Report Types

SignalBreak generates 10 governance reports for different stakeholders across 4 maturity phases.

Overview

SignalBreak's Governance Intelligence reports transform your AI infrastructure data into actionable insights for different audiences. Each report type addresses specific governance needs, from daily operations to boardroom presentations to regulatory compliance.

Report Phases

Reports are organized by maturity and complexity:

Phase	Focus	Audience	Report Count
Phase 1	Core Operations & Executive	DevOps, C-suite	2 reports
Phase 2	Compliance & Audit	GRC, Legal, Auditors	3 reports
Phase 3	Advanced Compliance & Risk	Enterprise, Federal, Procurement	3 reports
Phase 4	Deep-Dive Analysis	Technical, Strategic	2 reports

Phase 1 Reports (Available Now)

1. Operational Brief 📊

Target audience: DevOps, Platform Engineers, AI/ML Teams

Purpose: Weekly digest of operational AI governance status for technical teams managing day-to-day AI infrastructure.

What it contains:

Active signals (last 7 days): Provider changes affecting your workflows
At-risk workflows: Workflows without fallbacks or single-provider dependencies
Upcoming changes: Model deprecations, pricing changes with deadlines
Active scenarios: Running business continuity tests
Quick wins: Low-effort, high-impact improvements you can make this week

When to use:

Monday morning team stand-ups
Weekly sprint planning
Incident response prioritization
Quarterly OKR planning

Report length: 2-3 pages

Example use case:

Use case: Platform team needs to prioritize this week's tasks

Report shows:
- 3 critical workflows with no fallback (high risk)
- OpenAI deprecating gpt-3.5-turbo-0301 in 30 days (12 workflows affected)
- Quick win: Add fallback to "Customer Support Chatbot" (15 mins)

Action: Team spends Monday morning adding fallbacks to 3 critical workflows
Result: Reduced single-point-of-failure risk from 15 to 12 workflows

Key sections:

Executive Summary: 3-sentence overview of operational status
Critical Alerts: Signals requiring immediate action (< 7 days)
Workflow Health: At-risk workflows table with remediation steps
Provider Changes: Upcoming deprecations/pricing/policy changes
Recommendations: Prioritized quick wins ranked by impact/effort

2. Board Summary 👔

Target audience: C-suite (CEO, CTO, CFO), Board Members, Executives

Purpose: High-level governance overview for leadership to understand AI risk posture without technical details.

What it contains:

Governance maturity score (0-100): Overall AI governance health (Green/Amber/Red)
Provider concentration risk: Dependency on single providers (charts)
Top exposures: Highest-risk workflows ranked by business impact
90-day trend: Governance score trajectory (improving/stable/declining)
Key performance indicators (KPIs): Critical metrics for decision-making

When to use:

Monthly board meetings
Quarterly business reviews
Investor due diligence
Executive risk committee updates
Budget/resource allocation decisions

Report length: 2 pages (designed for executive brevity)

Example use case:

Use case: CFO presenting AI risk to board

Report shows:
- Overall Score: 72/100 (Amber) - up from 65 last quarter
- Concentration Risk: 85% of workflows use OpenAI (critical dependency)
- Top Exposure: Fraud detection system (£50k/day revenue at risk)
- Trend: Improving (+7 points in 90 days)

Action: Board approves £50k budget to diversify providers
Result: Reduced OpenAI concentration from 85% to 60% in Q2

Key sections:

RAG Status Dashboard: Red/Amber/Green governance indicators
Governance Maturity: Score with maturity level (L1-L5)
Concentration Risk Chart: Provider dependency breakdown
Top 5 Exposures: Critical workflows with business impact estimates
90-Day Trend: Line chart showing governance score trajectory
Executive Actions: 3-5 prioritized recommendations

RAG Status Table (unique to Board Summary):

Category	Status	Score	Action Required
Provider Diversity	🔴 Red	35/100	High concentration (85% OpenAI)
Fallback Coverage	🟡 Amber	65/100	45% of critical workflows have fallbacks
Signal Response	🟢 Green	90/100	All signals reviewed within 48h
Governance Maturity	🟡 Amber	72/100	L3 (Defined) - target L4 by Q3

Phase 2 Reports (Available)

3. ISO 42001 Alignment 📋

Target audience: GRC (Governance, Risk, Compliance), Compliance Officers, Internal Audit

Purpose: Gap analysis against ISO 42001:2023 AI Management System standard to demonstrate compliance readiness.

