Intent & context
The interface first determines user intent and relevant local context.
QAVIRIO INTELLIGENCE PLATFORM · ACTIVE R&D
Qavirio AI · QAI
Qavirio’s intelligence technology layer: conversation, knowledge, research, tools and controlled automation under explicit boundaries.
QAI is the intelligence platform layer Qavirio is developing for conversation, knowledge, live research, pattern formation, artifacts and later controlled tool use. Sovereign, Companion, Autolearn, ARENA and Guardian have separate responsibilities and authority boundaries. The goal is one reusable intelligence core for Qavirio products and ultimately direct users, without building an unrestricted black-box actor.
STATUSACTIVE R&D · PLATFORM UNDER DEVELOPMENT
REAL INTERFACE
Real R&D interfaces show both conversational and defensive research directions.
Large product views show how information, roles and actions actually work together.
FROM PROBLEM TO WORKFLOW
Many AI workflows are powerful but difficult to bound around data, source use, network access and execution authority.
QAI explores a different foundation: local runtime where possible, explicit source and web paths, evidence/confidence where relevant and defensive intelligence without automatic production authority.
- Local independence where practical
- Source and web access as explicit capability
- Keep evidence, confidence and conflicts visible
- Separate analysis from production authority
Local knowledge
Available local knowledge, artifacts and prior context are used in a controlled way.
Controlled source/web route
External information is used only when an allowed route requires it.
Compose & qualify
Answer or analysis is composed with confidence/source rules where that route supports them.
Guardian / Watcher
Defensive observations can be correlated locally into incidents and advisory without automatic blocking or production write.
Human / owner boundary
Experiments, proposals or advisories do not flow freely into production; explicit review and separate productisation remain required.
CAPABILITIES
What the system actually does.
A capability only matters when it makes a real task, decision or hand-off simpler and controllable.
Companion
Multilingual local conversation and knowledge interface with practical artifact and source routes.
Controlled web intelligence
Internet or source use is an explicit route, not implicit unrestricted network authority.
Guardian / Watcher
Observes, correlates, scores and advises defensively; automatic blocking and production write remain off unless a separate future capability explicitly qualifies them.
Evolution Core
Isolated experimental space for experience, reflection and controlled improvement proposals.
Local knowledge & artifacts
Local sources and generated artifacts can remain in the local context without default cloud-first dependence.
Safety boundaries
R&D makes authority, network paths and advisory-only status visible so experiment and production do not blur together.
PEOPLE & ROLES
The interface follows responsibility.
Knowledge / research user
Uses Companion for questions, local knowledge, sources and artifacts.
Defensive analyst
Reviews Guardian/Watcher status, incidents, advisories and audit without automatic production authority.
R&D / engineering
Tests routes, models, local runtime, safety boundaries and productisability.
USE CASESCOMPANION ARTIFACT GUARDIAN
Designed for real scenarios.
Local knowledge question
A user asks for an explanation or summary; QAI uses local context and can open a controlled source route when needed.
From answer to artifact
Companion can turn selected output into practical artifacts without turning the conversation core into unrestricted automation.
Defensive advisory
Watcher correlates observations; Guardian shows priority and recommendation while owner review and advisory-only boundaries remain visible.
INSIDE THE PRODUCT
QAI is designed as a platform layer, not as a single chatbot.
The current architecture combines Sovereign, Companion and Autolearn on a Linux VPS with local knowledge, research and oversight layers. The goal is to reuse the same intelligence in Qavirio products and as a usable assistant, without automatically granting production authority to every capability.
Orchestration
Companion chooses between local knowledge, controlled research and specialised routes; jobs receive budgets, timeouts, retries and audit context.
Knowledge with provenance
QKB/Vault, Source Registry and Knowledge Graph concepts preserve not only conclusions but source provenance, freshness, contradictions and learning events.
Capabilities stay bounded
Web, models, artifacts, code generation and future actions each need their own route and authority contract. The current runtime does not yet fully support every intended capability.
VERIFIED TECHNOLOGY
We only name components that are demonstrably used in this product line or implementation.
Companion and service code runs in a dedicated Python virtual environment.
24/7 Linux runtime for Sovereign, Companion and Autolearn.
Separate services with autostart and restart policy.
Compact knowledge blocks, claims, relationships and provenance as target architecture.
Red/Blue/Judge/Observer remain isolated from production write.
Policy, anomaly/behaviour oversight, action gating and audit as a separate layer.
ENGINEERING & TRUST
Technology is strongest when its boundaries are visible.
Local-first core with separate routes for knowledge, web, defensive intelligence and experimentation.
QAI is not a monolithic “AI does everything” architecture. Companion, knowledge sources, controlled web access, Guardian/Watcher and Evolution Core have their own contracts and boundaries. Only an explicitly allowed route may use external access or a more advanced capability.
Security & data
- Local-first as default design where practical
- External access explicit per route
- Guardian advisory-only in shown interface
- No automatic production write by default
- Keep R&D and production boundaries visible
Sources and models are capabilities with their own boundary.
QAI can explore local knowledge sources and controlled external information paths. Availability of a model, source or web route does not mean it is always used or receives production authority.
Deployment & operations
Local R&D runtime
Primary current research environment on local hardware.
Controlled connected mode
External source/model access only for explicit routes with visible network policy.
No production deployment claim
Any future product baseline requires separate scope, threat model, security, operations and acceptance.
PRODUCT STATUS
ACTIVE R&D · PLATFORM UNDER DEVELOPMENT
Sovereign, Companion and Autolearn run as active services, but QAI is not yet a finished public production product. The interfaces shown are real R&D environments; capabilities are only presented as available after functional and safety validation.
R&D status and productisation
QAI runs as an active research runtime but is not yet a finished public software product. Capabilities such as reliable code/script generation, tool use and controlled actions are only presented as available after functional and safety validation.
DISCUSS THE USE CASE
QAI technology briefing →Discuss QAI as an R&D platform, not a finished software package.
A briefing can show Companion, Guardian/Watcher, local runtime, knowledge routes and safety boundaries. Any commercial application then begins with a separate product and assurance analysis.