cloudwright
AI-powered cloud architecture - describe infrastructure in natural language, get Terraform, cost estimates, and compliance reports
AI Architecture and Engineering
I work on the layer between language models and production: retrieval, evaluation, cloud infrastructure described in natural language. Mostly Python and TypeScript, mostly things that have to actually ship.
AI-powered cloud architecture - describe infrastructure in natural language, get Terraform, cost estimates, and compliance reports
Benchmark 19 retrieval architectures (vector, contextual, QnA, knowledge graph, LightRAG, hybrid, RAPTOR, PageIndex, BM25, metadata-filtered, temporal, rerank, HyDE, multi-query, late-interaction, SPLADE, agentic, plus two quantum-inspired rerankers) on your own docs. Citable evidence bundles, bootstrap CIs, significance tests.
Benchmark harness measuring AI coding tool+workflow performance, not just model capability. 100 tasks, sigmoid scoring, 12 capability dimensions, gap analysis.
Philippine civic data as MCP tools: the full PSA OpenSTAT statistical catalog, hazards, weather, procurement, elections, and one-call area profiles. 41 tools, no API keys.
Air-gapped AI customer support for enterprise. On-device LLM, offline-first, config-driven. 7 industry templates.
Approve, steer, and stop every Claude Code agent from one local page.
Twenty memory strategies through one lifecycle, one judge, one model. A 30-line vector store outranks every funded vendor SDK.
A human-calibrated Sentinel-2 canopy model for 17 NCR LGUs, 2019 to 2026, scored F1 0.78 against hand-labeled pixels.
Land subsidence for seven cities from Sentinel-1 InSAR, 2016 to 2025, mapped next to where the floods actually hit.