What it contains:

Control mapping: All 39 ISO 42001 clauses (4.1 - A.18)
Compliance status: Red/Amber/Green per control
Evidence trail: Specific data points proving compliance
Gap analysis: Missing controls with remediation guidance
Overall compliance percentage: (Green controls / Total controls) × 100

When to use:

ISO 42001 certification preparation
External audit readiness
Client/partner RFPs requiring ISO compliance
Quarterly compliance reviews
Management system documentation

Report length: 8-12 pages

Example use case:

Use case: Compliance preparing for ISO 42001 certification audit

Report shows:
- 28/39 controls Green (72% compliant)
- 8/39 controls Amber (needs improvement)
- 3/39 controls Red (critical gaps)

Red control: "A.12 - Data Protection Impact Assessment (DPIA)"
Gap: "No DPIA documented for high-risk AI systems"
Evidence needed: "DPIA for fraud detection + customer chatbot"

Action: Compliance completes 2 DPIAs over 3 weeks
Result: Red → Green, overall compliance 80% → 85%

Key sections:

Executive Summary: Overall compliance score and readiness level
Control Mapping Table: All 39 clauses with Red/Amber/Green status
Evidence Matrix: Data sources proving each control
Gap Analysis: Detailed breakdown of Amber/Red controls
Remediation Roadmap: Prioritized action plan to reach 100%
Certification Readiness: Estimated timeline to audit-ready state

ISO 42001 Clauses Covered:

Context (4.1-4.4): Organization context, stakeholder needs, scope, AI management system
Leadership (5.1-5.3): Top management commitment, policy, roles/responsibilities
Planning (6.1-6.4): Risk assessment, objectives, change management
Support (7.1-7.6): Resources, competence, awareness, communication, documented information
Operation (8.1-8.3): Operational planning, AI system lifecycle, third-party management
Performance (9.1-9.3): Monitoring, internal audit, management review
Improvement (10.1-10.2): Nonconformity, continual improvement
Controls (A.1-A.18): 18 specific AI controls (data quality, bias, explainability, etc.)

4. EU AI Act Readiness 🇪🇺

Target audience: Legal, Compliance, Data Protection Officers (DPOs), Product Teams

Purpose: Regulatory compliance assessment against EU AI Act (Regulation 2024/1689) to identify high-risk AI systems and demonstrate readiness.

What it contains:

AI system inventory: All workflows classified by risk level (High/Limited/Minimal/Unacceptable)
Article compliance: Status per EU AI Act article (Art 6, Art 9, Art 10-15, etc.)
High-risk system analysis: Mandatory requirements for high-risk AI (if applicable)
Transparency requirements: Disclosure obligations per risk category
Remediation roadmap: Steps to full compliance

When to use:

EU market entry planning
Product compliance assessment
Regulatory audit preparation
Customer/partner compliance questionnaires
Legal risk assessment

Report length: 10-15 pages

Example use case:

Use case: SaaS company selling to EU customers needs compliance

Report shows:
- 2 High-Risk AI systems identified:
  1. "Credit Scoring Model" (Art 6: High-risk - financial scoring)
  2. "Resume Screening AI" (Art 6: High-risk - employment decisions)

Compliance status:
- Art 9 (Risk Management System): Partial - no documented risk assessment
- Art 10 (Data Governance): Partial - training data not documented
- Art 13 (Transparency): Non-Compliant - no user disclosures

Action: Legal creates compliance package over 8 weeks
Result: All high-risk systems compliant, safe to sell in EU

Key sections:

Executive Summary: Risk profile and compliance readiness
System Inventory: All AI workflows with risk classifications
High-Risk Analysis: Detailed assessment if high-risk systems present
Article Compliance Table: All applicable articles with status
Transparency Requirements: Required disclosures per system
Compliance Roadmap: Timeline and actions to full compliance

