Insights
Engineering notes from production AI.
Practical lessons from systems we have designed and shipped: architecture decisions, evaluation, cost control and the mistakes worth avoiding.
All articles
6 min read
How to Choose a RAG Development Company: A Buyer's Checklist
Twelve questions to ask before you hire a RAG development company, covering proof, evaluation, retrieval, security, ownership and support, plus the red flags.
9 min read
Building an Enterprise Legal AI Platform: Triple Search, Anonymization and RAG
How I built Datagreffe Justice: triple-search retrieval over 50,000+ court decisions, 98% PII detection, 100% compliance and sub-2-second cited answers.
6 min read
LangGraph vs CrewAI for Enterprise AI Agents: How I Choose
A practical comparison from shipping both: when LangGraph's explicit state and interrupts win, when CrewAI's role-based crews win, and when to use neither.
6 min read
Multi-Jurisdiction PII Anonymization for Legal Documents with LLMs
How I approach anonymizing court decisions across jurisdictions with LLMs: layered detection, consistent pseudonyms, stricter safeguards and measured accuracy.
6 min read
The Model Context Protocol (MCP) Explained for Business Leaders
What the Model Context Protocol is, why it became the standard way to connect AI to business systems, and the governance questions to settle before rollout.
7 min read
RAG Development Cost in 2026: What Actually Drives the Price
What makes a RAG system cost what it does: data quality, retrieval, security, evaluation and scale, and how to scope a build so the budget lands where it matters.
6 min read
Triple Search: Why Legal RAG Needs Keyword, Semantic and Metadata Retrieval
Why vector search alone fails legal research, and how fusing keyword, semantic and metadata search retrieved 15% better across 50,000+ court decisions.
6 min read
Building a Production Voice AI Pipeline: WhatsApp, Whisper and Prompt Caching
Lessons from a 24/7 WhatsApp voice pipeline with Whisper, Claude replies and the prompt caching setup that cut input-token costs by roughly 90%.
7 min read
Building a Human-in-the-Loop Multi-Agent Platform with LangGraph and MCP
How I designed an agent platform on LangGraph with Model Context Protocol tools, persistent checkpointed memory and human approval before sensitive actions.
5 min read
RAG vs Fine-Tuning: When to Use Which
A practical breakdown of when retrieval-augmented generation beats fine-tuning and vice versa, based on production experience building both kinds of systems.
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