AI Governance

Patent Pending

Govern AI decisions with the rigor they demand

Register, monitor, and govern every AI model in your enterprise. Detect bias and drift, enforce human-in-the-loop policies, and maintain the audit trails regulators require - from EU AI Act to NYC Local Law 144.

EU AI Act ReadyFull Audit TrailHITL Enforcement

Challenges We Solve

Governance gaps that structured controls and audit trails eliminate.

Shadow AI Sprawl

Unsanctioned AI tools proliferate across teams with no inventory or risk scoring. Shadow AI Discovery inventories every tool and scores risk per team, while Agent Authority Boundary ensures agents stay inside their delegated envelope.

Prompt Injection & Jailbreaks

Deployed AI surfaces are vulnerable to adversarial inputs that bypass safety controls. Prompt Injection Exposure quantifies your attack surface, and LLM Jailbreak Resilience stress-tests defenses against evolving jailbreak corpora.

Missing Accountability & Provenance

When AI produces a bad output, tracing it back to the responsible prompt, model version, and human edit is impossible. AI Output Attribution Chain and Model Provenance Attestation close this gap.

Rubber-Stamp Oversight

Human-in-the-loop checkpoints exist on paper but don't change outcomes in practice. Human-in-the-Loop Efficacy measures whether HITL reviews actually alter decisions or just add latency.

AI Governance Lifecycle

AI Governance Pipeline

Every AI agent follows a four-stage governance lifecycle. Each stage is logged, scored, and auditable.

Stage 1

Register

Discover and inventory every AI agent, model, and tool across the organization with automated risk scoring.

Stage 2

Monitor

Continuously track agent behavior, output quality, and policy compliance in real time.

Stage 3

Govern

Enforce authority boundaries, approval gates, and human-in-the-loop checkpoints before actions execute.

Stage 4

Audit

Immutable logs capture every decision, input, output, and override for regulatory and fiduciary review.

Use Cases

Real governance scenarios powered by DecisionLedger.

Chief AI Officer

Runs Shadow AI Discovery across all teams, uncovering 23 unsanctioned AI tools. Scores each with Agent Authority Boundary, then uses Autonomy Graduation Readiness to determine which agents are safe for autonomous operation.

Full AI inventory with risk tiers - 8 tools flagged for remediation, 4 graduated to autonomous

Compliance Director

Uses AI Evaluator Calibration to detect a 12% drift in their LLM-as-judge scoring. Runs Human-in-the-Loop Efficacy to prove HITL reviews are changing outcomes. Generates EU AI Act evidence from Model Provenance Attestation and AI Output Attribution Chain.

Calibration drift caught before regulatory review - compliance evidence generated automatically

CTO

After a prompt injection incident, runs Prompt Injection Exposure across all AI surfaces and LLM Jailbreak Resilience stress tests. Uses Tool Call Chain Risk to identify agent workflows with unsafe rollback paths, then deploys the kill switch on high-risk agents.

Attack surface quantified, 3 vulnerable surfaces hardened, incident contained with full audit trail

Measurable Impact

Based on platform benchmarks across early adopters.

Shadow AI Inventory

Unknown tool count100% discovered and risk-scored

Full visibility

Prompt Injection

No exposure measurementPer-surface risk quantified

Proactive defense

HITL Effectiveness

Assumed effectiveMeasured with Bayesian analysis

Data-driven oversight

Model Provenance

No lineage trackingFull supply-chain attestation

Audit-ready

Agent Inventory

Tribal knowledge of deployed agentsAuto-discovered registry with risk scores

100% coverage

Bias Detection

Post-hoc bias auditsContinuous fairness monitoring

Real-time alerts

Platform Features

Built-in AI Governance Controls

Not just models about AI risk - actual enforcement tools that register, monitor, and control every AI agent and model in your organization.

Agent Registry

Register every AI agent with per-agent permissions, activity monitoring, and instant suspension. Know exactly what AI is doing across your organization.

Kill Switch

Circuit breaker for any AI model or agent. One-click disable across your entire tenant with automatic cool-down re-enable when you're ready.

Shadow Mode

Test new models in production without affecting live decisions or audit logs. Validate AI outputs side-by-side before going live.

Bias Auditing

Statistical bias detection across protected classes with a dedicated bias dashboard. Surface disparate impact before it becomes a compliance finding.

SHAP Explainability

Every prediction comes with SHAP waterfall plots showing feature importance and input-to-output transparency. No more black-box AI decisions.

Policy Guardrails

Define enforceable constraints with JSONLogic rules. Auto-flag, block, or escalate violations with full override tracking and rationale logging.

Drift Detection

Monitor policy and guardrail effectiveness over time with automated alerts when controls go stale. Detect when regulatory or policy changes invalidate existing controls.

