Skill UI

This comprehensive guide covers the entire data lifecycle management for Granola meeting notes. Users learn how to export data using local cache scripts or Enterprise APIs, set customized data retention policies, and handle data subject access requests (SARs). It is essential for maintaining GDPR/CCPA compliance and ensuring data portability.

This guide details the comprehensive setup of Granola for large-scale, multi-departmental enterprise environments. It covers creating isolated workspaces (e.g., Engineering, HR, Sales), integrating Identity Providers using SSO/SCIM, and implementing granular compliance controls (data retention, external sharing, MFA) to ensure data security and departmental autonomy.

This comprehensive checklist guides teams through the entire process of deploying Granola in a production or enterprise environment. It covers critical phases including plan selection, security hardening (SSO, data retention), integration setup (Slack, Notion, CRM), pilot testing, and post-launch monitoring, ensuring a smooth and successful organizational rollout.

This comprehensive guide outlines best practices for securing Granola meeting data. It covers critical compliance standards, including SOC 2 and GDPR, and details technical controls such as AES-256 encryption, TLS 1.3 transmission, and robust configuration of SSO and data retention policies for enterprise use.

This skill provides comprehensive methods for managing the entire data lifecycle of LLM observability platforms like Langfuse. Functions include exporting detailed traces and scores, configuring retention policies (e.g., automatic data cleanup), handling GDPR subject requests (access and erasure), and anonymizing Personally Identifiable Information (PII) for secure analytics. Essential for maintaining regulatory compliance in AI applications.

This skill provides comprehensive patterns for handling sensitive data when integrating with Mistral AI. It covers PII redaction (emails, phone numbers, etc.), implementing data retention policies, and enforcing compliance with global privacy regulations like GDPR and CCPA. Key features include safe API wrappers, dataset sanitization for fine-tuning, and conversation history management with TTL and user erasure rights.

Automated retention calculator guidance within data analytics workflows, assisting with SQL, visualization, BI, and statistical analysis to produce and validate production-ready outputs for retention insights.

Configure GDPR-compliant data handling, PII scrubbing, and data retention policies within Sentry. This skill provides detailed instructions on implementing client-side `beforeSend` hooks and server-side scrubbing rules to securely redact sensitive data (passwords, emails, IP addresses, CC numbers). Essential for achieving compliance with regulations like GDPR, HIPAA, and meeting SOC 2 audit controls.

Implement comprehensive GDPR and CCPA compliance measures within Supabase. This skill guides developers on setting up Row Level Security (RLS) for tenant isolation, managing PII columns, executing right-to-deletion workflows, auditing sensitive data, and establishing automated data retention policies. Essential for any SaaS application handling regulated user data.

This comprehensive workflow automates the entire meeting documentation process. It handles live or recorded audio input, performing accurate transcription with speaker diarization. Subsequently, it leverages advanced AI models to generate detailed summaries, extract key action items, draft follow-up emails, and create structured meeting minutes, significantly enhancing organizational knowledge retention and operational efficiency.

This skill provides comprehensive configuration for Windsurf deployments, managing data transmission controls, retention policies, and regional compliance settings. It ensures adherence to global privacy standards, such as GDPR, by handling data governance and defining code exclusion patterns.

Guides product and growth teams through evaluating whether to scale, test, or kill acquisition channels using unit economics (CAC, LTV, payback), customer quality (retention, NRR), and scalability indicators for data-driven go-to-market budgeting.