Learn - Share - Innovate - Elevate
DataOps Newsletter Volume 26 - Febaury 2026
Learn
Blogs:
Love to share the blog I curated best of my knowledge.
In Person Events:
https://www.meetup.com/awsugblr/events/313253190/
Online Events:
Meetup:
Share
Handson Session - Supercharging Agents with Built-in Tools: Code Interpreter
Happy to share that our DataOps Labs Community Leaders Session 2
Ranjini G | Vijayalakshmi B | Chandika
started their knowledge sharing Journey on
AWS Certified Machine Learning Engineer Associate (MLA-C01) - Session 2
Innovate
Let us Build —
Cease & Desist Document Processing System
Follow this Guide for reference - https://github.com/jayyanar/agentic-ai-training/tree/main/day5/capstone-project/guides
Successful Solution leveraging any AWS technologies will be provide 100$ Credits
🎯 Project Overview
Business Problem
Enterprises receive Cease & Desist requests from customers who want to stop all direct communication. Currently, human agents must manually read scanned PDF documents to determine if each request is legitimate, which is:
⏱️ Time-consuming and slow
💰 Expensive (requires human review)
❌ Error-prone (human fatigue, inconsistency)
📈 Not scalable (volume increases over time)
Your Mission
Build an intelligent multi-agent system that automates the classification and processing of Cease & Desist documents, reducing manual effort while maintaining accuracy and compliance.
Elevate
Podcast Title: From Automation to Agentic AI: Solving the Determinism Paradox in Financial Services
By: Ayyanar Jeyakrishnan
This episode explores the strategic shift from traditional rule-based automation to Agentic AI in the financial sector, where autonomous software agents manage complex, multi-step workflows across GRC, AML, and credit risk. It addresses the industry’s core technical paradox: reconciling the probabilistic, non-deterministic nature of large language models (LLMs)—including risks like hallucinations—with the strict regulatory demands for determinism, auditability, and traceability. Leading institutions are resolving this through hybrid architectures that layer automated reasoning engines and knowledge graphs over foundational AI models, grounding decisions in structured, verifiable data to ensure mathematical certainty. Ultimately, this transformation elevates the workforce from routine task execution to high-value cognitive orchestration, building a compounding institutional memory that becomes a sustainable competitive moat.
Strategic shift → From rule-based automation to Agentic AI
Core paradox → Probabilistic AI vs. Deterministic regulation
Solution → Hybrid architecture + reasoning + knowledge graphs
Impact → Cognitive orchestration and compounding institutional intelligence
Disclaimer “AI Generated Podcast” but content curated by me
Thanks for TRESIDUS for sponsoring this blog