AI Architecture Comparison Hub
Neutral, architect-led decision rubrics for enterprise AI. Cost benchmarks, switching costs, when-each-wins criteria. No vendor sponsorship.
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RAG vs Fine-tuning
TL;DR: RAG wins ~60% of the time. Fine-tune for style/format, not facts.
6-dimension rubric covering cost, latency, freshness, accuracy, and the hybrid pattern that wins most enterprise use cases.
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OpenAI vs Anthropic vs Open Source
TL;DR: Multi-vendor with a gateway is the architecture; single-vendor is the risk.
Vendor matrix: pricing, latency, capability, compliance, vendor stability. Multi-LLM gateway pattern.
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Vector Databases
TL;DR: Postgres+pgvector for <10M docs, dedicated vector DB above.
Pinecone, Weaviate, Qdrant, pgvector, OpenSearch — when to use each, switching costs, hybrid retrieval.
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Build vs Buy Enterprise AI
TL;DR: Hybrid (buy LLM, build orchestration) most common at scale.
7-dimension rubric with 3-year TCO modeling for buy/build/hybrid paths. Hidden costs most buyers miss.
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Custom AI vs Microsoft Copilot Studio
TL;DR: Copilot for M365-heavy + low-stakes, custom for regulated + revenue-bearing.
Where Copilot Studio fits, where custom wins, and the migration cost in either direction.
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