outcome network is fit for reliance by validating point-in-time lineage, DAG and CPT completeness, effective support, protected-attribute exclusions, and strictly out-of-time outcome calibration against a baseline.
Audit KPI threshold bunching
Detect a post-target excess concentration immediately above a governed KPI threshold: compare within-unit pre/post local mass and above-versus-below mirror asymmetry, bootstrap whole units, report density bins and a smoothed log-density jump, and explicitly refuse to equate bunching with individual gaming or intent.
Audit metric regime stability
Detect practical structural breaks across aggregate metric histories with recursive max-CUSUM search, moving-block null resampling, and familywise false-alarm control, then identify the defensible baseline regime.
Audit multigroup metric measurement invariance
Audit whether a multi-indicator aggregate management metric measures a comparable one-factor construct across teams, products, repositories, periods, or companies: fit training-only pooled and group PCA loadings, test configural dominance, metric loading cosine, scalar intercept range, residual variance, and untouched-test reconstruction invariance before any group ranking is trusted.
Audit multivariate metric drift
Detect material distribution shifts with reference-fixed quantile bins, PSI, Jensen-Shannon divergence, standardized Wasserstein distance, permutation tests, and FDR control.
Audit onboarding mentorship evidence integrity
Audit point-in-time onboarding cohorts, ordered autonomy milestones, source completeness and corroborated mentorship windows before publishing privacy-safe ramp evidence.
Audit operational alert decision integrity
Audit every point-in-time operational alert evaluation by recomputing fire/suppress decisions and verifying effective policy, cooldown, evidence freshness, context, controls, severity routing, acknowledgement, action and mature outcome lineage.
Audit order to cash bridge integrity
Reconcile the operational finance chain period by period: remaining performance obligation equals opening RPO plus bookings minus scope reductions and recognized revenue; signed net contract position equals opening position plus net billings minus revenue; accounts receivable equals opening AR plus net billings minus cash and write-offs; then enforce continuity, evidence and impossible-balance gates.
Audit org health score integrity
Reconstruct the organization-health composite from frozen component evidence and block publication when source completeness, consent, versioning, construct balance, cross-group measurement invariance, redundancy, privacy or leave-one-component stability fails.
Audit organizational change simulation integrity
Audit whether an organizational or technology what-if simulation is fit for reliance by checking point-in-time model lineage, local history, factor support, second-order dependency structure, calibration, scenario reconciliation and individual-level safeguards.
Audit point in time model integrity
Gate an analytical or AI model on point-in-time correctness by auditing actual feature availability, snapshot creation, target-window ordering, outcome resolution, source-record reuse, and embargoed train/calibration/test boundaries, with row and feature diagnostics rather than a generic leakage warning.
Audit policy feedback performativity
Audit whether deploying a probability-driven policy is associated with a changed score-to-outcome relationship: compute cluster-level exposed-versus-comparison pre/post differences in predictions, outcomes, calibration residuals, and Brier loss; bootstrap the assignment unit; and abstain when baseline balance or score overlap cannot support the comparison.
Audit portfolio dependency value double counting
Reconcile project and dependency business-case claims to governed unique benefit sources under coherent scenarios, quantifying naive, unique, duplicated, and unassigned value before portfolio prioritization.
Audit probabilistic forecasts
Audit whether resolved probability forecasts are accurate, calibrated, discriminating, and better than a base-rate prediction.
Audit probability policy subgroup equity
Audit an aggregate probability-driven policy across governed groups using weighted selection, error-rate, predictive-value, Brier, and calibration disparities; within-group bootstrap uncertainty; practical tolerances; privacy/support abstention; and Benjamini-Hochberg false-discovery control.
Audit proxy metric integrity
Audit whether an incentivized proxy structurally decoupled from outcomes or harmed guardrails using counterfactual residuals, bootstrap break tests, placebos, and multiplicity correction.
Audit recommendation coherence
Audit whether analytical recommendations for the same decision remain comparable, current, supported and coherent after every unique evidence lineage receives one vote split across its claimants, preventing duplicated source data from manufacturing consensus.
Audit recurring revenue bridge integrity
Audit recurring revenue as a continuous stock/flow ledger: reconcile opening revenue through new, expansion, reactivation, contraction, churn, FX and acquisition/divestiture movements to closing revenue; require each next opening to equal the prior close; and recompute GRR and NRR on an organic existing-customer perimeter that cannot be inflated by new business, reactivation, FX or M&A.
Audit release risk prediction integrity
Audit a complete eligible-change release-risk cohort for point-in-time prediction lineage, exact change-to-deployment linkage, mature mutually exclusive outcomes, selective labels, score-triggered intervention contamination, calibration and false alarms before the score influences a release decision.
Audit ROI denominator integrity
Reconcile each claimed ROI investment denominator with evidenced cost entries, required categories, inclusion fractions, and shared evidence identity, then recompute ROI before a business case reaches prioritization.
Audit root cause traceback evidence integrity
Audit whether an anomaly traceback is complete, point-in-time, multiplicity-controlled and honestly labeled as temporal or causal, including every upstream candidate, path lag, edge identification basis and later root-recovery validation.
Audit scenario tree decision integrity
Audit whether an adaptive management or capital policy is executable rather than clairvoyant: reconcile terminal probability mass, tree depth and unique node ancestry; require identical actions and information releases for indistinguishable histories; reject actions whose declared evidence is revealed only later; and retain unverified scenario exposure.
