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System of Record

Know every AI system the institution depends on.

Create a canonical, continuously maintained inventory of models, agents, applications, suppliers and material AI use across the institution.

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Why institutions need it

The problem is already operating inside the organisation.

Cybatar is designed for material AI activity: systems, decisions, spend and dependencies that can create institutional consequence if they remain fragmented or ungoverned.

01

AI usage spreads faster than governance teams can inventory it.

02

Business units buy AI-enabled SaaS without a common ownership record.

03

Model, agent and supplier information lives in disconnected spreadsheets and questionnaires.

04

Executives cannot answer which AI systems are material, unowned, duplicated or approaching renewal.

What Cybatar provides

Institutional capability, not another isolated dashboard.

01

Universal AI Registry

Maintain one institutional inventory across models, agents, applications, vendors and internal AI systems.

02

AI Passports

Give every material AI system an accountable dossier for ownership, purpose, lifecycle, risk, controls, evidence and economics.

03

Discovery & Shadow AI

Surface candidate AI usage from configured sources and route it into institutional review rather than leaving it invisible.

04

Lifecycle & Ownership

Track proposed, approved, deployed, restricted and retired systems with accountable owners and decision history.

Institutional outcomes

What changes when ai estate becomes part of the operating model.

01One canonical AI inventory
02Fewer unowned systems
03Faster due diligence
04Clear lifecycle accountability
Connected by design

The control plane should sit across the AI estate—not require the estate to move into one vendor.

Cybatar is designed to connect institutional records, providers and workflows while preserving a common governance and evidence model.

Cloud and AI providers SaaS and supplier records Identity and workspace systems Procurement and contract data
The wider platform

Every operating layer works against the same AI estate.

View platform architecture →
System of ControlAI Control

Route material AI activity through intake, authorisation, policy, regulatory obligations, review and exception handling before risk becomes operational dependency.

 System of EvidenceAI Evidence

Preserve interaction, decision, source, calculation, tool, moderation and review evidence so material AI facts can be reconstructed and independently inspected.

 Continuous AssuranceAI Assurance

Combine model governance, review queues, moderation, incidents, controls and ongoing assurance so risk management does not stop at initial approval.

 AI EconomicsAI Economics

Connect provider usage, token spend, infrastructure, suppliers, programmes and validated business outcomes into one economic view of the AI estate.

 System of CommerceAI Commerce

Bring supplier assurance, procurement, contracts, compute, capacity and commercial terms into the same operating model as AI governance and economics.

 Executive Control TowerExecutive Control Tower

Bring portfolio, risk, investment, evidence, economics and decision queues together so executive teams can govern AI as an institutional estate rather than a collection of projects.
Next step

Request an AI Estate Assessment

Bring the current operating context. Cybatar will structure the estate, decision problem, evidence requirement and next practical step.

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