A proactive content moderation and detection stack that identifies AI-generated content, deepfakes, and potential violations before regulators mandate platform liability. Combines detection with creator protection tools.
How the workflow runs
01pangram-4-and-ai-image-detection-model — Scan all uploaded images to detect AI-generated content with high precision
02ai-video-detector — Analyze video content to identify AI-generated deepfakes and synthetic media
03ai-likeness-detection — Protect verified creators by scanning for unauthorized deepfakes of their likeness
04substack-content-detection-tool — Flag AI-generated text content for editorial review or labeling
05gemini-omni — Analyze multimodal content (text, image, video combined) to detect sophisticated AI-generated campaigns
As AI-generated content platforms face regulatory pressure, this stack implements the content labeling and detection systems that regulators will eventually mandate. Getting ahead of regulation protects platforms from liability while maintaining creator trust. The multi-modal approach catches sophisticated AI content that single-method detection misses.
Total (5 tools)$19.99/mo
For Corporate legal counsel managing AI deployment risk
A defensive stack that monitors AI system outputs, detects potential regulatory violations, and auto-generates compliance documentation before regulators come knocking. Combines real-time content analysis with automated anonymization and audit trails.
How the workflow runs
01anonymizer-ner — Automatically detect and redact PII from all AI-generated outputs before storage or distribution
02vulnhunter — Scan AI system prompts and responses for potential safety vulnerabilities or jailbreak attempts
03gemini-agent — Generate compliance reports and flag potential regulatory issues across enterprise AI deployments
04gsc-mcp-server — Track public-facing AI content performance and detect reputational risks
05copilot-in-power-bi — Build real-time compliance dashboards showing AI usage patterns and risk metrics
As eight states sue OpenAI and regulatory scrutiny intensifies, this stack creates an automated compliance moat. Legal teams can demonstrate proactive governance, and enterprises can deploy AI with confidence knowing every interaction is logged, sanitized, and auditable. The combination of NER anonymization with vulnerability scanning catches issues before they become lawsuits.
Total (5 tools)$260/mo
For AI safety engineer at an enterprise deploying autonomous agents
Monitor deployed AI systems for signs of alignment failure, goal drift, or unexpected autonomous behavior before they trigger the first major enterprise AI shutdown. Combines agent monitoring with decision auditing and human-in-the-loop controls.
How the workflow runs
01inspect-ai — Continuously evaluate agent outputs against safety benchmarks and alignment criteria
02decision-1 — Route agent decisions to human review when confidence scores fall below safety thresholds
03qwengyre — Use reinforcement learning framework to detect when agents deviate from intended long-horizon plans
04gemini-3-5-flash — Deploy fast agentic model with computer use for controlled testing of agent behaviors in sandbox
05buzz — Alert human teams in real-time when agents exhibit unexpected communication or behavior patterns
The prediction of AI alignment failures triggering enterprise system shutdowns demands proactive monitoring. This stack implements defense-in-depth: evaluate outputs, audit decisions, monitor long-term behavior, test in sandboxes, and alert humans. Organizations using this avoid becoming the cautionary tale that triggers industry-wide panic and over-regulation.
Total (5 tools)Free
For Research director preparing for enterprise AI procurement
Mirror Anthropic's explosive growth trajectory by building a research infrastructure that combines frontier reasoning models with rigorous evaluation frameworks. Focuses on alignment-safe outputs and academic-grade analysis.
How the workflow runs
01rosalind-academic-plan — Access ChatGPT Enterprise free tier for university research labs to establish baseline capabilities
02claude — Deploy Claude for complex reasoning tasks requiring long-context analysis and alignment-conscious outputs
03gemini-4-argon — Use Google's most capable frontier model for advanced coding and technical problem-solving
04inspect-ai — Evaluate all model outputs against rigorous safety and accuracy benchmarks
05elicit — Cross-reference AI-generated insights against peer-reviewed research literature
06notebooklm — Ground all research conclusions in uploaded source documents to prevent hallucination
As Anthropic heads toward a $100B+ IPO, enterprises need to understand what makes their approach successful. This stack replicates the safety-first, research-grade methodology that's driving their growth. By combining Claude's alignment focus with rigorous evaluation tools, organizations can build AI systems that survive regulatory scrutiny and deliver enterprise-grade reliability.
