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Klaritee Architecture Overview

Model-Agnostic Determinism

Same Input Same Verdict Every Time

THE CHALLENGE

Wrapper Limitations

AI wrappers send prompts to models and return outputs directly, with limited control over how decisions are made. This creates three critical problems: outputs vary between runs, results change when models update, and there is no audit trail for compliance. When the underlying model changes, the product breaks.

01

Variable Outputs

Outputs vary between runs

02

Model Dependency

Results change when models update

03

No Audit Trail

No audit trail for compliance

THE SOLUTION

The Klaritee Approach

Klaritee inverts the architecture. Our deterministic engine owns the logic, the LLM is just an extraction layer. The verdict, scores, and reason codes are computed by our proprietary rules, not generated by AI. 

OLD WAY: AI WRAPPER Prompt LLM KLARITEE WAY Deterministic Engine Architecture Inversion Any LLM OLD WAY: AI WRAPPER Prompt → LLM KLARITEE WAY Deterministic Engine Works with Any LLM
CORE PRINCIPLE
The model can change, our output cannot.

SYSTEM DESIGN

Architecture

Layer 1

KLARITEE ENGINE

(Proprietary Logic)

Layer 2

ADAPTER LAYER

(Normalization)

Layer 3

ANY LLM

(Interchangeable)

Input Engine scores & constrains Deterministic Output

PROPRIETARY ASSETS

What Klaritee Owns

Visionary applications emerging from interpretive geometry research

 

01

Deterministic Scoring Engine

 Propritary math that produces consistent scores regardless of which model extracts the underlying data.

02

Reason Code Library

Auditable, explainable codes that map findings to specific business logic, not AI hallucinations.

03

Evidence Extraction Rules

 Structured schemas that constrain what the model can return, preventing drift and ensuring consistency.

04

Consistency Verification

 Simply, we prove it works.

VALIDATION

Testing

We’ve ran hundreds of identical inputs through OpenAI, Anthropic, Gemini, and Grok. Result: identical verdicts, identical scores, identical reason codes. The LLM didn’t determine the outcome, our engine did.

 

OpenAI
Gemini
Grok
“The LLM didn’t determine the outcome, our engine did.

IMPACT

Trajectory

Compliance Ready

Full audit trail. Every verdict traceable to specific rules.

Model Independent

Swap any AI model. Zero impact on outputs.

Defensible IP

The logic is ours. Model Agnostic. Not Rented.

Input Engine scores & constrains Deterministic Output