EU AI Act Risk Categories:

Category	Definition	Examples	Requirements
Unacceptable Risk	Prohibited AI practices	Social scoring, subliminal manipulation	Banned - cannot deploy
High-Risk	Significant impact on rights/safety	Credit scoring, CV screening, medical diagnosis	Strict requirements (Art 8-15)
Limited-Risk	Transparency obligations	Chatbots, deepfakes, emotion recognition	User disclosure required
Minimal-Risk	Low or no risk	Spam filters, inventory management	No specific requirements

5. Audit Pack 📁

Target audience: External Auditors, Regulators, Certification Bodies

Purpose: Evidence bundle with integrity verification for third-party audits. Provides tamper-proof governance trail.

What it contains:

All governance reports: Operational, Board, ISO 42001, EU AI Act (all generated at same timestamp)
Data manifest: List of all reports with SHA-256 integrity hashes
Verification instructions: How auditors can verify report authenticity
Timestamp & version: SignalBreak version used for report generation
Export format: ZIP archive with markdown files + checksums

When to use:

External compliance audits (ISO, SOC 2, etc.)
Regulatory inquiries or investigations
Customer/partner due diligence
Insurance underwriting (cyber insurance)
Legal discovery/evidence preservation

Report length: Bundle of all reports (25-40 pages total)

Example use case:

Use case: External auditor requires governance evidence trail

Report shows:
- 5 reports generated at 2025-01-15 14:23:00 GMT
- Each report has SHA-256 hash for integrity verification
- SignalBreak version: v2.1.3

Auditor actions:
1. Downloads audit-pack-2025-01-15.zip
2. Verifies SHA-256 hashes match manifest
3. Reviews all 5 reports
4. Confirms no tampering (hashes valid)

Result: Auditor accepts evidence as authentic, audit proceeds smoothly

Key sections (Manifest):

Table of Contents: All included reports with page counts
Manifest: Report filenames + SHA-256 hashes
Verification Guide: Step-by-step hash verification instructions
Generation Metadata: Timestamp, SignalBreak version, tenant
Individual Reports: Each report as separate markdown file

Integrity Verification:

bash

# Auditors verify report authenticity

# On Windows (PowerShell)
CertUtil -hashfile operational-brief.md SHA256

# On macOS/Linux
shasum -a 256 operational-brief.md

# Compare output to manifest hash
# If match: Report is authentic
# If mismatch: Report was tampered with

Phase 3 Reports (Available)

6. SOC 2 Type II Readiness 🔒

Target audience: Enterprise Sales, Security Teams, Compliance, Prospective Customers

Purpose: Trust Services Criteria (TSC) assessment for enterprise sales and SOC 2 certification readiness.

What it contains:

5 Trust Services Categories: Security, Availability, Processing Integrity, Confidentiality, Privacy
Control objectives: 64 common criteria + 25 additional points of focus
Evidence mapping: How SignalBreak data demonstrates control effectiveness
Gaps & remediation: Missing controls with implementation guidance
Readiness score: (Met criteria / Total criteria) × 100

When to use:

SOC 2 Type II certification preparation
Enterprise customer RFPs (security questionnaires)
Security program assessment
Vendor risk reviews
Trust Center documentation

Report length: 12-18 pages

Example use case:

Use case: SaaS startup pursuing enterprise customers needs SOC 2

Report shows:
- Overall Readiness: 78% (70 of 89 criteria met)
- Security (CC1-CC9): 85% met
- Availability (A1): 100% met (fallback coverage strong)
- Processing Integrity (PI1): 60% met (gaps in AI accuracy monitoring)

Gap: "PI1.4 - Processing is complete, accurate, and timely"
Evidence needed: "AI model output quality monitoring"

Action: Implement quality monitoring dashboards over 4 weeks
Result: PI1 readiness 60% → 95%, overall readiness 78% → 88%

Key sections:

Executive Summary: Overall readiness and certification timeline
TSC Scorecard: 5 categories with Met/Partial/Not Met status
Control Objectives: Detailed breakdown of 89 criteria
Evidence Matrix: SignalBreak data mapped to each control
Gap Analysis: Critical gaps blocking certification
Remediation Roadmap: Prioritized action plan with timelines

