Simor

Data Infrastructure for Production AI

Practical writing on AI data engineering, feature stores, and the infrastructure choices that determine whether AI systems work in production.

Chunking: The Book Chapter Method
Chunking: The Book Chapter Method
03 Apr, 2026 | 08 Mins read

You have a 600-page book on regulatory compliance. You do not read it front to back. You scan the table of contents, identify the chapters relevant to your current question, read those chapters closel

Tool Calling and Function Calling: Connecting AI to Enterprise Systems
Tool Calling and Function Calling: Connecting AI to Enterprise Systems
28 Mar, 2026 | 14 Mins read

A language model that only generates text is not enough for most enterprise problems. The real value emerges when an AI system can look up your customer record, check inventory levels across warehouse

Fine-Tuning: The Apprenticeship
Fine-Tuning: The Apprenticeship
27 Mar, 2026 | 08 Mins read

A master woodworker takes on an apprentice. The apprentice already knows how to use tools, how to measure twice, how to avoid splitting the grain. What the apprentice needs is not general woodworking

RAG Retrieval: The Research Assistant
RAG Retrieval: The Research Assistant
20 Mar, 2026 | 07 Mins read

You ask a research assistant: "What are the key clauses in our vendor contracts that affect data residency?" The assistant does not know off the top of their head. They go to the document store, find

AI Enablement Programs: Building Organizational Capability, Not Just Technology
AI Enablement Programs: Building Organizational Capability, Not Just Technology
19 Mar, 2026 | 11 Mins read

A technology company built an impressive AI platform. They had GPU clusters, fine-tuning pipelines, evaluation frameworks, and a growing model registry. They opened access to any team that wanted to u

Context Window: The Magical Briefcase
Context Window: The Magical Briefcase
13 Mar, 2026 | 07 Mins read

Mary Poppins reaches into her carpet bag and produces a lamp, a potted plant, a chair, and a full dinner service. The bag is impossibly large on the inside. But Mary does not reach past the top layer.

Feature Stores for AI: The Missing MLOps Component Reaching Maturity
Feature Stores for AI: The Missing MLOps Component Reaching Maturity
12 Mar, 2026 | 11 Mins read

A recommendation system team built their tenth model. Each model required feature engineering. Each feature engineering project started by copying code from the previous project, then modifying it for

Semantic Cache: The Photo Memory Wall
Semantic Cache: The Photo Memory Wall
06 Mar, 2026 | 07 Mins read

You have a wall covered in photos. You are looking at one from a beach trip. Nearby are other beach photos, vacation snapshots, summer memories. Not identical shots, but related moments. The clusterin

Case Study: Building a Production AI Knowledge Layer for Financial Services
Case Study: Building a Production AI Knowledge Layer for Financial Services
01 Mar, 2026 | 10 Mins read

A regional bank's investment research team spent 60% of their time gathering information and 40% doing analysis. Analysts had to search through regulatory filings, internal research memos, market data