Compliance Badges

Pre-mapped controls for EU AI Act, NYC Local Law 144, SOX 302/404, and DOL Fiduciary Rule. Generate compliance evidence automatically from your governance activity.

Connects With

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

Salesforce

HubSpot

Stripe

Shopify

Google Analytics 4

Workday

QuickBooks

Snowflake

Slack

Zendesk

GitHub

Meta Ads

Mailchimp

NetSuite

Jira

Power BI

Salesforce

HubSpot

Stripe

Shopify

Google Analytics 4

Workday

QuickBooks

Snowflake

Slack

Zendesk

GitHub

Meta Ads

Mailchimp

NetSuite

Jira

Power BI

Featured Models

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

Algorithmic Impact Assessment

Formal AIA as quantitative decision model with statistical bias analysis, EU AI Act article scoring, and remediation roadmap

Risk Matrix

Agent Authority Boundary

Scores whether an AI agent's proposed action falls inside its delegated authority envelope.

Risk Matrix

Prompt Injection Exposure

Quantifies organizational exposure to prompt injection across deployed AI surfaces.

Risk Matrix

AI Evaluator Calibration

Detects drift in LLM-as-judge scoring relative to human ground truth.

Anomaly Detection

Model Provenance Attestation

Verifies model lineage, training data attestation, and supply-chain trust.

Risk Matrix

Agentic Workflow Replay Risk

Scores reproducibility risk of agent decisions when re-executed against changed external state.

Risk Matrix

RAG Grounding Quality

Measures retrieval grounding strength, hallucination probability, and citation faithfulness.

Weighted Sum (MCDA)

AI Cost Attribution Anomaly

Detects anomalous per-team or per-feature LLM spend.

Anomaly Detection

Shadow AI Discovery

Inventories unsanctioned AI tool usage with risk scoring per tool/team.

Risk Matrix

Human-in-the-Loop Efficacy

Measures whether HITL checkpoints actually change outcomes versus rubber-stamping.

Bayesian Inference

Autonomy Graduation Readiness

Decides whether an AI workflow has earned the right to move from supervised to autonomous operation.

Weighted Sum (MCDA)

Multi-Agent Check Bypass Detection

Detects when multiple AI agents converge on outcomes that bypass intended controls.

Anomaly Detection

Tool Call Chain Risk

Scores risk in agent tool-call chains based on depth, side-effect surface, and rollback feasibility.

Risk Matrix

AI Output Attribution Chain

Tracks which prompt, model version, retrieval source, and human edits produced a given output.

Risk Matrix

Synthetic Data Provenance

Detects synthetic content used as training input or evidence with provenance tracking.

Risk Matrix

Appeal Process Documentation

Captures the customer's appeal channel, response SLA, and review record.

Weighted Sum (MCDA)

Fine-Tuning Data Leakage Risk

Scores extraction risk of confidential or PII training data from fine-tuned models.

Risk Matrix

Agent Termination Safety

Pre-deployment scoring of whether an agent can be safely halted mid-execution.

Risk Matrix

LLM Jailbreak Resilience

Tests deployed AI surfaces against jailbreak corpus and tracks resilience drift.

Stress Testing

AI Vendor Lock-In Exposure

Scores switching cost across model providers including prompt portability and contract terms.

Weighted Sum (MCDA)

AI Incident Postmortem Completeness

Scores AI incident postmortems against structured template.

Weighted Sum (MCDA)

How It Works

Three steps to structured, auditable decisions.

Discover & Score Risk

Run Shadow AI Discovery to inventory unsanctioned tools, then score each agent with Agent Authority Boundary and Prompt Injection Exposure to quantify your attack surface and authority gaps.

Validate & Harden

Stress-test with LLM Jailbreak Resilience, verify RAG Grounding Quality for hallucination risk, and audit Tool Call Chain Risk to ensure agent workflows can be safely rolled back.

Monitor & Govern

Track AI Evaluator Calibration for scoring drift, measure Human-in-the-Loop Efficacy to prevent rubber-stamping, and detect Multi-Agent Check Bypass before controls are circumvented.

Graduate & Audit

Use Autonomy Graduation Readiness to decide when workflows can move from supervised to autonomous. Maintain full provenance with AI Output Attribution Chain and Model Provenance Attestation.

Replace Your Stack

How many AI agents in your organization have been tested against prompt injection, have verified provenance, or have measured whether human oversight actually changes outcomes?

Spreadsheet AI inventories

Static model lists with no risk scoring, authority boundaries, or jailbreak testing

Manual compliance documentation

No automated provenance attestation or output attribution chain

MLOps tools without governance

Track model versions but not prompt injection exposure, HITL efficacy, or agent authority

GRC add-on modules

Generic risk tools that don't understand agent tool chains, RAG grounding, or multi-agent bypass risks

All in one governed platform

Start with AI Governance today

See how DecisionLedger AI transforms your decision-making.