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Decision Models
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Scientific Methods
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Integrations
Four steps from raw data to governed, auditable, defensible decisions.
Define your decision structure: criteria, weights, alternatives, and constraints. Choose from 298 pre-built models or create your own.
Run scenarios using 14 proven decision science methods, from Monte Carlo simulation to Bayesian inference. Compare outcomes side by side.
Route through approval workflows, enforce policy guardrails, and pass governance gates. Every decision is logged with an immutable audit trail.
Record outcomes against predictions. Monitor AI agent costs, calibrate model accuracy over time, and close the feedback loop with defensible evidence.
The pillars that turn unstructured decisions into governed, repeatable, defensible processes.
298 pre-built models across HR, Finance, Operations, and Strategy. 14 academically-grounded methods including MCDA, Monte Carlo, Bayesian inference, and linear programming with full transparency into every reasoning structure.
Agent registry, kill switches, shadow mode, governance gates, and an independent AI evaluator that grades every model run. Real-time compliance posture across every agent and decision.
See what every AI decision actually costs, attributed to the project and the decision that drove it, not just a monthly bill. Set budgets that warn, throttle to lower-cost models, then block before spend runs away. Cache-aware accounting, spend anomaly detection, optimization recommendations, and unit economics like cost per decision and AI spend as a percent of revenue. Carbon estimates included.
Route every AI call through one governed gateway that meters cost and applies savings automatically: cache identical requests so you never pay twice for the same answer, try a lower-cost model first and escalate only when needed, and run non-interactive work in batch. Outcome-conditioned routing learns which model delivers the best real-world result for each kind of decision and steers spend to the most cost-effective model that meets your quality bar.
Run projects that combine human labor cost and AI spend in one budget. Pull payroll and effort from your HRIS, attribute every governed AI decision to the project that drove it, and track total cost, ROI, and budget burn across people and AI together. Separate labor and AI envelopes keep workforce cost and model spend legible side by side.
Full observability over every LLM call: tokens, latency, success rates, and cost broken down by provider, model, agent, user, and project. Live dashboards with trend, velocity, and forecast show where spend is going and where it is growing, with anomaly flags on unusual spikes. Unified across Claude, GPT, and Gemini.
Define enforceable policies in plain rules. Compliance packages map to regulatory frameworks (EU AI Act, SOC 2, GDPR). GRC export bundles evidence for auditors on demand.
Track decisions from draft through analysis, deliberation, approval, execution, and monitoring to closure. Full lifecycle with outcome recording, calibration, and decision-to-decision traceability.
Full board portal with resolutions, AI-powered meeting minutes, ESG tracking, and director management. Committee voting workflows with quorum enforcement and resolution registers.
Custom KPI libraries with threshold alerts. Cascading OKRs from company to individual. Benchmark against FRED, BLS, SEC EDGAR, and peer organizations with drift detection. Upload premium data from Mercer, Radford, or SHRM. Browse and share benchmarks in the data marketplace.
Monte Carlo simulation, sensitivity heatmaps, counterfactual exploration, and what-if comparison. Chain models into multi-step playbooks with automated execution.
150+ connectors for CRM, marketing, ecommerce, finance, HR, analytics, and support platforms. Bidirectional sync with writeback capabilities. Zoom meeting integration, scheduled runs, webhooks, and MCP-native Claude AI integration.
Solutions by domain
The same governed engine, shaped to the decisions your team makes every day. Pick a domain to see the models, the methods, and the governance behind them. These are eight of our most-used domains; the full catalog spans 298 models across 19 business domains.
Give CHROs structured, defensible answers to their hardest people decisions.
Decisions you'll make
Methods behind them
Governance built in
Every model is auto-audited for adverse impact (EEOC, OFCCP, NYC LL144) with a full evidence trail.
Every model uses academically-grounded methods, not black boxes. Full transparency into the reasoning structure behind every recommendation.
298 pre-built decision models organized by domain. Deploy in minutes, customize to your data.
Comparison
Spreadsheets, BI tools, and GRC platforms each solve a piece. DecisionLedger is purpose-built for the full decision lifecycle.
| Feature | Spreadsheets | BI Tools | GRC | DecisionLedger |
|---|---|---|---|---|
| Structured decision models | ||||
| Full audit trail per decision | ||||
| AI-powered recommendations | ||||
| Policy guardrails & enforcement | ||||
| Monte Carlo & scenario modeling | ||||
| Outcome tracking & calibration | ||||
| Market benchmark context | ||||
| EU AI Act / SOC 2 evidence export |
Connect to the systems your teams already use across CRM, marketing, ecommerce, finance, HR, analytics, and support. Bidirectional sync keeps everything in lockstep.
Salesforce
Workday
Slack
NetSuite
Power BI
Salesforce
Workday
Slack
NetSuite
Power BISync contacts, deals, and pipeline data so revenue models run on live numbers.
Pull campaign performance from ad platforms and email tools for spend decisions.
Sync orders, revenue, and subscriptions for forecasting and unit economics.
Connect your ledger and billing systems for cashflow and budget models.
Sync employee data, org structures, and workforce metrics in real time.
Bring traffic, funnel, and product usage data into decision context.
Sync tickets, conversations, and satisfaction data for service decisions.
Query and push results to your analytical data layer.
Run models conversationally via MCP-native integration. AI agents with cost tracking and governance controls.
Embed decision outputs in dashboards and reports your teams already use.
Benchmark decisions against real-time economic data and industry metrics.
Push decision notifications and approval requests to team channels.
