CLARIXO
Product Overview

Two primary sides for AI systems, with responsibility spanning both.

CLARIXO is structured across the LLM-side and the User-side. The LLM-side includes Runtime, AgentOps, Approval, and Responsibility. The User-side includes Evidence API and Audit Workspace. Responsibility is the highest-order capability, extending across both sides while unlocking responsibility-sensitive review surfaces such as Audit Workspace.

Read Docs View Pricing View Architecture Explore Evidence API Explore Audit Workspace
What CLARIXO Is

Not a model. A two-sided product structure for AI operation, evidence, and review.

CLARIXO does not compete with model providers on raw generation. Instead, it gives teams a structured system across two primary sides: the LLM-side for runtime control, observability, approval, and Responsibility, and the User-side for Evidence API and Audit Workspace. Audit Workspace belongs to the User-side architecture, but access to it is unlocked through Responsibility on the LLM-side. Read the documentation hub, review the contract reference, and use the capability overview for the higher-level product summary.
POSITIONING

AI runtime visibility layer

CLARIXO provides a control and observability layer between application logic and external AI providers. It is designed for teams that want routing flexibility, runtime visibility, operator-ready review paths, and a cleaner execution boundary between product logic and model vendors.

OUTCOME

Visible, reviewable, and governable AI behavior

Teams can understand runtime decisions, detect drift, explain why outputs changed across execution windows, and decide when execution should move from visibility into review and governed boundary control without rebuilding application logic around each vendor.

Core Components

The four runtime layers inside CLARIXO

CLARIXO is built around four core runtime layers: Router, Guard, Runtime Memory, and Explain / Audit.
ROUTER

Request routing

Routes requests across providers, models, contexts, and fallback paths.

GUARD

Runtime guard

Surfaces drift, divergence, confidence, stability, and other runtime control signals.

RUNTIME MEMORY

Runtime windows

Tracks recent execution behavior, identity persistence, and transition history across windows.

EXPLAIN / AUDIT

Explainable review

Produces structured narratives and auditable signals for human and developer review.

Runtime Guard

The signals CLARIXO surfaces during execution

CLARIXO turns AI runtime behavior into structured signals that can be monitored, logged, explained, and acted on. For the full observability model, read the AI Runtime Observability guide. For the control layer behind those signals, also read the AI Runtime Guard guide.
Decision Delta
What changed between recent decisions or routing paths.
Drift Score
How far runtime behavior has shifted from expected control bands.
Runtime Identity
Which active execution profile currently dominates the response path.
Identity Window
How runtime identities are distributed and how transitions evolve over time.
Confidence
A structured confidence reading built from risk, stability, and drift.
Trend Strip
A compact runtime timeline for quick drift and stability inspection.
Architecture Fit

How CLARIXO fits into real systems

CLARIXO is designed to sit between application code and one or more AI providers. For a simplified visual overview, read the AI Runtime Diagram.
Application Your SaaS, workflow engine, agent, or internal tool.
→
CLARIXO Runtime Router · Guard · Runtime Memory · Explain / Audit
→
AI Providers OpenAI, Claude, DeepSeek, local models, or future provider adapters.
Before provider call Route requests, attach context, and decide fallback policy.
After provider call Evaluate output behavior, drift, confidence, and guard narratives.
Use Cases

Where CLARIXO is most useful

MULTI-MODEL

Model routing and fallback

Select providers and runtime paths without locking product behavior to a single model vendor.

AGENT SYSTEMS

Agent runtime visibility

Inspect how agents shift in identity, route decisions, and runtime stability over recent windows.

OBSERVABILITY

AI behavior monitoring

Surface drift, divergence, and confidence signals in a structured format teams can act on.

AUDIT

Explainable runtime traces

Provide readable narratives and audit-friendly logs for AI decision behavior.

USER-SIDE REVIEW SURFACE

Audit Workspace

The User-side review surface for grouped evidence reading, reviewer context, and formal case export after evidence capture, unlocked through Responsibility rather than sold standalone.

HANDOFF

Formal review and export handoff

Move from evidence records into structured case review and delivery-ready export when responsibility-sensitive workflows need a formal surface.

CLARIXO is not an AI model. It is a two-sided product structure that helps teams govern AI on the LLM-side, evidence behavior on the User-side, and move into responsibility-sensitive review through capabilities that span both sides.