architecture

This article breaks down how to build an Agentic RAG system using LangChain, LangGraph, Cursor, MCP, and more. Get hands-on with practical code examples for AST parsing, vector database integration, and IDE plugins.

I share how Nixtla's TimeGPT (and its potential synergy with Neo4j) is impacting customer behavior analysis in banking. Forget linear regressions, detects anomalies, and predicts future trends.

By 2027, a significant shift in the financial sector will see 70% of leading institutions adopting graph database technology like Neo4j to overcome relational database limitations and enhance customer experiences.

Bank executives, are you leaving revenue on the table? "Beyond Transactions" reveals how mastering product holding ratios, advanced CLV modeling, and AI-powered customer lifetime optimization isn't just theory.

This article tackles the practical hurdles banks face when implementing Data Mesh, a crucial architecture for unlocking the full potential of data and AI. I explore common roadblocks.

A must-read for bank executives, CDOs, and Heads of Data Science. The future of banking hinges on data and AI. It's not just about incremental improvements; it's a fundamental shift.

For bank executives seeking to drive substantial growth in CLV, enhance customer loyalty, and optimize product adoption, AI-driven Customer Lifetime Orchestration offers a compelling solution.

Recommendation systems have become an integral part of our digital lives, influencing our choices from movies and music to products and services. These systems aim to provide personalized recommendations by analyzing user behavior and preferences.

A well-architected CDP can also serve as a foundation for advanced AI applications, such as generative AI and machine learning.