Built for regulated industries. Every layer of the platform enforces isolation, auditability, and compliance.
Enterprise single sign-on with SAML 2.0 and OpenID Connect support.
Tenant-scoped data isolation enforced at the database layer.
Every decision, approval, and data change recorded with tamper-proof S3 Object Lock storage.
Multi-tier role-based access control for fine-grained team management.
Monitor token usage, estimated costs, and compliance posture across every AI agent that touches your decisions.
Automatic detection and classification of personally identifiable information in every model input and output.
Pre-execution policy enforcement that blocks, flags, or escalates model runs that violate org-defined rules.
Export audit-ready evidence bundles mapped to EU AI Act, NIST AI RMF, SOC 2, GDPR, and CCPA frameworks.
Complete data and compute isolation between organizations. No cross-tenant bleed.
Agent-generated Excel and Word files encrypted with AES-256. Set a default password per agent or override per run.
Conversations are automatically classified by regulatory domain, activating the right safeguards: privilege preservation for legal, HIPAA-strict scanning for healthcare, MNPI embargo for financial, and evidence linking for compliance.
Structured intake forms for decision requests. Route submissions through approval workflows and auto-create decision records from form data.
Browser push notifications for approval requests, agent completions, drift alerts, and decision lifecycle events. Stay informed without polling.
Most tools stop at showing you data. DecisionLedger AI™ takes you from insight to executed, traceable, defensible decisions.
Track every decision from draft through deliberation, approval, execution, and monitoring to closure. Record outcomes, measure prediction accuracy, and build an organizational decision memory.
See exactly what your AI agents cost: total token usage, estimated spend in USD, success rates, and compliance posture. Per-agent and cross-agent breakdowns with time-series trending.
Collaborative spaces where stakeholders debate decisions with threaded discussions, voting, and AI-powered synthesis that distills consensus from diverse perspectives.
Chain multiple models into sequenced playbooks. Run multi-step decision workflows with automated handoffs, from data ingestion to final recommendation.
Visualize how decisions relate to each other: dependencies, contradictions, and causal chains. Detect duplicates and conflicts across your decision portfolio automatically.
Ask 'what if we had decided differently?' Replay past decisions with altered inputs and compare to actual outcomes. Post-mortem analysis for continuous improvement.
Agents that reason through your decision frameworks - governed, traceable, and cost-tracked from first token to final outcome.
Design agents visually. Define system prompts, tool access, model selection, and triggers - then deploy with governance baked in. Schedule agents on cron or fire them from events automatically.
Every agent run receives the full decision graph: prior decisions, linked scenarios, and outcome history. Agents reason with organizational memory, not just prompts.
Route agents through model-specific governance gates. Different policies for Claude, GPT, Gemini - unified audit trail regardless of provider.
Test new agents in shadow mode before going live. Kill switches halt any agent instantly, with no delay.
Agents build persistent memory across runs - learned patterns, preferences, and context that carry forward. Delete or inspect any memory key from the UI.
Full version history for every agent configuration change. Compare snapshots side by side and restore any previous version in one click.
Record what actually happened after agent decisions execute. Calibrate agent accuracy over time and feed outcomes back into future decision runs.
AI Assistant
The first AI assistant that classifies conversations by regulatory domain from the start. Legal privilege, HIPAA, SOX/MNPI: each domain activates its own guardrails, audit trail, and document export format automatically.
Choose a conversation domain
Based on employment law precedent, the severance structure should include ADEA waiver provisions...
Each conversation is governed by its regulatory domain, which activates domain-specific guardrails, retention policies, watermarking, and audit events. Legal privilege stays privileged, PHI stays compliant, and MNPI stays restricted.
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Domain modes
SHA-256
Attestation
Word
Domain-aware export
SHA-256 attestation, work-product watermarking, litigation hold, counsel-directed workflows, and exportable privilege logs. Built for privilege-safe, counsel-directed confidentiality.
PHI-aware conversations with 6-year retention, strict PII redaction, and HIPAA §164.312(b) audit events generated for every interaction.
Material non-public information handling, SOX audit trail, insider-list tracking, and restricted-distribution watermarks on every export.
Tie every conversation to SOX, GDPR, HIPAA, or EU AI Act frameworks. Every response becomes linkable, defensible evidence.
Download conversations as Word documents with domain-specific headers, footers, watermarks, and privilege designations baked in.
Real-time classifier detects when conversation content drifts outside the selected domain, alerting users before sensitive data is misrouted.
Privilege Preservation technology - U.S. Provisional Patent Application No. 64034271. Domain classification, attestation chains, and privilege-aware document export are patent-pending.
"We built DecisionLedger because every organization deserves a decision engine that is auditable, governed, and grounded in real data, not gut instinct. Every model run produces evidence you can defend."
Ryan Brush
Founder & Chief Architect, DecisionLedger AI
Why teams trust us early
Every significant engineering and product decision here is modeled, governed, and recorded in DecisionLedger itself. Our own commits carry the Decision-ID that links the code back to the decision and its evidence.
We are onboarding a focused group of design partners who work directly with the founding team, shape the roadmap, and get hands-on implementation support as they roll out governed AI decisions.
The platform is built for regulated buyers from day one: immutable audit logs, policy enforcement before execution, and compliance evidence mapped to the EU AI Act, NIST AI RMF, and SOC 2.
DecisionLedger's full model library is now accessible via Claude AI. Run M&A diligence, workforce analytics, financial models, and 298 more with full audit trails, PII scanning, and defensible outputs.
Adjust the sliders to match your team and see the potential impact of structured decision-making.
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