Audit selective label partial identification
Partially identify event risk, calibration gap, and Brier score when a policy selectively reveals outcomes: retain missing labels, model observed-versus-missing event odds within each decision stratum under a governed sensitivity ratio, propagate Beta posterior uncertainty, expose unsupported strata and label coverage, and fail closed on wide bounds or undocumented decision rules.
Audit service continuity recovery evidence integrity
Audit whether each critical service has a current, independently reviewed recovery plan whose complete capability/dependency path, backup, restore, failover, communications, RTO and RPO were proven in a recent production-representative exercise.
Audit shadow AI inventory integrity
Reconcile the approved AI-service registry against gateway, DNS/CASB, SSO, expense and provider evidence by deduplicating canonical aggregate usage events, then audit registration, status, domain/data-class policy, broker routing, contracts, security/privacy review, telemetry completeness and reported usage/spend.
Audit software supply chain integrity
Audit the deployed runtime software supply chain from application roots through resolved dependency edges: reconcile SBOM freshness, version resolution, source pinning, artifact attestation, support horizon, license policy, vulnerability disposition, evidence coverage and unique application value without treating repository text as provenance or exploitability evidence.
Audit staggered rollout identification
Audit staggered team-by-team adoption with not-yet-treated controls and require every simultaneous pre-period interval to fit inside a governed equivalence margin.
Audit strategic assumption lineage
Audit every aggregate initiative-value claim against a versioned canonical premise, unit, validation period and independent evidence lineage; retain unknown references, detect stale, unverified, conflicting and source-reused exposure, and gate hidden portfolio concentration in assumptions shared across initiatives.
Audit sunk cost escalation
Audit whether cumulative sunk cost predicts aggregate project continuation after project fixed effects, checkpoint time, forward value, success probability, remaining cost, and future irreversibility, with project-cluster bootstrap uncertainty.
Audit technical asset lifecycle integrity
Audit technical-asset lifecycle and value lineage across placed-in-service, assessment and retirement events; detect orphan active assets, stale recoverability evidence, active value links after retirement, remaining book value on retired assets and duplicated value-source attribution without treating engineering activity as accounting evidence.
Audit technology diligence evidence integrity
Audit a frozen technology diligence case against buyer-declared system/domain/claim scope, management assertions and fresh, rights-cleared, independently reviewed point-in-time evidence.
Audit technology financing plan integrity
Audit multi-period technology financing plans as continuous sources-and-uses ledgers: reconcile cash and debt identities, opening-to-closing continuity, period completeness, verified evidence, liquidity headroom and reported versus computed net-leverage covenants without hiding undefined leverage behind a favorable ratio.
Audit technology loss scenario integrity
Audit a technology loss-scenario ledger as a complete, zero-inclusive, point-in-time financial perimeter: reconcile every expected aggregate exposure and source, freeze scenario/currency/price basis, enforce evidence and privacy, and detect economic-loss lineage reused outside an explicit shared-loss group.
Audit technology risk appetite integrity
Audit whether board technology-risk appetite is executable rather than rhetorical: verify approval and point-in-time lineage, reconcile the root to finance limits, cover every aggregate risk unit exactly once, validate an acyclic owner/action limit tree, cap unsupported diversification credit and surface every breach with an executable escalation.
Audit value realization chain integrity
Audit one frozen aggregate cohort chain from eligible strategy scope through implementation, adoption, business outcome, monetization and cash collection, using whole-cohort bootstrap and simultaneous conversion, end-to-end, evidence and support gates.
Audit vendor lock in exposure
Audit whether every vendor-dependent business capability has a complete, scenario-executable exit portfolio; solve minimum-loss set cover exactly inside a governed state boundary, disclose heuristic fallback, and report infeasible-exit probability, expected loss, CVaR, lead time, and value concentration without converting vendor exposure into misconduct evidence.
Audit workforce identity access evidence integrity
Audit the point-in-time chain from an opaque workforce subject through authorized accounts, independent identity evidence, approved least-privilege grants and MFA/device-backed access events.
Detect operational critical slowing down
Detect early-warning patterns associated with an aggregate system losing resilience before a possible regime transition: locally detrend rolling windows, track rising lag-one autocorrelation, variance, and spectral reddening, compare endpoint shifts with a frozen reference regime, and control multiplicity under a circular moving-block bootstrap.
Evaluate offline policy doubly robust
Estimate a proposed contextual policy's value from logged decisions using cross-fitted outcome models, doubly robust scores, paired bootstrap safety bounds, and overlap diagnostics.
Monitor forecast calibration eprocess
Continuously monitor binary forecasts for calibration drift with an anytime-valid mixture e-process that does not incur a repeated-peeking penalty.
Monitor sequential intervention experiment
Monitor cumulative binary intervention outcomes with beta-binomial posteriors, Bayes factors, expected regret, and preregistered success, harm, or futility stopping.
Reconcile hierarchical delivery forecasts mint
Reconcile independently produced portfolio, product, team, repository, or workstream forecasts into one additive hierarchy using shrinkage MinT: learn the cross-level residual covariance on training forecasts, prove coherence, gate accuracy on later untouched periods, and return coherent current forecasts with uncertainty intervals.
Reconcile plan actual variance drivers
Reconcile plan-to-actual value variance with an exact, order-independent Shapley decomposition of a declared multilinear operating model.
Validate temporal leading indicators
Validate aggregate leading indicators only when their lagged history improves expanding-window forecasts beyond target autoregression, with block inference and FDR.