Marmon Holdings, Inc. OS

What are we working on?

Build governed apps, documents, and workflows with your organization's context.
Starter workspaces
Federated Cyber Risk Command CenterAlign security maturity with business risk across autonomous operating companies while preserving local ownership.
Live App
Federated Security Operating ModelDraft a decision brief that combines shared security guardrails with company-owned implementation and risk decisions.
Document
Cyber & AI Governance ReviewCompare security automation candidates through common evaluation, data-boundary, cost, and human-approval controls.
Slide Deck
Illustrative prototype. Uses public company context and simulated data; no connection to Marmon Holdings, Inc. systems.Marmon Holdings publicly identifies as a Berkshire Hathaway company; this prototype is independent and illustrative.Open the Marmon/Keystone OS demo
Federated Cyber Risk Command Center
Illustrative
Build a permission-scoped cyber risk command center for Marmon's autonomous companies. Use aggregate evidence, material exceptions, and accountable local owners. Include a synthetic Marmon/Keystone manufacturing scenario without pooling raw company data.
AI
I start with no access. I'll request only the evidence needed for this workspace.
Gatekeeper: Federated Security Evidence
Read-only access to simulated control attestations, material-event metadata, risk exceptions, and ownership records. Raw company logs, credentials, and operational data remain isolated.
Approve read-only access.
AI
Executed deterministic query
const summaries = await env.FEDERATED_RISK.listSummaries({ scope: "industry-group", evidence: "aggregate-only" }); const exceptions = await env.SECURITY_EXCEPTIONS.list({ status: ["review", "monitor"], includeOwner: true }); app.render(FederatedRiskView, { summaries, exceptions });
The portfolio view is ready. It centralizes evidence and decisions while each operating company retains ownership of systems, remediation, and risk acceptance.
Create a federated security operating model for Marmon. Address identity, manufacturing and operational resilience, third-party access, incident escalation, and evidence exchange while preserving local accountability.
AI
I'll use curated company context and request only the resources needed for this workspace.
Gatekeeper: Standards + Decision Records
Read-only access to simulated standards, maturity submissions, risk exceptions, and decision records. Operating-company production data and credentials are not exposed.
AI
The brief defines shared outcomes and review paths without replacing local implementation, operational judgment, or risk ownership.
Create an executive governance review for cross-company security evidence summarization, manufacturing threat triage, and third-party access review. Keep data company-scoped and include quality, privacy, cost, and human decision gates.
AI
I'll use curated company context and request only the resources needed for this workspace.
Gatekeeper: Model Registry + AI Gateway
Read-only access to simulated use-case metadata, evaluation summaries, control attestations, and aggregate spend. Prompts, credentials, and raw operating-company data are not exposed.
AI
Executed deterministic query
const candidates = await env.MODEL_REGISTRY.list({ domain: "security", include: ["owner", "evals", "risk-tier"] }); const controls = await env.AI_GATEWAY.getPolicySummary({ include: ["dlp", "budgets", "rate-limits"] }); deck.render(CyberAIReview, { candidates, controls });
The review is ready. Each candidate remains company-scoped, evaluation-gated, gateway-routed, and accountable to a human owner.
Federated Cyber Risk Command Center
Live App
Illustrative data. Every score, exception, status, and event is synthetic. Public organizational facts do not describe Marmon's security posture, systems, incidents, or performance.
11
Public industry groups
120+
Public autonomous companies
4
Synthetic exceptions
2
Illustrative approvals
Attention queue
Review: A synthetic manufacturing access exception requires a local business owner and enterprise risk reviewer.
Monitor: An illustrative third-party connection is nearing its proposed review date; evidence remains bound to the source company.
Synthetic evidence readiness by sample scope
Marmon/Keystone sample
86%
Monitor
Rail group sample
93%
Complete
Medical group sample
78%
Monitor
Foodservice Technologies sample
69%
Review
Federated Security Operating Model
Document
Illustrative planning artifact. Based on Marmon's public supported-autonomy operating model and synthetic scenarios, not internal architecture, controls, priorities, or plans.

Marmon - Federated Security Operating Model

Federated decision brief | Illustrative draft

Purpose

Align security maturity to business risk across a diverse industrial portfolio through common outcomes, permission-scoped evidence, explicit exceptions, and accountable local execution.

Jobs to be done

PriorityJourney momentRequired review
Identity and privileged-access baselineEnterprise guardrail, local implementationCompany security + risk review
Manufacturing and operational resilienceCompany-owned protection and recoveryOperations + security review
Third-party access and incident evidenceException-based portfolio reportingRisk + legal review

Operating principles

  • Start with a measurable job to be done, not a new tool.
  • Use curated company context before model knowledge.
  • The human owner remains accountable for every output.
  • An agent never receives more permission than the person using it.
Gatekeepers hold credentials, scope every resource, and preserve the observation trail when work is shared.