Trust Services Categories:

Category	Common Criteria	Focus	SignalBreak Evidence
Security (CC)	CC1-CC9	Control environment, risk assessment, monitoring	Workflow access controls, audit logs, signal monitoring
Availability (A)	A1	System uptime and continuity	Fallback coverage, provider health tracking
Processing Integrity (PI)	PI1	Accurate, complete, timely processing	AI output quality, workflow monitoring
Confidentiality (C)	C1	Confidential data protection	Model access controls, data residency tracking
Privacy (P)	P1-P8	Personal data handling	PII processing workflows, consent tracking (if applicable)

7. NIST AI RMF Alignment 🏛️

Target audience: US Federal Agencies, Defense Contractors, Highly Regulated Industries (Healthcare, Finance)

Purpose: AI Risk Management Framework (NIST AI 100-1) alignment assessment for US government and regulated industries.

What it contains:

4 Core Functions: GOVERN, MAP, MEASURE, MANAGE
47 Subcategories: Detailed practices for each function
Implementation status: Implemented / Partial / Not Implemented per subcategory
Evidence mapping: How SignalBreak data proves implementation
Maturity assessment: Current maturity level per function

When to use:

Federal procurement (RFPs, contracts)
FedRAMP compliance preparation
Healthcare AI compliance (FDA premarket approval)
Financial services AI (OCC guidance)
Executive Order 14110 compliance (Federal AI use)

Report length: 15-20 pages

Example use case:

Use case: Healthcare AI startup bidding on federal contract

Report shows:
- Overall NIST AI RMF Alignment: 68%
- GOVERN: 85% implemented (strong governance foundation)
- MAP: 70% implemented (AI system inventory complete)
- MEASURE: 55% implemented (gaps in performance tracking)
- MANAGE: 60% implemented (incident response needs work)

Gap: "MEASURE 2.11 - AI system performance is regularly monitored"
Evidence needed: "Automated model quality monitoring"

Action: Implement monitoring dashboards for 3 critical AI models
Result: MEASURE function 55% → 80%, overall 68% → 75%
Federal contracting officer accepts proposal

Key sections:

Executive Summary: Overall alignment percentage and maturity
Function Overview: 4 core functions with implementation status
Subcategory Mapping: All 47 practices with evidence
Gap Analysis: Not Implemented subcategories with recommendations
Maturity Roadmap: Path from current state to full implementation
Federal Compliance: Mapping to Executive Order 14110 requirements

NIST AI RMF Functions:

Function	Focus	Subcategories	Key Practices
GOVERN	Organizational AI governance	12	AI governance structure, policies, roles, risk culture
MAP	AI risk identification	11	System inventory, context analysis, impact assessment
MEASURE	AI risk quantification	14	Performance metrics, bias testing, transparency, documentation
MANAGE	AI risk mitigation	10	Risk response, incident management, third-party oversight

8. Vendor Risk Assessment ⚖️

Target audience: Procurement, Security, Risk Management, Third-Party Risk Teams

Purpose: Per-provider risk scoring to quantify supply chain risk and inform vendor selection/diversification decisions.

What it contains:

Provider risk profiles: Each AI provider scored on 6 risk dimensions
Overall risk score (0-100): Higher = more risk (inverse of governance score)
Risk dimensions: Operational, Data, Concentration, Continuity, Compliance, Financial
Aggregated view: Portfolio-level risk summary across all providers
Comparison matrix: Providers ranked by risk level

When to use:

Vendor selection (RFPs, procurement decisions)
Third-party risk assessments
Contract negotiations (SLA requirements)
Budget/resource allocation
Supplier diversification strategy

Report length: 8-12 pages (depends on provider count)

Example use case:

Use case: Procurement evaluating 3 AI providers for contract renewal

Report shows:

Provider A (OpenAI):
- Overall Risk Score: 75/100 (High)
- Concentration Risk: 85% of workflows (critical dependency)
- Continuity Risk: No fallbacks for 12 critical workflows
- Financial Risk: Recent 30% price increase

