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Home/Capabilities/AI Safety
Capability #14 · Trust

AI Safety & Guardrails

Prompt injection protection, policy enforcement, toxicity filtering, hallucination mitigation, secure tool access and data isolation.

Prompt-injection defensePolicy-as-codeToxicity & PIIGrounding
#14
Capability
Trust
Category
Live
In production
Day 1
Available
Trust

AI Safety & Guardrails

Prompt injection protection, policy enforcement, toxicity filtering, hallucination mitigation, secure tool access and data isolation.

  • Prompt-injection defense
  • Policy-as-code enforcement
  • Toxicity and PII filtering
  • Citation-anchored answers
  • Scoped tool access and data isolation
RBAC Guardrails Isolation Audit SOC 2 ISO 27001 GDPR HIPAA
How it works

Six pillars of AI Safety & Guardrails.

Each pillar can be enabled, configured and audited independently.

Prompt-injection defense

Out-of-model enforcement.

Policy-as-code

OPA / Rego compatible.

Toxicity & PII

Output filtering and redaction.

Grounding

Citation-anchored answers.

Tool scoping

Per-agent allowlists.

Isolation

Per-tenant, per-team data isolation.

How it works

Safety enforced at every layer.

Safety isn't a prompt. It's a stack — defense-in-depth from input parsing through tool execution to output review.

1

Input filtering

Prompt injection patterns, PII, jailbreak attempts and out-of-policy requests are detected and either rewritten, denied, or escalated.

2

Reasoning constraints

The reasoning engine operates within explicit role and policy constraints — what an agent may consider, propose, or call.

3

Tool sandboxing

Tool calls run with least-privilege scopes, mTLS, and per-call policy checks. Destructive operations require human approval.

4

Output review

Generated text and structured outputs are checked for hallucinations, toxicity, leaked secrets, and policy violations before delivery.

5

Feedback loop

Every blocked attempt is logged, classified, and fed back to improve guardrails — without retraining base models.

Outcomes

What customers measurably ship with this capability.

Real numbers from production deployments — across banking, healthcare, telco, manufacturing and the public sector.

Multi-layer
Defense in depth
0
Tolerance for leaks
Real-time
Policy checks
Tunable
Per role & context
Time-to-value

Hallucinations bounded by retrieval

Agents cite sources from the policy-aware RAG layer. Answers without grounding either trigger retrieval or are rejected — no plausible-but-wrong drift to production.

Risk reduction

Adversarial-tested

Built-in red-team prompts and ongoing adversarial evaluation catch new injection patterns before they reach your users.

Industry use cases

How AI safety & guardrails shows up in production.

Six concrete patterns from regulated enterprises across financial services, healthcare, telecom, public sector, energy and manufacturing.

Banking

Customer-facing guardrails

Agents will not give investment advice, will not reveal internal account flags, and will not run trades outside policy.

Insurance

PHI / PII protection

Agents redact protected attributes before any outbound LLM call, with strict allow-lists per regulator.

Healthcare

Clinical advice gating

Clinical recommendations are bounded by formulary, contraindication and dose-range checks, then routed for human approval.

Telecom

Fraud-resistant flows

Account-change requests require multi-factor confirmation and pattern checks before execution.

Public sector

Determination integrity

Benefit-determination agents cannot bypass eligibility rules; every denial includes a citation.

Manufacturing

Operational technology boundary

Agents cannot issue commands to PLCs / SCADA without explicit, time-bounded human authorization.

Why xyner

Prompt-only safety vs. platform safety.

Telling a model 'don't do bad things' is necessary but radically insufficient. Production safety is a stack.

Dimension
Without xyner
With xyner
Prompt injection
Best-effort filter at one layer
Detected at input, reasoning, tool, and output layers
PII / PHI leakage
Hope the model doesn't
Redaction enforced before any outbound call
Hallucinations
Detected by your users
Retrieval-grounded with confidence gates
Tool misuse
Implicit scopes
Least-privilege, approval-gated, audited
Toxicity / abuse
One-shot filter
Policy library with per-context tuning
New attack patterns
React after incident
Continuous adversarial testing
xyner' guardrails are the first I've seen that survive a real red-team.
CISO · Multinational Bank
FAQ

Common questions, straight answers.

How do you defend against prompt injection?

Outside-the-model controls — policy, allowlists, output validation, redaction, and approval gates.

Do you red-team releases?

Yes. Every release goes through an adversarial red-team suite.

How quickly can we adopt this capability?

Most customers adopt new capabilities in 2-4 weeks through starter packs and onboarding workshops.

Does this require new infrastructure?

No. The capability runs on your existing xyner deployment — cloud, hybrid, on-prem or sovereign.

Do you provide migration help?

Yes — our customer success team and partners deliver guided migrations and pilots.

Get started

Ready to put autonomous agents to work?

See xyner in your environment with a guided executive demo.

Request a demo Contact us
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