AI/ML●●Solid
I built proxy that keeps RAG working while hiding PII
Consistent pseudonymization beats redaction when RAG embeddings must survive.
Big BrainSolve My Problem
rohansx
403mo ago
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Sentinel – Go LLM Proxy with 13ms Semantic Cache and PII Scrubbing
by ChipShotz·Mar 4, 2026·1 point·1 comment
AI Analysis
●MidSlickCrowd Pleaser
Multi-model LLM router with semantic cache, but caching+fallback already exist (Anthropic, LangSmith, Unify).
Strengths
- •Zero-refactor integration: drop-in base_url replacement works with OpenAI SDK and LangChain—genuine ease-of-use win
- •Semantic caching under 50ms with zero token cost on cache hits addresses real cost friction for repeated queries
- •PII scrubbing + prompt injection blocking bundled as toggles, not separate products or dependencies
Weaknesses
- •Semantic caching (13ms claim vs 50ms in copy) and multi-model routing are table-stakes commodities—Anthropic, LangSmith, Unify, Baseten all do this
- •No evidence of differentiation: tokenization methodology, cache recall accuracy, or fallback routing logic not disclosed—appears to be orchestration of existing services
Category
Target Audience
AI app developers and teams managing multi-model inference pipelines at scale
Similar To
Anthropic Models API · LangSmith · Unify.ai
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