Provider B (Anthropic):
- Overall Risk Score: 45/100 (Medium)
- Concentration Risk: 10% of workflows (healthy)
- Continuity Risk: All critical workflows have fallbacks
- Compliance Risk: Strong data residency options (EU/US)

Provider C (Google):
- Overall Risk Score: 60/100 (Medium)
- Operational Risk: 3 outages in last 90 days
- Data Risk: Limited regional availability

Action: Procurement negotiates multi-year contract with Provider B
+ diversification strategy to reduce Provider A dependency
Result: Concentration risk reduced from 85% to 55% over 6 months

Key sections:

Executive Summary: Aggregate portfolio risk and top concerns
Provider Risk Profiles: Each provider scored on 6 dimensions
Risk Heatmap: Visual matrix comparing all providers
Concentration Analysis: Dependency breakdown by provider
Recommendations: Diversification opportunities and cost trade-offs

Risk Dimensions Explained:

Dimension	What It Measures	High Risk Indicators
Operational	Provider reliability and uptime	Frequent outages, slow response times, API instability
Data	Data sovereignty and residency	Limited regional options, unclear data handling, GDPR concerns
Concentration	Workflow dependency	>50% of workflows on single provider, critical systems single-sourced
Continuity	Business continuity preparedness	No fallbacks, single-provider dependencies, long RTO/RPO
Compliance	Regulatory alignment	Missing certifications (SOC 2, ISO), poor audit trail
Financial	Cost volatility	Frequent price changes, unclear pricing, high cost per transaction

Phase 4 Reports (Coming Soon)

9. Provider Deep-Dive 🔍

Target audience: Technical Leads, Solution Architects, AI/ML Engineers

Purpose: Detailed technical analysis of single provider to inform architecture decisions and risk mitigation.

What it will contain:

Dependency mapping: All workflows, models, and API calls for this provider
Usage analytics: API call volume, latency, error rates, cost breakdown
Failure scenarios: Impact analysis if this provider fails
Migration plan: Step-by-step guide to reduce/eliminate dependency
Alternative providers: Comparison matrix with migration effort estimates

When to use:

Provider migration planning
Architecture reviews
Incident postmortems
Cost optimization initiatives
Contract renegotiations

Report length: 10-15 pages

Planned availability: Q2 2025

10. Third-Party AI Exposure 🔗

Target audience: Procurement, Security, Vendor Management, Legal

Purpose: Map AI dependencies hidden in vendor software to understand indirect AI exposure.

What it will contain:

Vendor AI inventory: Which vendors use AI in their products
Indirect exposure: AI dependencies you don't directly control
Cascading risk: Impact if vendor's AI provider fails
Contract gaps: Missing AI-specific terms in vendor contracts
Remediation strategy: How to mitigate third-party AI risk

When to use:

Vendor due diligence
Third-party risk assessments
Contract negotiations
Supply chain risk mapping
Regulatory compliance (EU AI Act subprocessor requirements)

Report length: 12-18 pages

Planned availability: Q3 2025

Choosing the Right Report

By Audience

Audience	Primary Report(s)	Secondary Report(s)
DevOps / Platform Engineers	Operational Brief	Provider Deep-Dive
C-suite / Board	Board Summary	-
GRC / Compliance	ISO 42001, EU AI Act	SOC 2, NIST AI RMF
Legal	EU AI Act	ISO 42001
External Auditors	Audit Pack	ISO 42001, SOC 2
Procurement / Vendors	Vendor Risk	Third-Party AI Exposure
Enterprise Sales	SOC 2	Board Summary
Federal / Defense	NIST AI RMF	SOC 2

By Use Case

Use Case	Recommended Report(s)	Frequency
Weekly operations	Operational Brief	Weekly
Board meetings	Board Summary	Monthly/Quarterly
ISO 42001 certification	ISO 42001 Alignment	Quarterly (until certified)
EU market entry	EU AI Act Readiness	One-time + annual
External audit	Audit Pack	As needed
Enterprise sales	SOC 2	Quarterly + RFPs
Federal procurement	NIST AI RMF	Per contract
Vendor selection	Vendor Risk	Per procurement cycle
Provider migration	Provider Deep-Dive	As needed
Third-party risk	Third-Party AI Exposure	Annual

