Intent-First AI Guardrails for Regulated Enterprises

1. Executive Summary

As enterprises move AI from experimentation into production, the primary risk has shifted. It is no longer about model accuracy or intelligence.
The dominant risk is unintentional exposure of regulated, sensitive, or proprietary data at the moment humans interact with AI systems.
Most AI governance solutions focus on controlling outputs or filtering responses after generation. By then, data has already crossed system boundaries, introducing regulatory, legal, and audit exposure.
Cortx Guardrails introduce an intent-first AI governance model, enforcing policy before data reaches agents, tools, or models, across every channel where AI interaction occurs.

This is not content moderation.
This is end-to-end AI interaction control.

2. Where AI Risk Actually Begins

2.1 The Flawed Assumption in Traditional AI Governance

Most AI governance frameworks assume risk begins when:

  • A model generates output

  • A tool retrieves sensitive data

  • A backend moderation service flags content

This assumption is incorrect.

Once data reaches a model or backend service, exposure has already occurred.

2.2 Intent as the Primary Risk Surface

AI risk begins at the moment human intent is expressed, including:

  • Typed chat messages

  • Voice input

  • Streaming drafts

  • Uploaded documents

  • Agent instructions

  • Enterprise chat messages

  • API-triggered workflows

Cortx Guardrails are designed to stop risk before this intent crosses any system boundary.

3. The Cortx Guardrails Architecture

3.1 Defense-in-Depth Model

Cortx enforces governance using a six-layer defense-in-depth architecture, ensuring no single control failure results in exposure.

Invariant:  No inbound content — regardless of source — can reach an agent, tool, or model without passing through guardrails.

LayerPurposeCoverage
Client-Side GuardrailsStop sensitive data at intentWeb, voice, files
Channel Middleware GuardrailsProtect messaging platformsTeams, Slack, APIs
Prompt GuardrailsInstruction governanceAgent prompts
Tool & Retrieval GuardrailsAuthorization enforcementDBs, APIs, RAG
Model Boundary GuardrailsLLM-aware controlsPublic vs private
Response GuardrailsOutput safetyAI responses

3.2 Unified Control Plane

Cortx Guardrails operate as a single unified AI control plane across all ingress and egress channels.

Ingress Sources

  • Web & mobile clients

  • Voice interfaces

  • File uploads

  • Microsoft Teams & Slack

  • API-triggered workflows

All inbound intent flows through the same policies, detection logic, and audit pipeline, ensuring deterministic enforcement.

4. Layer 1 – Client-Side Guardrails

Client-side enforcement establishes the browser and device as the primary trust boundary, where raw intent first appears.

Intercepted at this layer:

  • Typed and pasted text

  • Streaming drafts

  • Voice transcripts before transmission

  • Files before upload

Performance Characteristics

OperationLatencyMemory
ML Model Load2–5s (one-time)~420MB
ML Inference100–200msMinimal
Rule-Based Scan<5ms<1MB
Streaming Analysis<50ms<10MB
File Scan (1MB)<500msMinimal
All scanning occurs locally with zero data exfiltration.

5. Layer 2 – Channel Middleware Guardrails

Enterprise messaging platforms require protection beyond the browser.

Cortx middleware guardrails enforce the same policies for:

  • Microsoft Teams

  • Slack

  • Webhooks

  • API-driven events

Messages, attachments, edits, and context are inspected before any AI invocation.

6. Layer 3 – Prompt Guardrails

Prompts are treated as governed instructions, not free-form input.

Before prompts are saved or executed, they are:

  • Validated against policy

  • Checked for prohibited intent

  • Evaluated for role-based authorization

  • Audited for compliance restrictions

Agents are constrained executors of user intent.

7. Layer 4 – Tool & Retrieval Guardrails

Tools never act independently.

Every tool invocation is evaluated using:

  • User identity

  • Role and group membership

  • Workspace scope

  • Tool-specific policy

Retrieval pipelines enforce:

  • Least-privilege data access

  • Row- and column-level filtering

  • Redaction or summarization

8. Layer 5 – Model Boundary Guardrails

Public vs Private LLM Risk

Model TypeRisk ProfileData Handling
On-Prem / Private LLMControlledRich context allowed
VPC-Hosted LLMRestrictedLimited context
Public SaaS LLMHighMasked or summarized only

Cortx dynamically adjusts:

  • Context depth

  • Masking rules

  • Retrieval scope

  • Model eligibility

Public models never receive regulated data unless explicitly permitted.

9. Layer 6 – Response Guardrails

Auto-Redaction

Before responses are delivered, Cortx scans outputs to detect:

  • Echoed sensitive inputs

  • Hallucinated identifiers

  • Prohibited claims

Actions include:

  • Redaction

  • Rewriting

  • Warning annotation

  • Full blocking

10. Advanced Detection Capabilities

Context-Aware Detection

Cortx evaluates conversation history, enabling:

  • Test vs production intent detection

  • Placeholder recognition

  • Reduced false positives

  • Adaptive risk scoring

11. Auditability & Compliance

11.1 Tamper-Resistant Audit Trail

Every decision generates an immutable audit event containing:

  • Event ID

  • Timestamp (ms precision)

  • User & session identity

  • Channel

  • Detected patterns

  • Decision

  • Override justification (if any)

11.2 Tamper Detection

Audit records are secured using SHA-256 hashing.
Any modification is cryptographically detectable.

11.3 Export Capabilities

Audit logs can be exported as:

  • CSV (compliance officers)

  • JSON (SIEM & automation)

No sensitive content is centrally stored.

12. Regulatory Alignment

Compliance Mapping

Cortx Guardrails support:

  • SEC Rule 10b-5

  • SEC Reg FD

  • FINRA 5320 & 2210

  • GLBA

  • HIPAA

  • GDPR / CPRA / PIPEDA

  • SOC 2 Type II

  • PCI DSS

Each regulation maps to explicit technical controls.

13. User Experience Controls

13.1 Remember Preferences

Users may persist preferences for non-mandatory rules, reducing friction while preserving compliance.
Mandatory high-severity rules cannot be bypassed.

14. Integration & Extensibility

14.1 API Integration

bash

POST /api/guardrails/scan
{
“text”: “Message to analyze”,
“channel”: “api”,
“userId”: “user123”,
“context”: [“Previous message”]
}

14.2 Custom Pattern Addition

Enterprises can define:

  • Regex patterns

  • Keywords

  • Contextual rules

  • Severity levels

  • Channel-specific enforcement

14.3 Policy Customization

Configurable controls include:

  • Block / warn thresholds

  • Mandatory vs optional rules

  • Role-based policies

  • Channel-specific enforcement

15. Performance & Scalability

Latency Benchmarks

OperationP50P95P99
Client Scan2ms5ms10ms
ML Inference100ms180ms220ms
File Scan300ms480ms650ms
Batch (100 msgs)150ms280ms400ms

16. Deployment & Rollout

Implementation Timeline

  • Weeks 1–2: Policy design & planning

  • Weeks 3–4: Pilot deployment

  • Weeks 5–6: Expansion & tuning

  • Weeks 7–8: Full rollout

  • Week 9+: Optimization & audits

17. Conclusion

Cortx Guardrails enforce AI policy from human intent through model response — controlling what users can ask, what agents can do, what tools can retrieve, what models can see, and what responses can say.
This is not reactive moderation. This is enterprise-grade AI governance by design.

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