#architecture

Articles tagged with #architecture

DRIFT SHIELD: Behavioral Anomaly Detection for Autonomous AI Systems
TL;DR Autonomous AI systems face a unique threat class: behavioral drift. Malicious prompts, poisoned training data, compromised integrations, and adversarial attacks cause gradual model degradation — the system appears to work but produces corrupted...
Mar 8, 202610 min read
Privacy Proxy Architecture: How to Build Private LLM Inference at Scale
Published: Dev.to | Topic: AI Infrastructure | Length: 5,000+ words TL;DR Privacy proxies sit between users and LLM providers. They're not just frontend scrubbers—they're complete infrastructure stacks: PII detection, request anonymization, metadata...
Mar 8, 202613 min read
Zero-Trust Architecture for AI: Building Privacy-First Inference Pipelines
TL;DR Every time you use ChatGPT, Claude, or any AI service, your request travels directly to the provider's servers. They see your IP, your query, your metadata. They log it. They train on it. Zero-trust architecture means: never send sensitive data...
Mar 8, 202611 min read12
Building Privacy-First AI Proxies: Architecture, Costs, and Compliance
TL;DR Every API call to OpenAI, Claude, or Groq is a surveillance event. Your prompts contain secrets—customer names, internal emails, API keys, patient records, financial data. Your IP address is logged. Your usage patterns are profiled. Privacy-fir...
Mar 8, 20269 min read
Zero-Log LLM Proxy Architecture for Healthcare: Designing Enterprise AI Systems That Don't Leak Patient Data
TL;DR: Healthcare organizations want to use Claude/ChatGPT for clinical analysis but fear HIPAA violations—providers log prompts forever. Zero-log proxy architecture (scrub PII → proxy → restore) solves this: users get AI capabilities, patient data n...
Mar 8, 20263 min read
Privacy Proxy Architecture: Multi-Provider Inference Without Data Leakage
TL;DR A privacy-first LLM proxy must route requests across multiple providers (OpenAI, Anthropic, Groq, Gemini, Mistral) without exposing user data to any single point of failure. This requires: (1) request transformation to normalize across incompat...
Mar 8, 202611 min read