Bring accounting AI into enterprise control — from use-case intake to monitored release.
ZoikoLogia™ with Kriton™ helps multidisciplinary governance teams define context, control sources and providers, evaluate changes, require human decisions, preserve evidence and manage exceptions across accounting and finance workflows.
Source Authority
Approved sources, scope and effective dates remain visible.
Human Decision Rights
Consequential decisions remain with authorized people.
Evaluation Gates
Changes require evidence, review and release conditions.
Evidence Continuity
Inputs, versions, reviews, exceptions and outcomes can be traced.
Change Control
Organizations can restrict, pause, roll back and retire governed capability.
Privacy and Security
Access, provider, retention and data handling controls are visible.
Accounting AI governance extends beyond the model.
Every layer — from source authority to professional boundaries — requires explicit control, evidence, and accountable human decisions.
Use case
Purpose, population, consequence and workflow determine risk.
Govern the work being done, not only the underlying model.
Sources and evidence
Authority, rights, freshness and applicability affect answer reliability.
Source governance is a first-class control.
Ontology and context
Framework, jurisdiction, entity, period and terminology shape meaning.
Context changes the control requirement.
RAG bundles and prompts
Selection, retrieval and instructions can change outcomes.
Version and evaluate the complete answer pathway.
Model and provider
Capabilities, limitations, contracts, data handling and change notices vary.
Provider review is necessary but not sufficient.
Tools and integrations
Read/write authority can create consequential actions.
Action modes require explicit authorization and review.
Policies and reviewers
Rules, exceptions and human decisions determine release boundaries.
Accountability must be assigned and evidenced.
Monitoring and incidents
Quality can change after release.
Governance continues after deployment.
Professional obligations
Accounting, tax, audit, payroll and compliance duties remain human and jurisdiction-dependent.
Platform assistance does not replace qualified judgment.
Find your governance path.
Each discipline has distinct evidence requirements, decision rights and review obligations. Select your role to route to the right controls.
Turn principles into controlled operating decisions.
Use-case register, policy gates, exceptions and evidence
Review boundaries, obligations, mappings and human decisions.
Professional boundaries, policy evidence and limitations
Control data, providers, identity, incidents and exports.
Tenant boundaries, minimum access, provider receipts and response states
Review platform and provider evidence before commitment.
Due diligence packet, pilot, data flow and contractual evidence
Governance operating lifecycle and decision artifacts.
Every governed use case moves through explicit stages, each requiring a defined artifact, human decision gate, and evidence record.
Intake
Use-case proposal and accountable owner
Classification
Risk and context profile
Control Design
Policy and control plan
Build / Configure
Versioned system configuration
Evaluate
Evaluation plan and results
Release Decision
Review packet
Deploy
Controlled release record
Monitor
Quality, exceptions, drift, incidents
Change / Revalidate
Change impact and regression evidence
Retire
Retirement and data/evidence plan
AI governance capability system.
Connected to approved Platform and Kriton™ destinations. Each layer delivers a governance outcome with traceable evidence.
Source & Context
Source-Governed Intelligence; Accounting Ontology; RAG Source Bundles
Advisor & Workflow
Ask Accounting Questions; Learning & Practice; Workflow; Review; Admin
Evidence & Evaluation
Audit Evidence Ledger; Evaluation & Benchmarks
Human Accountability
Human Escalation; Professional Boundaries
Enterprise Integration
Enterprise Integrations
Governed evaluation and benchmarks.
Governed accounting AI in practice.
Illustrative examples using synthetic data. All scenarios are clearly labeled and do not expose customer controls, incidents or confidential evaluation results.
Enterprise finance team proposes a close assistant using approved ERP extracts and policy documents.
Confidential finance data; propose-only journal support; controller review; no autonomous posting.
Conditionally approved for one business unit with expiry and read-only integration.
No claim that the system closes the books or approves financial statements.