Report Features

Generation

How reports are generated:

Navigate to Dashboard → Governance → Reports
Select report type
Click "Generate Report"
Wait 5-30 seconds (depends on data volume)
View in-browser or download as markdown/PDF

Generation time:

Fast (5-10s): Operational Brief, Board Summary
Medium (10-20s): ISO 42001, EU AI Act, SOC 2
Slow (20-30s): Audit Pack, NIST AI RMF, Vendor Risk

Formats

Available export formats:

Markdown (.md): For version control, GitHub, internal wikis
PDF (.pdf): For sharing with stakeholders, printing
HTML: For embedding in internal tools
JSON (Audit Pack only): For programmatic consumption

Scheduling

Automated report generation:

Configure in Settings → Reports → Schedules
Frequency: Daily, Weekly, Monthly, Quarterly
Delivery: Email, Slack, Webhook
Recipients: Email addresses or Slack channels

Example schedule:

Operational Brief: Weekly (Monday 9am)
Board Summary: Monthly (1st of month, 8am)
ISO 42001: Quarterly (end of quarter)

Best Practices

1. Start with Operational Brief

Why: Simplest report, immediate value for teams managing AI daily.

Recommended workflow:

Week 1: Generate Operational Brief, review with team
Week 2-4: Act on quick wins, monitor progress
Month 2: Add Board Summary for leadership visibility
Month 3+: Add compliance reports based on needs

2. Schedule Regular Generation

Why: Reports become stale quickly as your AI landscape changes.

Recommended frequencies:

Operational Brief: Weekly (Monday morning prep)
Board Summary: Monthly or quarterly (before board meetings)
ISO 42001 / EU AI Act: Quarterly (track compliance progress)
SOC 2 / NIST AI RMF: Quarterly (certification prep)
Vendor Risk: Bi-annually or per procurement cycle

Why: Governance is a team sport. Different stakeholders need different reports.

Who should see what:

Everyone: Operational Brief (transparency builds trust)
Leadership: Board Summary (executive visibility)
Compliance: ISO 42001, EU AI Act, SOC 2, NIST AI RMF
Procurement: Vendor Risk Assessment
External auditors: Audit Pack only (on demand)

4. Track Report Trends Over Time

Why: Single report is a snapshot. Trends show progress.

What to track:

Board Summary: Governance score trend (aim for consistent improvement)
ISO 42001: Compliance percentage (track gap closure)
Operational Brief: At-risk workflow count (aim to reduce)
Vendor Risk: Provider concentration (aim for diversification)

How to track:

Save reports to version control (Git)
Name files with timestamps: board-summary-2025-01-15.md
Generate quarterly comparison charts

5. Use Reports in Decision-Making

Why: Reports are only valuable if they drive action.

Examples:

Operational Brief shows 15 workflows with no fallback → Sprint to add fallbacks
Board Summary shows 85% concentration on OpenAI → Budget allocated for diversification
ISO 42001 shows Red controls → Compliance prioritizes gap remediation
Vendor Risk shows high financial risk → Procurement negotiates price lock-ins

FAQ

Can I customize reports?

Not currently. Report templates are fixed to ensure consistency and compliance alignment.

Future feature: Custom report builder (Q3 2025) will allow:

Custom branding (logo, colors)
Section selection (include/exclude specific sections)
Custom KPIs and metrics

How long does report generation take?

Typical times:

Operational Brief: 5-10 seconds
Board Summary: 10-15 seconds
ISO 42001 / EU AI Act: 15-20 seconds
SOC 2 / NIST AI RMF: 20-25 seconds
Audit Pack: 25-30 seconds (bundles all reports)

Factors affecting speed:

Data volume (number of workflows, signals, providers)
Report complexity (Audit Pack is slowest)
LLM API latency (Claude Sonnet used for generation)

Are reports updated in real-time?

No. Reports are snapshots at generation time.

How it works:

Generate report at 10:00 AM → Uses data as of 10:00 AM
Add new workflow at 10:30 AM → Not included in 10:00 AM report
Re-generate report at 11:00 AM → New workflow included

Best practice: Re-generate reports before important meetings or presentations to ensure latest data.