Delivery sequence

Map: Identify accountable local owners, critical services, data boundaries, and relevant obligations.

Pilot: Model an opt-in Marmon/Keystone scenario with synthetic evidence, isolated access, and explicit success measures.

Scale: Publish reusable controls, exception paths, and recovery measures without centralizing raw company data.

Control alignment

Local autonomy, least privilege, credential isolation, evidence provenance, legal review, operational safety, recovery testing, and human-owned risk decisions are mandatory design inputs.

Cyber & AI Governance Review
Slide Deck
Slide 1 of 4

Cyber & AI Governance Review

Marmon OS | Illustrative prototype

Slide 2 of 4

Public-context opportunity areas

Use caseStageHuman ownerNext gate
Cross-company security evidence summarizationCandidateEnterprise risk + company ownersValidate source permissions
Manufacturing threat triageCandidateLocal security + operationsTest accuracy and escalation
Third-party access reviewExploreVendor risk + legalConfirm human decision path

Illustrative candidates and synthetic controls only. This is not a statement of Marmon initiatives, models, deployments, incidents, or performance.

Slide 3 of 4

Governance scorecard

100%
Human owner
3
Evaluation suites
0
Shared raw datasets
4
Approval gates

Illustrative target-state controls.

Slide 4 of 4

Next operating loops

Context: curate terminology, policies, and quality criteria.
Evaluation: define task-specific quality, safety, and fairness tests.
Access: bind every data resource through a Gatekeeper.
Efficiency: use code for deterministic work and models only for judgment.

Integrations

Organization-wide connections for Marmon Holdings, Inc. OS. Gatekeepers hold credentials, scope resources, and log each action.

Prototype catalog. Connections and authorization states are simulated.
Gatekeepers
1
Productivity suite
Mail, calendar, documents, spreadsheets, and files
2
Collaboration
Chat, channels, meetings, and workflow notifications
3
Project tracking
Programs, epics, issues, sprints, and delivery status
4
Knowledge base
Policies, procedures, standards, and team documentation
5
Service management
IT tickets, incidents, change requests, and asset data
6
HRIS
Employee directory, organization, benefits, and lifecycle workflows
7
ERP & procurement
Finance, planning, purchasing, supply chain, and billing
8
CRM
Customer, account, partner, and service relationship data
9
Code platform
Repositories, reviews, issues, and engineering standards
10
Data platform
Governed warehouse, catalog, analytics, and reporting
11
Security operations
Alerts, cases, exposure, audit, and control evidence
12
Business intelligence
Dashboards, semantic models, and executive reporting
MCP Server Portals

Illustrative remote services available to authorized workspaces.

Security Operations
https://security.mcp.demo.example/mcp
Auto
Enterprise Data Catalog
https://data.mcp.demo.example/mcp
Needs auth
Finance & Procurement
https://finance.mcp.demo.example/mcp
Auto
People Directory
https://people.mcp.demo.example/mcp
Needs auth
Cloudflare API
https://cloudflare.mcp.demo.example/mcp
Auto

Organization Context

Shared, curated knowledge that grounds every Marmon Holdings, Inc. OS workspace. Context is versioned and read-only to agents.

Public operating context: marmon.com · Internal-looking documents below are illustrative.
md
company-strategy.md
Mission, operating model, annual priorities, and outcome definitions
md
brand-and-communications.md
Terminology, voice, accessibility, and approved communication patterns
md
security-standards.md
Identity, data protection, secure development, and incident requirements
md
responsible-ai-standard.md
AI risk tiers, evaluations, human oversight, and acceptable use
md
data-classification.md
Data categories, handling rules, retention, and sharing restrictions
md
architecture-principles.md
Technology standards, decision records, review criteria, and ownership
md
vendor-risk.md
Due diligence, contract controls, monitoring, and exit requirements
md
customer-experience.md
Journey definitions, service standards, and quality measures
md
operations-playbook.md
Service ownership, runbooks, escalation, continuity, and recovery
md
finance-controls.md
Planning, purchasing, expense, audit, and reporting procedures
md
people-policies.md
Hiring, onboarding, performance, leave, and workplace guidance
md
legal-and-compliance.md
Review paths, records, privacy, accessibility, and regulatory obligations

Skills

Reusable workflows for every function. The human requester owns the result.

