Trust Center: How Rovixal Stays Honest

Transparency builds trust. This page is a single source of truth for how Rovixal secures your data, prevents hallucination, defends against adversarial attacks, and ensures AI responses are grounded in your documentation and verifiable.

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Adversarial tests
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Attack dimensions
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Evaluation runners
Citation verification available
RAG-grounded responses

Deploy in under 10 minutes.* Trust infrastructure is built in from the start — not bolted on later.

*10 minutes = basic deploy (connect 1 source + embed widget). Advanced rollout (policies, escalation tuning, QA) may take longer.

Security Architecture

Four independent systems work together to prevent hallucination and ensure responses are accurate, sourced, and verifiable.

Citation Verification Pipeline

Claims in RAG-grounded responses are traced back to specific sections of your documentation. Low-confidence responses are flagged and can trigger automatic escalation to a human agent.

Confidence Scoring

Every response includes a confidence score (0-1) based on semantic similarity to source documents. Low-confidence responses are flagged and can trigger automatic escalation to human agents.

Source Authority Weighting

Not all documentation is equal. Rovixal supports three authority levels (PRIMARY, SECONDARY, REFERENCE) so official docs are weighted higher than informal notes in answer generation.

Freshness Tracking

Documents are tagged as CURRENT, AGING, or STALE based on their last update. Stale content is deprioritized in search results to prevent outdated information from reaching customers.

AI Safety Framework

Every Rovixal deployment is tested against 55 adversarial attacks across 5 dimensions. These tests run automatically in CI/CD and block deployment if any test fails.

Prompt Injection

System override attempts, delimiter attacks, role hijacking, encoded payloads, and identity disclosure.

Retrieval Edge Cases

Cross-tenant data isolation tests, authority bypass attempts, and source manipulation.

Confidence Failures

Fabricated citation attacks, hallucination inducement, and false confidence scoring.

Multi-Turn Manipulation

History replay attacks, mode switching across turns, and context window stuffing.

Tenant Isolation

Cross-organization data leakage prevention and tenant boundary enforcement.

If any test fails, the deployment is blocked.

Trust Score Methodology

The Rovixal Trust Score (RTS) is a weighted composite metric that gives you a single number representing your bot's reliability. It is recomputed on every deployment.

Source Grounding

How well responses are anchored to your source documents.

Citation Accuracy

Whether cited sources actually support the claims made.

Refusal Accuracy

Quality of refusals when the bot lacks sufficient information.

Hallucination Resistance

Ability to avoid fabricating information under adversarial pressure.

Injection Resistance

Defense against prompt injection and manipulation attacks.

Consistency

Same questions produce consistent answers across sessions.

Trust Score (Preview)
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Trust Score

Example score shown. Connect your knowledge sources to generate your real Trust Score.

Source Grounding
96
Hallucination Resistance
98
Citation Accuracy
95
Refusal Accuracy
88
Injection Resistance
91
Consistency
90

8 Evaluation Runners

Continuous evaluation across safety and accuracy dimensions. These runners measure your bot's performance on every deployment.

Faithfulness

Measures whether responses are grounded in source documents

Citation Accuracy

Verifies that cited sources actually support the claims made

Hallucination Resistance

Tests the model's ability to refuse making up information

Injection Resistance

Measures defense against prompt injection and manipulation attempts

Consistency

Checks that the same question gets consistent answers across sessions

Authority Compliance

Verifies that source authority levels are respected in answer generation

Freshness Compliance

Ensures stale content is deprioritized in responses

Refusal Quality

Evaluates quality and helpfulness of refusal messages when the bot can't answer

Prompt Injection Defense

Rovixal implements multiple layers of defense against prompt injection attacks — the most common vulnerability in LLM-powered applications.

Input Sanitization

Conversation history is sanitized on every turn, filtering injection markers, mode-switch patterns, and chat delimiters before they enter the context window.

Mode-Switch Detection

Multi-turn attacks that attempt to shift the bot into developer, DAN, or unrestricted mode are detected and filtered in both the current message and conversation history.

Chat Marker Stripping

Special characters and formatting that could be used to manipulate prompt boundaries are neutralized before processing.

Current-Turn Input Validation

Every user message is validated against known injection patterns before being processed by the AI engine.

Data Security

Your documentation and conversation data are protected by industry-standard security practices.

Encryption

All data encrypted at rest (AES-256) and in transit (TLS).

Tenant Isolation

Strict data isolation between organizations. Cross-tenant access is impossible by design.

No Third-Party Model Training

Your documentation and conversations are not used for third-party model training.

Audit Logging

Full audit trail of all actions: who did what, when, and on which resource.

RBAC

Role-based access control with OWNER, ADMIN, and MEMBER roles.

Compliance Dashboard

Our compliance posture at a glance. We are actively pursuing certifications to meet enterprise requirements.

SOC 2 Type IIIn Progress - Q2 2026
GDPRAligned
Data Processing AgreementAvailable
HIPAAPlanned - 2026
ISO 27001Planned - 2026

Downloadable Assets

Request or download the documents your security team needs.

Data Processing Agreement

Our standard DPA covering GDPR requirements and data handling practices.

Request DPA

Security Questionnaire

Pre-filled security questionnaire covering infrastructure, access controls, and incident response.

Request Questionnaire

Architecture Diagram

High-level architecture diagram showing data flow, encryption boundaries, and isolation layers.

Request Diagram

Rovixal vs. Unguarded AI

Generic GPT Wrapper

  • No citation verification
  • No confidence scoring
  • No injection defense
  • No mechanism to avoid guessing
  • No source weighting
  • No freshness tracking
  • No knowledge gap tracking

Rovixal

  • Citation verification available for RAG-grounded responses
  • Confidence scoring with auto-escalation
  • 55 injection defense tests
  • Hallucination resistance scoring
  • 3-tier source authority weighting
  • Document freshness tracking
  • Knowledge Gap Tracking on every plan

See our trust and safety in action.

Start with the free plan to explore citation verification, confidence scoring, and adversarial testing. Or talk to our team for an enterprise walkthrough.

Free plan includes confidence-guided responses, Adversarial Testing, and Knowledge Gap Tracking.