Yes. Use the Audit Pack for external sharing.

Why Audit Pack:

Includes integrity hashes (tamper-proof)
Bundled format (all reports together)
Verification instructions included
Designed for third-party auditors

Security:

Reports contain tenant-specific data (workflows, providers)
Only share with trusted parties (auditors, compliance consultants)
Use encrypted channels (email encryption, secure file sharing)

Do reports contain sensitive data?

Yes. Reports include:

Workflow names and descriptions
Provider names and models
Business context and impact estimates
Governance scores and maturity levels

What's NOT included:

API keys or credentials
Actual AI prompts or responses
Customer data or PII
Financial details (beyond high-level cost estimates)

Access control:

Reports require authentication (logged-in user)
Role-based: Not all users can generate all report types
Audit trail: All report generations logged

Can I generate reports via API?

Yes (Enterprise plans only).

Endpoint:

http

POST /api/reports/generate
Content-Type: application/json

{
  "reportType": "operational",
  "format": "pdf"
}

Response:
{
  "reportId": "abc-123",
  "downloadUrl": "https://signalbreak.com/api/reports/abc-123/download",
  "expiresAt": "2025-01-16T14:23:00Z"
}

Use cases:

Automated report generation (cron jobs)
Integration with BI tools (Tableau, PowerBI)
Custom workflows (Zapier, n8n)

Governance: Understand governance maturity scoring and how it feeds into Board Summary
Workflows: Workflow configuration impacts Operational Brief and Vendor Risk reports
Signals: Active signals appear in Operational Brief and Board Summary
Scenarios: Scenario execution results feed into risk assessments

Report Types ​

Overview ​

Report Phases ​

Phase 1 Reports (Available Now) ​

1. Operational Brief 📊 ​

2. Board Summary 👔 ​

Phase 2 Reports (Available) ​

3. ISO 42001 Alignment 📋 ​

4. EU AI Act Readiness 🇪🇺 ​

5. Audit Pack 📁 ​

Phase 3 Reports (Available) ​

6. SOC 2 Type II Readiness 🔒 ​

7. NIST AI RMF Alignment 🏛️ ​

8. Vendor Risk Assessment ⚖️ ​

Phase 4 Reports (Coming Soon) ​

9. Provider Deep-Dive 🔍 ​

10. Third-Party AI Exposure 🔗 ​

Choosing the Right Report ​

By Audience ​

By Use Case ​

Report Features ​

Generation ​

Formats ​

Scheduling ​

Best Practices ​

1. Start with Operational Brief ​

2. Schedule Regular Generation ​

3. Share Reports Widely ​

4. Track Report Trends Over Time ​

5. Use Reports in Decision-Making ​

FAQ ​

Can I customize reports? ​

How long does report generation take? ​

Are reports updated in real-time? ​

Can I share reports with external auditors? ​

Do reports contain sensitive data? ​

Can I generate reports via API? ​

Related Features ​

Support ​

Report Types

Overview

Report Phases

Phase 1 Reports (Available Now)

1. Operational Brief 📊

2. Board Summary 👔

Phase 2 Reports (Available)

3. ISO 42001 Alignment 📋

4. EU AI Act Readiness 🇪🇺

5. Audit Pack 📁

Phase 3 Reports (Available)

6. SOC 2 Type II Readiness 🔒

7. NIST AI RMF Alignment 🏛️

8. Vendor Risk Assessment ⚖️

Phase 4 Reports (Coming Soon)

9. Provider Deep-Dive 🔍

10. Third-Party AI Exposure 🔗

Choosing the Right Report

By Audience

By Use Case

Report Features

Generation

Formats

Scheduling

Best Practices

1. Start with Operational Brief

2. Schedule Regular Generation

3. Share Reports Widely

4. Track Report Trends Over Time

5. Use Reports in Decision-Making

FAQ

Can I customize reports?

How long does report generation take?

Are reports updated in real-time?

Can I share reports with external auditors?

Do reports contain sensitive data?

Can I generate reports via API?

Related Features

Support