Swiftask integrates advanced Guardrails to automatically filter and mask sensitive data before it reaches your AI models.
Result:
Ensure compliance in your interactions and prevent confidential data leaks while maintaining agent efficiency.
The risk of data leaks via generative AI
The growing use of LLMs in the enterprise exposes organizations to major risks: accidental transmission of customer data, financial information, or trade secrets to third-party models. Without robust security, confidentiality becomes the weakest link.
Main negative impacts:
Swiftask Guardrails act as an intelligent filter. They analyze inputs and outputs in real-time to detect, mask, or block sensitive information before it is processed.
BEFORE / AFTER
What changes with Swiftask
Without Swiftask filtering
An employee asks the AI about a client file and accidentally includes Social Security numbers or banking details. These data points are sent in plain text to the language model, creating an immediate security vulnerability.
With Swiftask Guardrails
The system instantly detects patterns of sensitive data. It automatically replaces this information with anonymized tokens (e.g., [CLIENT_NAME]) before sending the request to the AI, ensuring total confidentiality.
Implementing your security in 4 steps
STEP 1 : Define policies
Configure the types of data to filter (emails, card numbers, addresses, proprietary data) in your Swiftask dashboard.
STEP 2 : Activate Guardrails
Apply selected filters to your specific AI agents. No code is required to activate this protection layer.
STEP 3 : Real-time analysis
The filtering engine intercepts every message, identifies sensitive entities, and applies configured masking rules.
STEP 4 : Monitoring and auditing
Review security logs to verify filtering alerts and adjust your protection policies based on actual usage.
Advanced protection capabilities
Our Guardrails use Named Entity Recognition (NER) and regex pattern detection to identify risks.
Each action is contextualized and executed automatically at the right time.
Each Swiftask agent uses a dedicated identity (e.g. agent-guardrails@swiftask.ai ). You keep full visibility on every action and every sent message.
Key takeaway: The agent automates repetitive decisions and leaves high-value actions to your teams.
Why secure your agents with Swiftask
1. Simplified compliance
Easily meet GDPR requirements and internal company security policies.
2. Zero-risk approach
Prevent confidential data leaks to third-party AI models without human intervention.
3. Total flexibility
Adapt your filtering policies based on evolving business needs and data sensitivity.
4. Full transparency
Benefit from complete traceability on all blocked attempts to transmit sensitive data.
5. Confident adoption
Empower your teams to use AI with confidence, without fear of compromising critical data.
Enterprise-focused approach
Swiftask applies enterprise-grade security standards for your guardrails automations.
To learn more about compliance, visit the Swiftask governance page for detailed security architecture information.
RESULTS
Security metrics
| Metric | Before | After |
|---|---|---|
| Added latency | N/A | < 50ms |
| Sensitive data filtered | Manual risk | 100% automated |
| Security visibility | None | Full audit logs |
| Technical complexity | Complex development | No-code setup |
Take action with guardrails
Ensure compliance in your interactions and prevent confidential data leaks while maintaining agent efficiency.