AI Guardrails: Preventing Hallucination, Injection, and Data Leaks
Enterprise AI needs safety nets. ZenSearch's guardrails system validates both inputs and outputs to catch prompt injection, hallucination, PII exposure, and toxic content.
AI guardrails are automated checks applied before a prompt reaches the model and after the response comes back. In ZenSearch they catch prompt injection and PII in inputs, and hallucinations unsupported by retrieved sources, toxicity, and off-topic drift in outputs — with per-team sensitivity thresholds and a complete audit log for compliance.
Deploying AI in the enterprise without guardrails is like deploying a web application without input validation. It might work most of the time, but the failures are costly. ZenSearch includes a comprehensive guardrails system that validates both inputs and outputs.
Input Guardrails
Before a query reaches the search or chat pipeline, input guardrails check for:
Prompt Injection — Detects attempts to override system instructions or extract internal prompts. Uses both pattern matching and AI-based classification.
Content Moderation — Flags queries containing harmful, offensive, or inappropriate content. Configurable severity thresholds per team.
PII Detection — Identifies personally identifiable information (SSNs, credit card numbers, phone numbers) in queries. Can block or redact before processing.
Length Validation — Prevents token-stuffing attacks by enforcing maximum query lengths with accurate token counting.
Output Guardrails
After the AI generates a response, output guardrails verify quality and safety:
Hallucination Detection — Three detection modes:
- Lexical — Checks that response claims appear in the retrieved source documents
- Semantic — Uses embedding similarity to catch paraphrased fabrications
- Hybrid — Combines both for maximum coverage
Source Verification — Ensures cited sources actually exist and contain the claimed information. Strips citations that can't be verified.
Toxicity Filtering — Scans generated responses for toxic, biased, or inappropriate content.
Relevance Checking — Validates that the response actually addresses the user's question rather than tangentially related content.
Per-Team Configuration
Guardrail settings are configurable per team. Teams can enable or disable individual guardrails and tune sensitivity thresholds without any downtime. Changes take effect within seconds.
Audit Trail
Every guardrail violation is logged with the triggering content, the rule that fired, and the action taken (blocked, modified, or flagged). This audit trail is essential for compliance reporting and for tuning guardrail sensitivity over time.