Cover image

When Markets Dream: The Rise of Agentic AI Traders

Opening — Why this matters now The line between algorithmic trading and artificial intelligence is dissolving. What once were rigid, rules-based systems executing trades on predefined indicators are now evolving into learning entities — autonomous agents capable of adapting, negotiating, and even competing in simulated markets. The research paper under review explores this frontier, where multi-agent reinforcement learning (MARL) meets financial markets — a domain notorious for non-stationarity, strategic interaction, and limited data transparency. ...

November 5, 2025 · 3 min · Zelina
Cover image

Agents with Interest: How Fintech Taught RAG to Read the Fine Print

Opening — Why this matters now The fintech industry is an alphabet soup of acronyms and compliance clauses. For a large language model (LLM), it’s a minefield of misunderstood abbreviations, half-specified processes, and siloed documentation that lives in SharePoint purgatory. Yet financial institutions are under pressure to make sense of their internal knowledge—securely, locally, and accurately. Retrieval-Augmented Generation (RAG), the method of grounding LLM outputs in retrieved context, has emerged as the go-to approach. But as Mastercard’s recent research shows, standard RAG pipelines choke on the reality of enterprise fintech: fragmented data, undefined acronyms, and role-based access control. The paper Retrieval-Augmented Generation for Fintech: Agentic Design and Evaluation proposes a modular, multi-agent redesign that turns RAG from a passive retriever into an active, reasoning system. ...

November 4, 2025 · 4 min · Zelina
Cover image

Serverless Bulls and Bears: How One Developer Built a Real-Time Stock Analyst with Zero Infrastructure

Most real-time financial systems rely on deep stacks of infrastructure, from custom APIs to cloud VMs and high-frequency data ingestion pipelines. But what if a single developer could deploy a daily-updating, AI-powered stock analysis engine without a single server? That’s exactly what Taniv Ashraf set out to do — and accomplished — in his recent case study on a fully serverless architecture using Google Gemini, GitHub Actions, and static web hosting. The result is an elegantly simple yet conceptually powerful demonstration of how qualitative LLM analysis and automation tools can replace entire categories of financial tooling — if wielded strategically. ...

July 15, 2025 · 4 min · Zelina