The Honest Parts: Residency, Tenancy, and Saying No
You cannot reliably detect where an LLM runs inference. Any product claiming otherwise is overclaiming. This is about the Aegis design decisions th...
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Guardrails That Tell You the Truth About Streaming
A guardrail that silently runs at reduced fidelity is worse than no guardrail, because you've stopped watching. The hardest design problem in the A...
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Rebuilding an AI Gateway as a Framework, Not a Product
The first version of Aegis worked, and that was the problem. Every governance feature was hardcoded into one request path, so every change was a co...
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Advanced RAG: Hybrid Search with Sparse and Dense Retrieval Plus Cross Encoder Reranking
Learn how to upgrade your RAG system with hybrid search combining sparse (BM25) and dense (vector) retrieval, enhanced with cross encoder reranking...
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Building Aegis An Enterprise AI Gateway
How to build an enterprise-grade AI gateway: a provider-agnostic LLM routing layer with deterministic compliance, PII protection, and intelligent c...
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Building a Local RAG System for Document Question Answering
A practical guide to building a retrieval-augmented generation system for document question answering using local LLMs. Learn how to overcome outda...
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