Data & AI Security

Safe AI, in production.

ArthaShield runs AI where the stakes are real. Two controls make that safe for regulated institutions: an LLM-as-Judge layer that checks every output, and an agentic security perimeter that bounds what agents can do.

Control 01

LLM-as-Judge, in production

No AI output reaches a user or a workflow unchecked. Every recommendation, classification and summary ArthaShield produces is scored by an independent judge model against a versioned rubric before it is shown or acted on.

1

Generate

A task model produces an output, grounded in evidence from the knowledge graph.

2

Judge

A separate judge scores it on groundedness, policy compliance, scope and PII leakage.

3

Gate

Pass → released with its score. Borderline or fail → quarantined for a human, never auto-actioned.

4

Learn

Judgments are logged and sampled against human reviewers; rubrics ship only through an eval gate.

Independence

The judge is a separate model and prompt from the generator — it never grades its own work.

Rubric, not vibes

Scoring is against explicit, versioned criteria, so a verdict can be explained and reproduced.

Fail closed

Low-confidence outputs are held for review, not shipped. Safety beats coverage.

Evidence-bound & audited

Groundedness ties each claim to source data; every judgment is logged with score and rationale.

Control 02

Agentic security, in production

ArthaShield's agents read context and propose actions, but they operate inside a controlled perimeter. Autonomy is bounded by least privilege, human approval and a complete audit trail.

Task Agent reasons Guardrails Human approval Sandboxed tool Audit log

Least-privilege tools

Each agent is granted only the scoped tools its task needs. Nothing is ambient or standing.

Human-in-the-loop gates

State-changing actions — file a report, update a case, trigger a workflow — require explicit approval.

Prompt-injection defense

Instructions come only from the user or task. Content read from documents, tickets and the web is data, never commands.

Sandboxed execution

Tools run in isolated contexts with rate limits and circuit breakers to contain runaway behaviour.

Schema-validated I/O

Agent outputs are validated against strict schemas before they ever touch a system of record.

Secrets isolation & audit

Credentials are never exposed to the model; redaction at the boundary; every action is logged immutably.

Aligned to recognised frameworks

These controls are designed to map onto the security and AI-governance standards our customers are audited against.

SOC 2 ISO/IEC 27001 NIST AI RMF ISO/IEC 42001

This page describes ArthaShield's security architecture and approach. Specific certifications and assurances are shared under NDA on request.