Total (6 tools)$17.99/mo
For Operations director at a mid-market company evaluating automation platforms
A future-proof automation stack that hedges against the predicted M&A consolidation in the no-code space. Combines the strengths of multiple platforms with AI-native routing and failover to avoid vendor lock-in.
How the workflow runs
01omniroute — Route automation requests across multiple AI providers with automatic fallback if one service is down
02zapier — Connect consumer and SaaS apps for simple trigger-action workflows
03make — Build complex visual automations requiring branching logic and data transformation
04gemini-agent — Deploy enterprise AI agents for Google Workspace automation that Zapier and Make don't natively support
05agent-native-cloud — Scale high-volume agent workflows on enterprise-grade infrastructure
With no-code platforms racing toward M&A consolidation, this stack avoids single-vendor risk. OmniRoute ensures you can switch providers without rewriting workflows, while combining Zapier's breadth with Make's power and Gemini Agent's enterprise capabilities creates a best-of-breed approach. When the consolidation wave hits, you're positioned to negotiate rather than migrate in panic.
Total (5 tools)$31.99/mo
For Security engineer at a company using open-weight models
A security-first development workflow for organizations deploying open-source AI models. Scans codebases for vulnerabilities, tests models for adversarial robustness, and maintains air-gapped deployment options to address export control concerns.
How the workflow runs
01spiral-coder — Build and test AI features entirely on local hardware, ensuring no code leakage to cloud providers
02vulnhunter — Hunt for exploitable vulnerabilities in the AI-generated code before deployment
03laguna-s-2-1 — Use the secure open-weight coding model for generating additional test cases and security patches
04tabnine — Enable privacy-first code completion that learns from your secure codebase without cloud transmission
05inspect-ai — Rigorously evaluate model outputs for safety, bias, and adversarial resistance
With open-source AI facing potential export controls and licensing requirements, this stack lets teams prove security due diligence. Spiral-coder's local-first approach combined with VulnHunter's exploit detection creates a defensible security posture. Perfect for defense contractors, government agencies, and enterprises in regulated industries who need open models but can't risk security breaches.
Total (5 tools)$12.1/mo
For Smart home enthusiast preparing for the consumer robotics wave
Build the autonomous home assistant infrastructure before consumer robotics achieve mass adoption. Combines local LLM control with voice interfaces and cross-device orchestration to control robots, sensors, and traditional smart home devices.
How the workflow runs
01richard-companion — Deploy self-hosted voice-controlled home automation powered by local LLM
02enviouswispr — Enable sub-second on-device voice dictation for issuing commands to AI systems
03ailyn — Orchestrate AI intelligence across multiple devices and edge computing nodes in the home
04walkers2 — Integrate humanoid service robot for physical tasks once consumer models become available
05agent-native-cloud — Scale home AI infrastructure as more robotic and IoT devices come online
Physical AI and robotics are predicted to achieve breakthrough consumer adoption through home automation. This stack positions early adopters to control the entire ecosystem: voice input via EnviousWispr, local reasoning via Richard, cross-device orchestration via Ailyn, and future robot integration via WalkerS2. When consumer robots hit shelves, you'll have the control plane ready.
Total (5 tools)Free
For Product manager at an AI company pre-empting regulatory mandates
Build the youth-focused safety features and age verification systems that major AI companies will soon be forced to implement. Combines identity verification with content filtering and usage monitoring.
How the workflow runs
01ax-platform — Implement AI governance framework with audit trails and safety controls for organizational AI transitions
02anonymizer-ner — Detect and protect minor PII in conversations, preventing data collection that violates children's privacy laws
04google-gemini — Use Gemini's multimodal capabilities to detect inappropriate content in images shared by young users
05apple-intelligence — Leverage on-device AI to implement privacy-preserving age verification without collecting sensitive data
Regulatory mandates for youth safety are coming whether companies like it or not. This stack implements privacy-preserving protections that satisfy regulators without creating invasive surveillance. The combination of local processing (Apple Intelligence) with content filtering and NER anonymization creates defensible youth safety without building creepy age-tracking databases.
Total (5 tools)$20/mo
Generated weekly by Claude from the tools directory and current trends · costs computed from tracked pricing
