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AI MODELS

Technology Finance Intelligence Models.

The operational context layer behind faster, more consistent, more defensible technology finance decisions. TFIM is the framework Yarken is building so its AI systems can reason using your organization's structures, rules, taxonomies, and operational workflows. Not generic assumptions.

GOVERNANCE MODELS
Approval structures · Policy controls · Exception handling
CLOUD & TECHNOLOGY MODELS
Platforms · Applications · Infrastructure · Ownership
VENDOR & CONTRACT MODELS
Vendors · Contracts · Services · Commercial obligations
FINANCIAL & COST MODELS
Cost pools · Towers · Allocation · Chargeback
TFIM CORE
Technology Finance Intelligence Model
 ENTERPRISE AI REQUIRES OPERATIONAL CONTEXT

Every organization operates differently.

Different financial structures, allocation methodologies, governance frameworks, terminology, operating models, and delivery processes. Without this context, AI systems generate inconsistent and low-trust outputs. TFIM is being built to operationalize this knowledge into reusable intelligence.

 

Financial & cost models

Cost pools, tower structures, allocation methodologies, chargeback logic, product attribution, and financial hierarchies.

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Vendor & contract models

Vendors, contracts, services, commercial obligations, and procurement structures — mapped and traversable.

 
 
 

Cloud & technology models

Cloud platforms, applications, infrastructure services, resource ownership, and technology domains.

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Governance models

Approval structures, policy controls, operational standards, and exception handling processes.

 CONTINUOUS ORGANIZATIONAL LEARNING

Operational expertise should become a reusable strategic asset.

TFIM is being built so organisations can convert consultant expertise, operational playbooks, mapping methodologies, governance logic, delivery standards, and analytical decisions into reusable operational intelligence.

Over time, the platform is intended to become faster to deploy, more accurate, more explainable, and more aligned to operational reality.

•Consultant expertise converted to reusable intelligence
•Operational playbooks structured for execution
•Mapping methodologies preserved and applied consistently
•Governance logic captured and enforced at scale
•Delivery standards embedded into every workflow
•Analytical decisions made explainable and repeatable

"Generic AI produces generic outputs. Yarken grounds operational reasoning using your organization's operating model, not generic assumptions."

Yarken — TFIM design principle

More to explore

AI Engine

AI Models

Specialist agents coordinating enterprise financial operations.
Yarken's AI Engine breaks complex TBM and FinOps workflows into focused specialist agents: cloud, vendor, allocation, governance, reporting. An orchestration layer runs them consistently, with human approval at every consequential step.

AI Platform

AI Platform

A connected operational graph agents can traverse in real time.
Every connector, API, and capability registered as a semantic tool. Agents discover and select tools mid-workflow, traversing relationships across vendors, contracts, cost centres, and cloud resources without manual wiring.

AI Labs

AI Labs

Researching the operational layer that comes after the copilot.
AI Labs explores agentic workflows, knowledge-grounded intelligence, workflow formalization, and trust frameworks, studying how analyst expertise and governance decisions become structured, reusable operational intelligence at enterprise scale.

See how TFIM maps to your environment.