An Ontology Platform That Defines Data Semantics and Operational
Policies Within a Unified Framework

By defining and managing Entities, Relations, Policies, and Actions, AkasicON enables
AI to operate in a controllable manner within real business operations.

No matter how much data you have, AI systems cannot be fully operated without defined semantics and standards.

Inconsistent Definitions of Key Terms Across Systems

When key terms are defined differently across systems, confusion arises when integrating data or connecting it to AI.

Operational Rules Scattered Across Code, Documents, and Individual Know-How

When operational policies are spread across various locations, enforcing and managing them consistently becomes impossible.

Lack of Validation Criteria and Accountability for AI Recommendations

Real-world AI operations require rigorous validation and approval processes. Without those standards, AI remains stuck in experimentation.

AkasicON solves existing problems by establishing standards for data.

See how AkasicON sets those standards for yourself.

An Ontology That Serves as the Standard for Execution, Not Just Documentation.

AkasicON is a platform where defined rules are immediately applied to actual operations.

  • 1. Systematically Defining Data Semantics and Relationships Through Ontology Elements

    Clearly defines the meaning, attributes, and interrelationships of entities. Defined content supports version control for change tracking, rollback, and audit trails, ensuring consistency and stability in data operations.

  • 2. Platform-Embedded Governance That Automatically Applies Down to the DB

    Define access permissions, data usage rules, and approval processes within the platform—they are applied consistently all the way to AkasicDB without any additional configuration.

A Controlled Process Based on Validation and Approval, from AI Recommendations to Execution

In AkasicON, both AI-generated recommendations and human-entered changes go through the same review process. Execution only proceeds after change definition, difference verification, and approval.
AI Recommendation
Action plans derived by AkasicAI
Human Change
Changes entered by operators
Unified Review Process Applied
1
Define Change
Form-based
2
Verify Difference
Diff-based Review
3
Approve & Review
Authorized Review
4
Execution
Commit & Audit
Only approved changes are reflected in operations.

What-if Simulation to Assess Impact Before Execution

Instead of applying changes immediately, AkasicON first simulates their impact in virtual scenarios. You can verify which data is affected and how outcomes change before deciding whether to execute.
Proposed Changes
Adjust Policy A Thresholds
Redefine Entity Relations
Modify Approval Criteria
Instead of immediate deployment...
What-if
Virtual Scenario Simulation
VIRTUAL ENVIRONMENT
Analyze Impact Scope
Identify affected data and policies in advance
Compare Scenarios
Verify outcome changes between pre- and post-deployment
Execution Decision
Choose to apply or hold based on validation results
Apply
Hold

AkasicON: The Key Link from AI Experimentation to Real-World Operations

AkasicON assigns meaning to data prepared by AkasicIN, applies policies to AkasicDB, and provides the standards that enable AkasicAI to make decisions in a controlled environment. The reliability of the entire pipeline is built at AkasicON.
STEP 01
AkasicIN
Preparation
Collecting scattered data and standardizing it for AI utilization
STEP 02
AkasicDB
Integration
Unified storage for Vector, Graph, and SQL in one engine
STEP 03
AkasicON
Governance
Defining semantics and rules to make AI controllable
STEP 04
AkasicAI
Decision
Proposing evidence-based and validated action plans

GraphAI: A trusted AI data technology company across all industries.
GraphAI’s AI data solutions support fast and accurate enterprise decision-making.









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