NameDescriptionGroupSource
meeting-prepBuild an agenda and briefing from authorized calendar, CRM, and document contextGeneralShared library
weekly-operating-reviewCreate a cross-functional summary with decisions, owners, and open risksGeneralShared library
incident-responseAssemble evidence, draft updates, and preserve human approval for containmentSecurityShared library
vendor-risk-reviewCompare due-diligence evidence with security and privacy standardsSecurityShared library
control-evidence-packMap authorized evidence to control requirements and identify gapsSecurityShared library
architecture-reviewReview a proposal against architecture principles and decision criteriaIT & ArchitectureShared library
change-impactMap dependencies, affected services, stakeholders, and rollback requirementsIT & ArchitectureShared library
service-health-reviewSummarize service levels, incidents, changes, and capacity risksOperationsShared library
runbook-builderTurn a procedure into a deterministic workflow with approval gatesOperationsShared library
ai-model-reviewSummarize ownership, evaluations, drift, risk tier, and release readinessData & AIShared library
data-quality-reportAssess freshness, completeness, lineage, and policy complianceData & AIShared library
budget-varianceCompare actuals with plan and draft a finance-reviewed variance narrativeFinanceShared library
procurement-briefSummarize requirements, alternatives, risk, and approval statusFinanceShared library
job-descriptionDraft an accessible role description from approved job architectureHRShared library
onboarding-planCreate a role-based onboarding plan without expanding system permissionsHRShared library
contract-intakeExtract terms, route issues, and prepare a legal review checklistLegalShared library
privacy-assessmentMap a proposed workflow to data categories and privacy obligationsLegalShared library
account-briefCreate a customer briefing from authorized CRM and public informationSalesShared library
proposal-draftBuild a first draft using approved claims, pricing, and brand contextSalesShared library
executive-updateTurn project evidence into a concise decision-oriented updateGeneralShared library

Profile

Illustrative account information for this public prototype.

Demo User
No personal information is stored
Display name
Demo User
User ID
demo.user@example.com

AI Gateway

Illustrative demo data. Visibility and controls across every AI provider Marmon Holdings, Inc. uses — one console.

Requests
128,400
▲ 11% vs last mo
Tokens
342M
▲ 8% vs last mo
Est. spend
$9,120
76% of budget
Cache-hit
27%
▲ saves ~$2.4k
Error rate
0.6%
▼ 0.2 pts
p50 latency
480 ms
across providers

Models in Use

This month
ModelRouteTokensSpendSharep50 latency
Llama 3.3 70BWorkers AI156M$2,140310 ms
Claudevia AI Gateway98M$3,980720 ms
GPT-4ovia AI Gateway61M$2,510640 ms
Workers AI embeddings (bge)Workers AI27M$19040 ms

Spend vs. Budget

9 days remaining
$9,120spent of $12,000 cap
76%
On track · ~$2,880 left with 9 days
Top Users
Demo User 0142M tok $1,180
Demo User 0231M tok $960
Demo User 0328M tok $840
Demo User 0422M tok $610

Usage by Workspace / Team

342M tokens total
AI Enablement
121M tokens · $3,240
Platform Engineering
89M tokens · $2,460
Customer Experience
62M tokens · $1,510
Enterprise Operations
41M tokens · $1,020
Security & Compliance
29M tokens · $890
Model observability & controls powered by Cloudflare AI Gateway

Governance

Guardrails enforced by Gatekeepers + AI Gateway, with resource-scoped access, audit trails, and human approval.

Per-team allowed models

Restrict which providers each workspace can call.

Llama 3.3ClaudeGPT-4o+ embeddings

Monthly spend caps

Hard limits per team; agents stop before overrun.

Data & AI $4,000Platform $3,000

PII redaction

Strip sensitive fields from prompts before they leave.

Enabled

Prompt / response logging

Full request logs retained for audit & review.

Enabled · 90-day retention

Rate limits

Per-team request ceilings to protect budgets.

600 req / min|burst 1,000

Raise Data & AI cap to $6,000

Change queued by an agent — needs a human sign-off.

Requires approval

AI Gateway Explorer

Explore aggregate model traffic for This month.

4 models
ModelRouteTokensSpendSharep50
Llama 3.3 70BWorkers AI156M$2,14042%310 ms
ClaudeAI Gateway98M$3,98024%720 ms
GPT-4oAI Gateway61M$2,51018%640 ms
Workers AI embeddings (bge)Workers AI27M$19016%40 ms

Review spend cap change

AI Enablement · Monthly spend cap

Current cap$4,000
Requested cap$6,000

Change queued by an agent — needs a human sign-off. Approval updates this demo for the current session only.