Engineering Research & Benchmarks
Enterprise AI Research & Benchmarks
Empirical engineering research and architectural benchmarks conducted by the Esaholic engineering team. All case studies and technical benchmarks include documented methodology, system constraints, failure post-mortems, and reproducible configuration details across dense retrieval, multi-agent swarms, and private model inference pipelines.
Published Architectural Research
9 Case Studies Focus: Hybrid Search, Multi-Agent Swarms & Real-Time ML Open Methodology
Enterprise AI Case Studies & Benchmark Audits
Comprehensive technical blueprints evaluating pgvector hybrid retrieval, LangGraph multi-agent coordination, sub-50ms graph anomaly detection, and zero-disk-retention medical RAG across synthetic evaluation corpora.
Includes: Architecture Diagrams, Code Snippets & Post-Mortems
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